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Copyright © 2016, Sirona Genomics, Inc. All rights reserved.

Software User Guide v2.1

Advanced NGS HLA Genotyping Software

SR-790-00017

MIA FORA Software Ver.2.1

LC1619.2 (06/16) Copyright © 2016, Sirona Genomics, Inc. All rights reserved. of 90

Copyright Notice

This documentation and the MIA FORA NGS software are the confidential information of and are

copyrighted, © 2015, by Sirona Genomics, Inc. All rights are reserved. No part of this documentation or

the software may be reproduced, copied, displayed, transmitted, modified or used without the prior written

permission of Sirona Genomics, Inc.

Trademarks

MIA FORA is a trademark owned by Sirona Genomics, Inc.

All other trademarks and registered trademarks are the property of their respective owners.

All use of the MIA FORA software and this documentation are subject to the terms of the MIA FORA

License Terms and Conditions available at www.immucor.com/miaforasoftwareterms. BY USING THE

MIA FORA SOFTWARE AND/OR THIS DOCUMENTATION, YOU ACKNOWLEDGE THAT YOU HAVE

READ, UNDERSTAND AND AGREE TO BE BOUND BY SUCH TERMS AND CONDITIONS AS THEY

MAY BE UPDATED FROM TIME TO TIME.

MIA FORA NGS Software has been CE marked in the European Union only for IVD use with MIA FORA

NGS HLA Typing Kit Part Number SR-800-10377.

http://www.immucor.com/miaforasoftwareterms



Table of Contents

1. Introduction to MIA FORA NGS ................................................................................ 4

1.1 Genotyping Strategy ................................................................................................................ 4

1.2 Competitive Alignment to Reference Alleles .......................................................................... 5

1.3 Consensus Sequence Computation by Phasing .................................................................... 6

1.4 Central Read Coverage ............................................................................................................ 7

1.5 Computed Genotypes .............................................................................................................. 8

1.6 Smart Flagging System ........................................................................................................... 8

2. Getting Started ........................................................................................................ 10

2.1 Logging In .............................................................................................................................. 10

2.2 Preference Panel .................................................................................................................... 13

2.3 User Management .................................................................................................................. 14

2.4 Disclaimer Information .......................................................................................................... 14

2.5 Laboratory Information .......................................................................................................... 15

2.6 Date and Time Format Information ....................................................................................... 15

2.7 Report Format ........................................................................................................................ 16

2.8 Review Options ...................................................................................................................... 16

2.9 Transferring Files between server and user’s machine using VNC Viewer ........................ 17

3. Projects Window ..................................................................................................... 19

3.1. Create a new project .............................................................................................................. 20

3.2. Launch data analysis ............................................................................................................. 23

4. Statistics Window .................................................................................................... 25

5. Review Window ....................................................................................................... 29

5.1. Block A: Sample Information ................................................................................................ 29

5.2. Block B. Genotype Table ....................................................................................................... 30

5.3. Block C. Variants, LD Suggestion, and Smart Guide ........................................................... 36

5.4. Block D. Allele Candidate Table ............................................................................................ 38

5.5. Block E1. Coverage Plots ...................................................................................................... 42

5.6. Block E2. Alignment Browsers ............................................................................................. 44

5.7. Block E3. Reference Alignment ............................................................................................ 48

5.8. Block F. Contig Alignment Browser...................................................................................... 55

6. Summary Window ................................................................................................... 62

7. Auxiliary Tools......................................................................................................... 63

Appendix A: Software Color Codes Description ....................................................... 72

Appendix B: Glossary ................................................................................................. 75

Appendix C: Best Practices ........................................................................................ 77

Appendix D: Clickable Functions ........................................................................... 79

Appendix E: Additional Resources ............................................................................ 81

Appendix F: Third Party Libraries’ Licenses ............................................................ 82



1. Introduction to MIA FORA NGS

MIA FORA NGS software delivers HLA typing information for the major Class I (HLA- A,

B, and C) and Class II (DPA1, DPB1, DQA1, DQB1, DRB1 and DRB3/4/5) genes.

Genotypes are computed from massive, paired-end sequencing reads derived from the

Illumina Next Generation Sequencing (NGS) platform. The software provides accurate

and phase defined unambiguous HLA genotype information.

Figure 1-1: HLA Gene region showing relative locations of HLA Class I and Class II genes

HLA genes are one of the most complex regions of the human genome and the

accurate and complete sequence of the HLA genes is an enormously complex

endeavor. MIA FORA NGS software has been designed to take full advantage of the

NGS and provide to users a simple-to-use tool to make the right decision for an

unambiguous HLA typing call.

The software is designed to correctly identify HLA genotypes based on exon sequence.

Special consideration is given to the most highly sequenced exon regions, i.e. exons 2-

3 of Class I genes and exon 2 of Class II genes. At this time, less emphasis has been

placed on identifying intron variants.

MIA FORA NGS software includes an intuitive graphical user interface (GUI) and

complies with the requirements established by the HLA community. It provides to users:

first, the accurate and unambiguous HLA genotypes based on the latest IMGT

nomenclature and second, the complete phased sequence covered by the targeted

primers used to interrogate the HLA genes.

1.1 Genotyping Strategy

MIA FORA NGS software combines two complementary informatics strategies to

analyze each sample and then makes genotyping calls for target HLA genes using a

computed confidence score. The first strategy ranks computed allele candidates based

on mapping metrics. Coverage is calculated from competitive alignment of paired-end

NGS sequence reads with all HLA reference sequences in the latest IMGT database

and reference sequences produced by Sirona Genomics. The second strategy utilizes

Phasing by Dynamic Program to assemble reads and construct phased assembled

sequences. The approach is illustrated in Figure 1-2.

Class II Class III Class I

DP DQ DR B C A



Figure 1-2: MIA FORA NGS genotyping strategy. Two complementary strategies are employed to compute the best fit to HLA reference alleles and resolve consensus sequences. The left side is mapping. Paired end reads are mapped using competitive alignment algorithm to rank candidate alleles. The right side is phasing. Starting with Paired end reads, these reads will mapped and go

through local assembly, then phase resolution to construct phase resolved consensus.

1.2 Competitive Alignment to Reference Alleles

Mapping is used to rank candidate alleles based on competitive alignment of paired end

sequence reads with all HLA reference sequences to make sure that we capture all

SNPs and structural variance. The reference database includes all HLA reference

sequences in the latest version of IMGT HLA database and some generated through

cloning and sequencing at Sirona Genomics. Two types of internally generated

reference sequences are used in this tool: cloned and sequenced alleles and in silico

sequences.

1) Cloned and sequenced alleles:

Cloned sequences are derived from individual long-range PCR products amplified from

IHWG cell lines and samples. Thus, these sequences represent alleles that were



completed by filling in missing intron and exon sequences. Cloned sequences in the

database are indicated with one of three suffixes: e, v or x.

e: Sequences with the suffix e (e1, e2, etc.) are those with new intronic sequence

not represented in the IMGT database. The vast majority of cloned sequences

are of this type.

v: Sequences with the suffix v (v1, v2, etc.) are a small subset of cloned alleles

that contain new intron variants relative to existing genomic sequences in the

IMGT database.

x: Sequences with the suffix x (x1, x2, etc.) are a small subset of cloned alleles

that contain new exon variants. The suffix is added to the closest known

reference sequence but if confirmed by IMGT the allele name will change.

2) In silico sequences:

Many IMGT reference sequences contain partial exon sequences. To facilitate data

analysis, the closest complete exon was copied to fill in the gaps in IMGT reference

sequences with an incomplete exon. The suffix i (i1, i2, etc.) is used to identify those

computationally filled sequences.

The extensions used in the naming of the reference sequences are to inform the user

about the reference sequence that was used to make the allele assignment. The

coverage alignment can be viewed for the IMGT and corresponding extended reference

sequences. In all cases where the sequence has either been determined by actual

sequencing or in silico extension of reference sequences, the HLA type can be reported

in the accepted IMGT format without the extensions that are used for naming these

extended sequences.

1.3 Consensus Sequence Computation by Phasing

A Dynamic Phasing algorithm generates one or two phased consensus sequences

(contigs) by de novo assembly of mapped, paired-end sequences. In the same

assembly process, polymorphic sites are identified where the minor allele frequency

exceeds a threshold of 0.2.

Once polymorphic sites are identified, Phased Resolved Consensus sequences

(phased contigs) are built based on sequence assembly and polymorphic linkage.

Following Dynamic Phasing, the Phased Resolved Consensus sequences are aligned

to the HLA allele database to determine the best fit. Consensus Alignment provides an

independent check of the genotype call. Novel alleles are identified as discrepancies

from the exon sequence of the reference alleles.



1.4 Central Read Coverage

Central read coverage was developed to ensure base calls can be made with a high

degree of confidence. Central reads (Figure 1-3) are empirically defined as mapped

reads for which the ratio between the length of the left arm and that of the right arm

related to a particular point is between 0.5 and 2. When reads are mapped onto a

correct reference sequence, they form a continuous tiling pattern over the entire

sequenced region. However, when reads are mapped onto an incorrect reference

sequence, they form a staggered tiling pattern at some positions of the sequenced

region. To quantify this difference between the two alignment patterns, the numbers of

“central reads” are counted for any given point. Central Read Coverage ensures that

potentially mismatched reads are excluded.

Figure 1-3: Central reads of an anchor point are defined as mapped reads, where the ratio between the length of the left arm and that of the right arm related to a particular point is between 0.5 and 2. The left side of plot shows the mapping pattern of reads onto two correct references and one incorrect reference. The incorrect reference has a mosaic pattern at the two different positions between two correct reference sequences. From the plot, it can be seen that reads with an even tiling pattern are mapped to the correct reference sequence while reads mapped to the incorrect reference sequence have an uneven, staggered pattern. The coverage plot graphs on the right

side illustrate an example where central read coverage can distinguish a correct reference from an incorrect reference, while regular coverage cannot.



1.5 Computed Genotypes

For each gene, confidence scores are used to identify the best matching alleles in the

reference database. Key coverage statistics are combined in a proprietary algorithm to

calculate confidence scores and select the top computed alleles for each gene. The

best allele candidates are then selected as the computed genotype call. Key

components of the confidence score are illustrated in Figure 1-4Error! Reference source

not found.. Coverage statistics such as number of mapped reads and minimum

coverage are calculated mapping the paired end reads to the HLA reference allele

database. Phase-resolved consensus is determined through sequence assembly and

polymorphic linkage. Candidate pairs are also evaluated and included in the calculation.

Figure 1-4: Key components of confidence scores used to rank computed alleles. Confidence

scores are calculated using a combination of mapping, phase-resolved consensus, central read coverage, and candidate pair metrics.

1.6 Smart Flagging System

A Smart Flagging System was developed to display different information about the

genotypes for all the genes in the selected sample. Above each allele is a shape

indicator. Symbols for each of the indicators are:

Triangle - confidence score

Diamond - common or well-documented (CWD) allele

Pentagon – overwritten automatic call

Hexagon - consistency with linkage disequilibrium data

Circle with a question mark or exclamation mark – Question mark means

discordant calls between the competitive alignment (EM) and the phased

resolved consensus. An exclamation mark indicates that the allele is in the

Confidence Score

Mapping

Central Coverage

Phase Resolved Consensus

Candidate Pair



double-check list which requires careful manual review. The double-check list

includes alleles that can have issues in sample prep, sequencing or data

analysis. The circle will turn green after review and confirmed by the user.

Alleles on the double-check list include: A*02:10, DRB1*04:13, DRB1*15:01:17,

DRB1*15:11, DRB1*16:09:01.

PC - the number of phased resolved de novo contigs.

See the legend in Figure 1-5 for further explanation of each shape.

Figure 1-5: Flags (colored shapes) are used to depict each predicted genotype status. Indicators for confidence score (green triangle > blue > red > gray) green is the highest confidence score

and grey is the lowest confidence score, common or well-documented allele (green diamond) or not (amber diamond), whether a call has been edited (amber pentagon) or not (green pentagon),

whether a call is consistent with linkage disequilibrium data (green hexagon) or not (amber hexagon), and whether special review is required (amber circle with question mark), indicating a

potential novel allele in the exon sequence. PC: the number of phased contigs. If the count of contigs is different from the number of alleles of the corresponding locus, it will show amber color

in the circle. Otherwise, it is green color



2. Getting Started

The MIA FORA NGS software is an accessory for use with Illumina next generation

sequencing (NGS) data obtained by sequencing libraries prepared by targeted

amplification of the intended genes using the MIA FORA NGS HLA typing kit. Due to the

complex nature of HLA Testing, qualified laboratory personnel must review any result to

assure accuracy.

The software can be accessed through either a VNC Viewer connection or direct access

through monitor and keyboard attached to the server. To access the server directly, log

in using KDE plasma workspace mode instead of GNOME classic mode:

1. Turn ON the server and wait till logon screen appears. Once logon screen

appears, click on User Account to log in.

2. Click on Username and enter the Password. Before clicking on the Sign-in

button, click on the Gear icon next to the Sign-In button and select “KDE plasma

workspace” from the list. Then click on the Sign In button to login to Red Hat

Linux 7.

3. Follow the instructions to log in and access MIA FORA NGS software as

described below.

2.1 Logging In

VNC viewer can be downloaded from https://www.realvnc.com/download/viewer/.

Follow the instructions on the website to install VNC Viewer on your computer.

Open the VNC Viewer application by clicking on the VNC icon. Choose the appropriate

VNC Server name or IP address and click on Connect as shown in Figure 2-1. At the next

prompt, enter your unique login name and password.

Figure 2-1: VNC login screen. Choose the appropriate VNC Server name or IP address and click on Connect button. At the next prompt enter login credentials. Each user needs appropriate access privileges and a unique username. After three failures, the login will close, and the user will have

to re-open the window and begin the login process again.

After logging into VNC Viewer the remote desktop will be displayed. The VNC Viewer

may be configured for many functions, such as exporting and printing data. The latest

version of the VNC User Guide can be found at

http://www.realvnc.com/products/vnc/documentation/5.2/guides/user/VNC_User_Guide.pdf.

https://www.realvnc.com/download/viewer/



To access MIA FORA NGS software, follow the steps illustrated in Figure 2-2.

Step 1: Hover over the tab at the top of the window to reveal the pull-down menu and

select Full Screen Mode.

Step 2: Click on the MIA FORA icon found on the desktop or in the Quick Start menu.

Step 3: Enter login credentials. The password must be between 4-8 characters and

contain at least one lowercase letter, one uppercase letter and one number.

When logging into MIA FORA software for the first time, labdirector is the default user to

this software. Select labdirector as the username, and type default password:

$1r0naG3n0m1c$ After that, an End User License Agreement window will show up,

which the user needs to read before clicking the Agree button to continue. The

preference panel will show up to allow labdirector to add new user, provide lab

information such as lab contacts, and disclaims. The preference panel continues to

display until all information has been entered.

Figure 2-2: Steps for logging into MIA FORA NGS software from VNC Viewer. First, maximize the

window to fit the computer display. Second, click on the MIA FORA icon either from the Quick Start menu or from the icon on the desktop. Third, enter MIA FORA NGS software login

credentials.



Figure 2-3: End user license agreement dialog shown up when a new user log in first time.

The main window of MIA FORA NGS software, as illustrated in Figure 2-4, will be

displayed after logging in. Return to this page at any time by selecting the Projects icon

in the upper left-hand corner.



Figure 2-4: Main MIA FORA NGS window. Projects that have been created are listed in this main page. Return to this view at any time by selecting the Projects icon. Software commands can be accessed through the side panel and dropdown menus: three drop-down menus at the top of the

home screen with eight shortcuts under Tools; an icon list along the top left side to open data views; eight icons along the bottom left side for additional project commands; two buttons on the

bottom right to create or delete projects. User name, current project, current sample, current gene, storage capacity in percentage, and last action taken will be displayed in the status bar at

the bottom of the window once project is created.

2.2 Preference Panel

A Preference window with user management and account tools will be displayed the

first time a new lab director user logs in. Bypass the Preference window by clicking on

“X” in the upper right corner to close the window. For users accessing software directly

from server, press <Esc> button on keyboard to close the window. The preferences

menu can also be accessed from the top menu under File>Preferences, shown in Figure

2-5.

Figure 2-5: Top menu toolbars. There are three drop-down menus for accessing File, Tools and

Help functions

In addition, if the laboratory information and disclaimer information are not set and the

logged in user has the director role, the preference panel will show up as in Figure 2-6.

Until all the information in the preference panel window is filled in, it will pop up every

time a user with director access opens the software.



2.3 User Management

User management tools can be accessed through the User panel in the Preference

window, shown in Figure 2-6. When creating new accounts for users, it is important to

remember the privileges and abilities of each role. A user with the lab director role can

perform all actions with full access to the software. A lab technician can perform most of

the tasks except for confirming a sample and deleting a project. A guest has read only

access; therefore they cannot make any edits to allele calls when reviewing a project. A

guest user also cannot create, delete, export, or import projects. Detailed permission for

the three user types are show in Table 1.

Table 1. Permission for user roles: lab director, technician and guest. *Technician can report samples approved by a Lab Director.

Check

Results Comment Change

Call Approve Confirm Report Delete Add User Preferences

Lab Director

✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔

Technician ✔ ✔ ✔ ✔

✔*

Guest ✔ ✔

To add a user, select the role, enter a login name and email address and create a

password. The password must contain at least 8 characters including at least one upper

and one lowercase letter and one numeral. Only a lab director may delete a user.

Figure 2-6: Preference window of setting up new accounts, delete user or change password of

current user. Note that only user with director role has the privilege to add or delete user.

2.4 Disclaimer Information

From the preferences window, the user can set up new accounts and default parameters, including laboratory information and disclaimer language to be used in the HLA typing report, shown in Figure 2-7.



Figure 2-7: Disclaimer information panel displays the disclaimer information for the final report. A

user with lab director privileges can edit this information.

2.5 Laboratory Information

Figure 2-8: Laboratory information panel displays laboratory contact information to be shown in

final report

2.6 Date and Time Format Information

Figure 2-9: Date and Time format panel for setting date and time formats



2.7 Report Format

Figure 2-10: Report format options.

There are three options in Report Format window: “Allele extension”,” Show comments”,

and “A4 report Page Size”. Allele extensions are those characters (e, i, v and x) added

to the names of reference sequences generated internally either through cloning-and-

sequence or computationally. “Allele Extension” option will allow users to add allele

extension characters to the allele name in the final report. For example, when “Allele

Extension “box is unchecked, A*01:01:01:01v1 will be displayed as A*01:01:01:01 in

final report. “Show comment” option allows users to display comments created during a

review process in the final report. “A4 Report Page Size” option allows users to change

the page size to A4 format (European format).

2.8 Review Options

Figure 2-11: Review Options panel

Review option tab in the preference window allows a user to set configurations in the

review window. The default order of candidate alleles can be set to either order by Call

column or by cReads column in the genotype table. To order the candidate alleles by

cReads, tick the preference and select Apply. The default order of loci can be set to

Alphabetical order or conventional order. The conventional order is A, B, C, DRB1,



DRB3/4/5, DQA1, DQB1, DPA1, DPB1. To order the loci alphabetically, tick the

preference and select Apply.

2.9 Transferring Files between server and user’s machine

using VNC Viewer

VNC Viewer has a built-in File Transfer function. The File Transfer feature is useful for

uploading sample sheets and downloading reports. Caution is advised because this

function has the ability to transfer individual files or entire folders. Select only the

desired file to avoid transferring an entire folder instead of a single file.

Figure 2-11: VNC Viewer File Transfer window.

To fetch files from the VNC to the user’s computer:

1. Locate the VNC icon in the lower right corner of the VNC viewer window

2. Right click on the VNC icon to open a menu of options

3. Select File Transfer from the list of options

4. The file transfer dialog box will appear as shown

5. Choose the option Fetch files to: “Ask every time.”

6. Click on the button labeled Send files to open a new window and view your files

7. Select the file to transfer

8. Click on the OK button to transfer the selected file to the download location

specified above

9. A message will appear with a list of files transferred and their Download status



Files can also be loaded directly to the server using as USB Flash Drive.

To transfer files to the VNC Server from the user’s computer:

1. Hover over the top center of the VNC viewer window, and a menu will drop down

2. Locate and press the File transfer button and the file transfer window will be

displayed

3. From the pull down menu in the lower right corner of the window, fetch files to,

select the location of the files to be transferred

4. Choose the files to be transferred and press the Send files button in the lower left

corner of the window.

A message will appear when the file transfer was completed successfully

Files can also be loaded directly to the server using as USB Flash Drive.



3. Projects Window

Click on the project button to show a table of all projects created by users. Each

row displays one project with 10 columns: Project Name, Created on, Analyzed on, Lot,

Received on, Operator, Project Status (Sample, Analysis, Review, Approval, Report),

Next Step, Software Version and IMGT version. To refresh the page, click on the

Projects icon.

Figure 3-1: Projects window is displayed after clicking on the Projects button on the left panel or after successful login. When selecting any of the Statistics, Review or Summary, from the left

hand panel, a tab will display adjacent to the Project tab.

When selecting different Projects from the Project tab, the Review and

Summary tab do not refresh and must be closed to reflect the new Project

selection.

The complete project name will be generated once the project is created, which consists

of three parts: the project name provided by user, the date the project is created and a

randomly chosen English bird name. For example test_10Dec15_MURRE, where test is

provided by user through new project wizard, the second and third parts are added by



the software. Use the complete project name generated by MIA FORA software when

setting up a MiSeq run.

The status column is shown as Figure 3-2. There are five steps to completed status:

Sample, Analysis, Review, Approval and Report. Each one is represented by one

“moving next” shape. Each status has four states: ready for next step (amber), red

(failure), blue (progressing) and green (completed).

The next step button serves two purposes. First, once a new project is created, clicking

on the next step button will launch the fastq files upload wizard. Second, if a project

analysis failed, clicking on the next step button will change the status back to ready.

Figure 3-2: Project status indicators. Amber indicates ready for next step; red indicates an error; blue indicates step in progress; green indicates step is finished.

3.1. Create a new project

To create a new project and submit the sequencing results for HLA typing, click on the

New Project button in the lower right-hand corner of the main Projects page. See Figure

3-3.

Figure 3-3: New Project initiation. Select button in lower right corner of the main application page.

After clicking on the New Project button, a dialog box will appear. Enter project name,

which is created by the user, MIA FORA kit lot number and date that kit is received.

The software will add both the date when the project is created and one of random bird



names to create a unique, complete project name. Navigate to the Sample Barcode

sheet and confirm the sample names (Figure 3-4, to Figure 3-8).

See the MIA FORA NGS HLA Typing Kit LT24 User Guide for instructions on

how to create the Sample Barcode sheet. Sample Barcode sheet accepts

alphanumeric, dash and underscore. No special characters are accepted.

Figure 3-4: Welcome page of new project wizard

Figure 3-5: Project information dialog box of new project wizard



Figure 3-6: Filled dialog boxes on project information page of new project wizard.

Figure 3-7: Sample barcode confirmation page of new project wizard



Figure 3-8: Summary page of new project wizard. Note the project name is computationally generated with three parts: the part provided by user, current date and a random bird name.

3.2. Launch data analysis

To launch the data analysis, load the MiSeq fastq data files into the project by clicking

on the Next Step button. The fastq files wizard will open and navigate to load the fastq

files (Figure 3-9, Figure 3-10 and Figure 3-11). Hold down <ctrl> key to select both fastq files

together.

Figure 3-9: Welcome page of fastq files upload wizard



Figure 3-10: Filled input box of fastq files wizard showing files selected

Figure 3-11: Confirmation page of fastq files wizard

If data analysis cannot be launched, as indicated by no change in the

state/status indicator, the user should click on Clean in the Tools menu. After

that, the data analysis pipeline should be able to pick up a project to launch data

analysis.



4. Statistics Window

Statistics window displays sequence quality of the selected project. MiSeq quality

metrics from the selected project are shown as well as read distribution of barcoded

samples, insert distribution, and pie chart of valid reads.

Click on the Statistics button on the left side bar will bring up the statistics window

(Figure 4-1) for the selected project.

Figure 4-1: Statistics window displaying sequence quality of the selected project. MiSeq quality metrics from the selected project are shown as well as read distribution of barcoded samples,

insert distribution, and pie chart of valid reads.

Figure 4-2 shows the overall read distribution for three categories: invalid barcodes,

unused barcodes and valid barcodes. Reads with sequencing errors in the barcode or

contaminated barcode will be classified under Invalid Barcode. When a run consists of

24 samples but only a subset of samples are analyzed, any reads that are not analyzed

will be classified under Unused Barcode.



Figure 4-2: Pie chart of sequence reads distribution among invalid barcode, unused barcode and

valid barcode reads categories

Figure 4-3 insert distribution shows the distribution of end-to-end distance between

paired-end reads after mapping onto reference sequences.

Figure 4-3: Insertion size of paired end reads distribution

Figure 4-4 and Figure 4-5 show the read count for each barcoded sample in either

histogram or plate layout. The plate layout allows the user to diagnose a failed run. By

right clicking on the barcode distribution graph, the user can save the barcode

distribution table. All other graphs on the statistics page can be saved in the same way.

Figure 4-4: Bar graph of read count for each barcoded sample



Figure 4-5: Read count illustrated in 96-well format of plate layout. Barcode distribution within a plate is displayed in the Plate tab. Different colors represent the number of reads tagged with the index barcode for each well. The color key is displayed next to the plate diagram and ranges from

red for the lowest number of reads to blue for the highest number.

Figure 4-6 shows the distribution of nucleotides along each position of the sequencing

read. The first nucleotides of the graph represent the barcode region where the

distribution is distorted.

Figure 4-6: Distribution of nucleotides along each position of read.



Figure 4-7 shows the distribution of quality scores at each position along the read.

Figure 4-7: Distribution of MiSeq quality scores along each position of read should above Q30.



5. Review Window

Click on the Review button on the left side bar to display the Review window in a

tab as shown in Figure 5-1. It is important for reviewers to verify automatic calls for

flagged samples and make edits where necessary. Edits are necessary when

independent software algorithms are inconsistent in calling novel alleles, in detecting

polymorphisms, or in phasing.

Figure 5-1: Annotated review window. Block A displays sample information; Block B displays the

selected genotypes for the sample. Block C displays the Variants, Smart Guide, and LD Suggestion tables; Block D displays the table of computed allele candidates; Block E displays coverage plots and alignment browsers for mapped sequence of sample; Block F displays the

alignment browser for phase resolved de novo contigs

5.1. Block A: Sample Information

The sample information block contains Sample, Locus, and last visited date (Figure 5-2).

The Sample dropdown lists barcode ID and sample name. The Locus dropdown lists

HLA loci. Last visited field displays the date and time of the last visit. A user can view

different samples or genes through the dropdown lists, as shown in Figure 5-3 and Figure

5-4.

Figure 5-2: Sample information panel in review window



Figure 5-3: Sample information dropdown list. The background color indicates the review status

of each sample: gray indicates the sample has not been reviewed yet (visit time = 0); yellow indicates 1 to 10 visits; blue indicates more than 10 visits; green indicates the sample was

approved. The last visited sample is indicated with red text.

Figure 5-4: Locus dropdown list sorted alphabetically

5.2. Block B. Genotype Table

The sample genotype table (Figure 5-5) displays the selected genotype for the sample.

The phasing consensus (PC) column lists the number of contigs built by the de-novo

assembly algorithm. Each Allele column lists alleles predicted to be in the same

haplotype. There are two buttons above the genotype table: Approve and Confirm.



Figure 5-5: Genotype table for a single sample before approval. The Smart Flag is displayed above each allele. Alleles are organized by predicted haplotype; each column represents one predicted haplotype. Each cell of the table is clickable to switch to the review panel for selected gene. The highlighted alleles show automatic calls that should be manually reviewed. The legend for Smart

Flagging System can be shown by hovering cursor over the headers for allele columns.

The Approve button allows the lab director to approve the results. Once the Approve

button is clicked, a comment dialog will be shown as in Figure 5-6. The user can cancel

the action by clicking on the Cancel button. The user can add a comment in the New

Comment window. Click on the OK button to load the comment into the project log. After

the sample is approved, the Approve button will change to UnApprove.

Figure 5-6: Comment dialog box for sample approval

The Confirm button allows the lab director to confirm the results. Once the Confirm

button is clicked, a comment dialog loaded with previous comments will be displayed.

The user can cancel the action by clicking on the Cancel button. The user can add a

comment in the New Comment window. Click on the OK button to load the comment



into the project log. After the sample is confirmed, the Confirm button will change to

UnConfirm and the Report button will appear next to the UnConfirm button (Figure 5-7).

Figure 5-7: Genotype table of alleles for a sample after approval. Three buttons are displayed

(UnApprove, UnConfirm, and Report.)

Click on the Report button to display a report dialog box (Figure 5-8). If there is ambiguity

in the two alleles from DPB1, the equivalent pairs of alleles will be displayed in the last

column “Notes”. Two options (PDF and XML) allow the user to choose a different output

format. Enter output file name in a file dialog and save the file. The PDF output file

displays all comments related to the sample displayed at the bottom if the Report

Format preference has been selected to show comment. Similarly, if the Report Format

preferences have been selected to show allele extensions, they will display on the

report. Examples for each of the files formats are shown in Figure 5-9 and Figure 5-10.



Figure 5-8: An example of a report dialog box. Two (PDF and XML) buttons at the bottom right corner allow the user to choose either PDF or XML format. User can chose in the preference panel

whether or not to have comment and allele name extension (e, i, v, x) displayed, or A4 page format.



Figure 5-9: Example of a report in PDF format with both comments and allele name extensions

(Preferences are set to ‘Show Comments’ and show ‘Allele Extensions’)



Figure 5-10: Example of a report in XML format



5.3. Block C. Variants, LD Suggestion, and Smart Guide

There are three tabs in this block- Variants, Linkage Disequilibrium suggestion (LD info),

and Smart Guide. In the Variants tab (Figure 5-11). the first column (Pos) lists

polymorphic sites of de-novo assembled contigs. The second column (Depth) provides

the coverage depth of each polymorphic site. The number outside the bracket is the

total number of reads covering that site; the number within the bracket is the number of

nucleotides not listed in either contig. The third column (Contig1) lists the nucleotide and

its occurrence in contig 1 and the fourth column (Contig2) lists the nucleotide and its

occurrence in contig 2. The fifth column (Block) indicates phasing blocks; each block is

a continuous region which can be phased with support from paired-end reads; each

phased block begins and ends with the ‘--’ symbol.

Figure 5-11: Variants table. The first column (Pos) lists the position of each polymorphic site in

the de-novo assembled contigs. The second column (Depth) lists the coverage of each polymorphic position. The number outside the bracket is the total number of reads covering that site; the number within the bracket is the number of nucleotides not listed in either contig. The third column (Contig1) lists the nucleotide and its occurrence in contig 1 and the fourth column (Contig2) lists the nucleotide and its occurrence in contig 2. The fifth column (Block) indicates

phasing blocks; each block is a continuous region which can be phased with support from paired-end reads; each phased block begins and ends with the ‘--’ symbol highlighted with amber.

The block highlighted with amber, as shown in Figure 5-12. Amber highlighted entries in

Contig1 and Contig2 indicate positions where the ratio of the nucleotide frequencies

deviates from the average ratio across the sample. These polymorphic positions are

unreliable.



Figure 5-12: Variants table. Amber highlighted entries in Contig1 and Contig2 indicate positions where the ratio of the nucleotide frequencies deviates from the average ratio across the sample.

The LD info tab (Figure 5-13) displays LD Suggestions based information aggregated

information from the publicly available database and from analysis of internally typed

samples. The public haplotype data can be found at:

https://bioinformatics.bethematchclinical.org/HLA-Resources/Haplotype-Frequencies/

Each row represents alleles that have been observed to be associated with one

another. The LD suggestion panel is for information only; LD is not used to make

automatic allele calls.

Figure 5-13: LD Info tab displays LD Suggestion.



The Smart Guide (Figure 5-14) provides guidelines for reviewing the HLA typing results.

Possible reasons may be provided to explain why a user should review the specified

information in the review window. The recommended actions are described to provide

instructions for review. The smart guide will only contain information when an automatic

allele call is highlighted in the genotype table on the review page.

Figure 5-14: Smart Guide lists Reasons and Actions for reviewing allele calls.

5.4. Block D. Allele Candidate Table

The allele candidate table (Figure 5-15, Figure 5-16) lists the automatic allele calls and

parameters calculated from sequence reads mapped to HLA reference sequences.

Within this table, a user is allowed to comment on a selected allele, overwrite a

automatic allele call and make a manual allele call.

The Call Column (Call) contains a check symbol to indicate the automatic or manually

selected alleles. The green check symbol indicates that there is no warning associated

with the selected allele. The amber check symbol indicates a warning associated with

the selected allele. The blue symbol in the second column indicates there is a comment

associated with the corresponding allele.

After comparing the best-matched contig with the reference allele, the software displays

the number of mismatched nucleotides between the contig and the reference allele in

the exon (MME) or intron (MMI). The alleles highlighted in gray indicate a candidate

best matched with contig 1. The alleles highlighted in amber indicate a candidate best

matched with contig 2.

A Call warning occurs in four scenarios: first, if the selected allele is not CWD; second, if

the allele is inconsistent with LD information; third, if an exon of the selected allele has a



mismatch (MME) with the best-matched contig; fourth, if the underlying locus is

predicted to be homozygous.

There are four different sets of reference sequences: cRead (cDNA), eRead (partial

cDNA, exons 2 and 3 for class I and exon 2 for class II loci), gRead (genomic DNA),

xRead (gRead minus the eRead.) For each set of reference region, three quality metrics

are calculated: total number of reads, minimum overall coverage (Cov) and minimum

central coverage (Cen.). All 12 quality metrics are displayed for each of the candidate

allele in the table. The tooltip for metric definition can be displayed by hovering cursor

over the header for each column.

Figure 5-15: Example of candidate table. This table of 17 columns lists likely allele candidates for the corresponding locus of the sample and their mapping parameters. The first column (Allele) is

the allele name of candidates. The second column (Call) with check symbols indicates the automatic or manually selected alleles. The third column (Cmt) shows whether there is comment associated with the particular allele. The fourth and fifth columns (MME, MMI) list the number of

mismatched nucleotides in the exon or intron after comparing the best-matched contig with reference allele; The alleles highlighted in gray indicate a candidate best matched with contig 1. The alleles highlighted in amber indicate a candidate best matched with contig 2. Columns 6-8

(cRead, Cov, Cen) list the mapping parameters against cDNA reference sequences. Columns 9-11 (eRead, Cov, Cen) list the mapping parameters against partial cDNA reference sequences,

specifically Exons 2 and 3 for Class I loci and Exon 2 for Class II loci. Columns 12-14 (gRead, Cov, Cen) list the mapping parameters against genomic reference sequences. Columns 15-17 (xRead, Cov, Cen) list the mapping parameters against partial genomic reference sequences that include

everything except the partial cDNA sequence listed above. The table may be sorted by clicking on any column header.

Figure 5-16: Example of candidate table where the selected alleles check symbol is amber. The amber check symbol suggests that the locus requires manual review and the reason is given in

the smart guide. The blue dialog symbol in the second column indicates there is a comment associated with the corresponding allele.



Double-click on a header to sort on that column. Click on any cell to select the

entire row.

Technician or lab director user roles may override automatic allele calls. Common

reasons for overwriting an automatic allele call include a discrepancy in phasing,

incomplete detection of polymorphic sites, or presence of a novel allele.

Double-click on the second column (Call) to select or deselect an allele call (Figure 5-17.)

If the allele was previously checked, it will be unchecked; if the allele was unchecked, it

will be checked. Each time, the activity will be logged through the comment dialog box

(See Figure 5-18), where a user has the option to add comments about this activity.

Figure 5-17: Check or uncheck a candidate by double-clicking on the cell in the second (Call)

column

Figure 5-18: Comment dialog box when toggling the status of a selected allele



Double-click on the cell in the third column (Cmt) to activate the comment dialog box

(Figure 5-19). Users can log comments using the comment dialog box. This action will not

change the status of the selected allele.

Figure 5-19: Comment dialog box for attaching comments to a selected allele When average

coverage is less than 40X the display shows Insufficient Data. If user wants to

show genotype of a locus without sufficient data, user could type OWI (overwrite

insufficient data) in a comment dialog to bring up genotypes masked by

insufficient data. If user wants to cancel the effect, users could type XWI in a new

comment dialog window.

Click on the tab labeled “Candidate Pair” to view the candidate pair table (Figure 5-20). In

this table, each row represents a possible combination of two alleles listed in columns

one and two. Eight parameters are displayed for each candidate pair. The cRead

column lists the number of unique reads mapped to the cDNA reference sequences of

the two alleles. The eRead column lists the number of unique reads mapped to the

partial cDNA sequence containing only Exons 2 and 3 for Class I loci and only Exon 2

for Class II loci. The gRead column lists the number of unique reads mapped to the

genomic reference sequences. The xRead column lists the number of unique reads

mapped to partial genomic sequences that exclude the exon 2/3 regions detailed above.

The mismatch numbers in the exon (MME) and intron region (MMI) for Allele1 and

Allele2. Highlight a row of possible combination of two alleles and select Coverage to

directly plot coverage for the cDNA reference sequences and the genomic reference

sequences.



Figure 5-20: Candidate Pair table. The first and second columns (Allele1, Allele2) list the pair of

alleles examined. The third column (cRead) lists the number of unique reads mapped to the cDNA reference sequences of the two alleles; the fourth column (eRead) lists the number of unique

reads mapped to the partial cDNA sequence containing only Exons 2 and 3 for Class I loci and only Exon 2 for Class II loci. The fifth column (gRead) lists the number of unique reads mapped to

the genomic reference sequences. The sixth column (xRead) lists the number of unique reads mapped to partial genomic sequences that exclude the exon 2/3 regions detailed above. The

mismatch numbers in the exon (MME) and intron region (MMI) for Allele1 and Allele2.

5.5. Block E1. Coverage Plots

Coverage plots are generated for both cDNA and genomic DNA. The minimum

coverage across the reference should be above 20X. For each selected reference allele

in the candidate table, the coverage is plotted along either the cDNA region for the

cDNA coverage plot or the genomic region for the genomic coverage plot. Overall read

coverage is the number of individual sequence reads that were aligned across either

cDNA or genomic reference sequences (Figure 5-21).

To view coverage plots, select the alleles for review and click on the Coverage button

(first button on the left).

When the sequence reads of the sample match the selected reference sequence then

the coverage will be above the baseline across the whole region. When the sequence

reads of the sample is mismatched to the selected reference sequence then the

coverage will dip to the baseline at the mismatched position.

Positions that differ between selected alleles are highlighted with red bars (hash marks)

above the curves. Gray shaded regions display the coverage of all alleles for the gene

minus the coverage of the selected alleles. When the selected alleles map to all the

reads, then there are very low amount of gray in the coverage plot. If there is a

mismatch with the reference there is clear accumulation of reads, represented in grey,

that do not map to the reference sequence at that location.



Figure 5-21: Coverage plots. The left panel shows coverage along the cDNA reference sequences; the right panel shows coverage along the genomic reference sequences. Red bars (hash marks) above coverage curves indicate positions that are polymorphic between the selected reference

alleles. Windows can be resized.

To view local alignment of selected reference sequences, hold down <Shift> key and

click once at the desired location within the coverage plot. Local alignment of 30 bases

of the selected reference alleles will be displayed near the clicked position (Figure 5-22).

Figure 5-22: Local alignment of sequence fragment of two selected alleles at the clicked position

(Shift-click). Nucleotides that differ between the selected alleles are shown in red text

The coverage plot will zoom in to a selected rectangular region as shown in Figure 5-23. To zoom, click and drag desired region within the plot.

Figure 5-23: Zoomed-in view of a fraction of a coverage plot



Central coverage plots are generated for both cDNA and genomic DNA. The minimum

coverage across the reference should be above 10X. For each selected reference allele

in the candidate table, the central coverage is plotted along either the cDNA region for

the cDNA coverage plot or the genomic region for the genomic coverage plot.

To view coverage plots, select the alleles for review and click on the Central button

(second button on the left).

When the sequence reads of the sample match the selected reference sequence then

the coverage will be above the baseline across the whole region expect at exon

boundaries in cDNA central coverage plot. When the sequence reads of the sample is

mismatched to the selected reference sequence then the coverage will dip to the

baseline at the mismatched position.

Figure 5-24: Example of central read coverage plot

In the cDNA coverage plot, central reads are undefined at exon boundaries.

5.6. Block E2. Alignment Browsers

Click on the cDNA Browser to view alignment of reads against the cDNA reference

sequence, as shown in Figure 5-25. There are several buttons for navigation. Figure 5-26

and Figure 5-27 show the zoomed-in and zoomed-out view. The first reference sequence

is highlighted with gray background color and the second reference sequence is

highlighted with a tan background color. Those that differ from the first and second

reference sequences are highlighted in light blue and those bases are considered as

noise. Hovering over a read will highlight the entire read with a cyan background color

(See Figure 5-28).



Figure 5-25: Alignment browser against cDNA reference sequence. Four buttons on the top left corner allow easy navigation of the view. Prev and Next buttons jump to the previous or next

polymorphic sites. Zoom In and Zoom Out buttons will zoom the display in or out. Five tracks on the top of the alignment display coverage, length, poly site, the first and second selected alleles (if

two alleles are selected) and annotation of the reference sequence showing exon and intron locations. The red rectangle marks the cursor position where the position and the number of

nucleotides are displayed in blue text.

Figure 5-26: Zoomed-in view of cDNA alignment browser



Figure 5-27: Zoomed-out view of cDNA alignment browser. The yellow arrows are reverse reads

and the gray arrows are forward reads

Figure 5-28: Highlight of read under cursor with cyan color in cDNA browser

Click on Genomic Browser to view alignment of the sequence reads against the

genomic reference sequence, as shown in Figure 5-29 to Figure 5-32. Genomic browser

functions the same as those in the cDNA browser.

Due to large number of actual reads, only a partial set of mapped reads are

plotted in the cDNA and genomic browser, while the numbers next to the red

rectangle represent the total number of all mapped reads.



Figure 5-29: Alignment browser against genomic reference sequence. Four buttons on the top left

corner allow easy navigation of the view. Prev and Next buttons jump to the previous or next polymorphic sites. Zoom In and Zoom Out buttons will zoom the display in or out. Five tracks on top of the alignment display coverage, length, poly site, the first and second selected alleles (if

two alleles are selected) and annotation of the reference sequence showing exon and intron locations. The red rectangle marks the cursor position where the position and number of each

nucleotide are displayed in blue text.

Figure 5-30: Zoomed-in view of the genomic alignment browser



Figure 5-31: Zoomed-out view of the genomic alignment browser

Figure 5-32: Individual reads under the cursor are highlighted in cyan in the genomic browser. The

deletion is indicated by missing bases in the reference sequence.

5.7. Block E3. Reference Alignment

Click on the Reference Alignment button to view the reference sequence alignment of

selected alleles as shown in Figure 5-33 (for cDNA reference sequences) and in Figure

5-34 (for genomic reference sequences).



Figure 5-33: cDNA reference alignment of selected references in the candidate table. Pink bars

delineate the exon boundaries. Positions different among selected alleles are highlighted



Figure 5-34: Genomic reference alignment of selected references in the candidate table. Pink bars delineate the intron-exon boundaries. Positions that differ among the selected alleles are

highlighted



Click on the Consensus Alignment button to display multiple sequence alignment

between selected alleles and their best-matched de novo assembled contig (Figure 5-35

to Figure 5-38). The Phased Resolved Consensus sequence can be aligned with any

selected candidate alleles by clicking on the Consensus Alignment browser. The

alignment between selected alleles from the candidate table and the best-matched

contig will display. The best-matched contig is defined as the least number of exon

mismatches.

Figure 5-35: Multiple alignment of selected cDNA reference sequences with de novo contig1 sequence. Positions that differ between contig1 and the reference sequence are highlighted.

When no sequence is available the position is denoted with N.



Figure 5-36: Multiple sequence alignment of selected cDNA reference sequences with de novo

contig2 sequence. Positions that differ between contig2 and the reference sequence are highlighted



Figure 5-37: Multiple alignment of selected genomic reference sequences with de novo contig1 sequence. Positions different between contig1 sequence and reference sequences are

highlighted. Exon regions are shaded in gray



Figure 5-38: Multiple alignment of selected genomic reference sequences with de novo contig2

sequence. Positions different between contig2 sequence and reference sequences are highlighted. Exon regions are shaded in gray



Figure 5-39. Display amino acid codon in the contig sequence alignment window. The amino acid codon can be displayed by double clicking on any nucleotide.

Figure 5-40. Contig Alignment Browser centered at the select base position from contig sequence alignment. To align a specific position in consensus alignment browser with the contig alignment

browser, select and hold shift and double-click on the nucleotide in the consensus alignment browser. A red vertical box will highlight the selected position in the contig alignment browser.

Click on the Clear button to de-select any selected alleles in the candidate table.

5.8. Block F. Contig Alignment Browser

The contig alignment browser (Figure 5-41 to Figure 5-44) displays the de novo assembled

contigs for the selected sample. The functions in the browser are similar to the genomic

alignment browser (Figure 5-29) shown above. In addition, the contig alignment browser

has an “Export Consensus” button allowing the user to export the contigs in fasta

format.



Figure 5-41: Contig browser showing reads mapped to de novo contigs. Five buttons on the top left corner allow easy navigation of the view. Prev and Next buttons jump to the previous or next

polymorphic sites. Zoom In and Zoom Out buttons will zoom the display in or out. The Export Consensus button allows exporting the contig (consensus) sequences. Five tracks on top of the alignment display coverage, length, poly site, the first and second selected alleles (if two alleles are selected) and annotation of the reference sequence showing exon and intron locations. The

red rectangle marks the cursor position where the position and the number of each nucleotide are displayed in blue text.

Figure 5-42: Zoomed-in view of contig browser showing reads mapped onto de novo contigs



Figure 5-43: Zoomed-out view of contig browser showing reads mapped onto de novo contigs.

Gray rectangles denote paired-end reads; yellow arrows denote non-paired-end reads (singletons)

Figure 5-44: Contig Browser showing a single read highlighted in cyan; highlighting is visible by

hovering the mouse over the display

The unsequenced region between the paired-end reads is indicated with N.

5.8.1 Interaction between Variants table and contig alignment browser

Click on any position in the first column (Pos) of the Variants table to highlight the

polymorphic site in the contig alignment browser as shown in Figure 5-45.

Figure 5-45: Interaction between Variants table and contig alignment browser; clicking on a position in the first column (Pos) of the Variants table will center the Variants in the contig

alignment browser



5.8.2 Interaction between cDNA browser and contig alignment browser

Click on a location in the cDNA browser to center it in the contig alignment browser as

shown in Figure 5-46.

Figure 5-46: Interaction between cDNA alignment browser and contig alignment browser. Click on

a position in cDNA browser to center the corresponding position in the contig alignment browser.

The opposite action is also possible (click on contig browser to center the cDNA browser).

5.8.3 Interaction between genomic browser and contig alignment browser

Click on a location in the genomic browser to center the contig alignment browser at the

corresponding position as shown in Figure 5-47.

Figure 5-47: Interaction between genomic alignment browser and contig alignment browser. Click

on a position in genomic browser to center the corresponding position in the contig alignment browser. The opposite action is also possible (click on contig browser to center the genomic

browser)



5.8.4 Interaction between genomic coverage plot and contig alignment browser

Hold down <Ctrl> key and double click on a position in the genomic coverage plot to

center the contig alignment browser at the corresponding position (Figure 5-48).

Figure 5-48: Interaction between genomic coverage plot and contig alignment browser. Hold down

<Ctrl> key and double-click on a position in genomic coverage plot to center the corresponding position in the contig browser

5.8.5 Interaction between cDNA coverage plot and contig alignment browser

Hold down <Ctrl> key and double-click on a position in cDNA coverage plot to center

the contig browser at the corresponding position (Figure 5-49).

Figure 5-49: Interaction between cDNA coverage plot and contig alignment browser. Hold down <Ctrl> key and double-click on a position in cDNA coverage plot to center the corresponding

position in the contig browser



5.8.6 Interaction between cDNA coverage plot and cDNA alignment browser

Hold down <Shift> key and double-click on a position in the cDNA coverage plot to open

a new tab displaying the cDNA Alignment Browser and centered at the corresponding

position (Figure 5-50).

Figure 5-50: Interaction between the cDNA coverage plot and the cDNA browser. Hold down

<Shift> key and double-click on a position in the cDNA coverage plot to center the corresponding position in the cDNA browser

5.8.7 Interaction between genomic coverage plot and genomic alignment browser

Hold down <Shift> key and double-click on a position (shown as a blue bar) in the

genomic coverage plot to open a new tab displaying the Genomic Alignment Browser

centered at the corresponding position (Figure 5-51).



Figure 5-51: Interaction between genomic coverage plot and genomic browser. Hold down <Shift>

key and double-click on a position in the genomic coverage plot to center the corresponding position in the genomic browser



6. Summary Window

Summary table shows genotype calls for HLA genes for each sample in the project.

HLA genes are listed as columns. Alleles that require manual review is highlighted pink

in the summary table. A Smart Guide tooltip window will show when a user hovers the

mouse cursor over the highlighted allele.

Click on the summary button to bring up the summary window as shown in Figure

6-1. Click on any allele name to open the review window for that sample. Click on a

sample name to open the dialog box to approve that sample.

Figure 6-1: Summary table of genotypes for a project. The Smart Flagging System is displayed

above each allele, see Section 1 for details. Alleles that requires manual review is high-lighted in the summary table. A Smart Guide tooltip window will show when users hover the mouse cursor over the highlighted allele call. Green filled circles next to the sample names indicate approved samples. Right click to open the context menu (show at the right.) The summary table may be

exported in two different formats. The long CSV form shows alleles for one sample in a single row while the short CSV form shows two haplotypes (rows) for one sample. If ambiguity for DPB1 is found, then the equivalent allele pairs will be reported in an extra column in exported CSV file

together with user comments.



7. Auxiliary Tools

Click on Reference Alignment on the left side bar to open the reference sequence

alignment window as shown in Figure 7-1. Users can use this to check alignment of any

selected alleles of the same locus.

Figure 7-1: Reference Alignment Tool. The top left panel allows the user to switch between cDNA and genomic as well as switch between different genes; the left panel allows the user to choose

alleles and the right panel displays alignments for the selected alleles



Click on the Codon button on the left side bar to display a DNA codon table as


Figure 7-2: DNA Codon Table

Click on the Backup button on the left side bar to export a project into external

storage. After the user selects the location to store the backup data through a file dialog,

a status bar will appear in the lower right hand of the software window to indicate the

backup status.

Click on the Restore button on the left side bar to import a project from external

storage. After the user selects the backed up folder through a file dialog, a loading bar

will appear in the lower right hand of the software window to indicate the restore status.

Click on the Export log button on the left side bar to export the project log to a file.

Click on the Search button to activate the search features available to query for

detailed criteria on samples or alleles. The search feature can also be accessed from

the top menu: Open Tools and select Search, and the search window will appear. The

search has several criteria that can be used to find specific samples or alleles for the 9



HLA genes (A, B, C, DPA1, DPB1, DQA1, DQB1, DRB1, DRBo which includes DRB3,

4, and 5).

The options in the search window are explained in Figure 7-3 (Boxes A–H). After setting

up the options in the search window, click on the Find button to find projects in the

specified date range that contain the samples or alleles consistent with the search term.

To search for a specific allele, select “Allele” from the pull down menu in Box A. To

search specific samples, select “Sample” from the pull down menu in Box A. Enter a

search term for the sample or allele name in Box B. Format restriction is applied when

searching for an Allele.

The search term for allele must follow the following format: Gene*allele name. For

example, to find samples and projects that contain the allele DRB1*01:01:01 of gene

DRB1, the search term should be DRB1*01:01:01.

The user can search projects that contain linked alleles of the 9 HLA genes by entering

alleles separated by commas. For example, to find projects that have alleles A*01:01:01

and DRB1*01:01:01, the search terms for the two alleles should be entered in Box B as

A*01:01:01, DRB1*01:01:01. The search terms for alleles can be in any order.

Each gene should be entered only once in the search box.

To gain more search flexibility, the percent “%” and the underscore “_” wildcard

characters can be used in the search terms. Also, the prefix can be used to search for

the desired allele or sample. For example, if the search term in Box B is DRB1*01 then

it would be considered to be DRB1*01%. In this case, all alleles that start with DRB1*01

will be displayed. If the search term in Box B is DRB1*0_ then both DRB1*01, DRB1*02,

until DRB1*09 will be displayed.

To search the date range, select created after date in Box D and created before date in

Box E. The default values of Box D and Box E are respectively set to be the creation

dates of the earliest and latest projects currently available in the project table.

Box F has two states: checked or unchecked. When Box F is checked the allele search

term is case sensitive. If this box is unchecked then the matching is not case sensitive.

When Box G is checked, the search term must be exactly match with the allele name or

sample name in the projects. In this setting, “%” and “_” are not considered to be

wildcard characters.

Note that “%” and “_” are wildcard characters only if Box G is unchecked. In this case

the search term will be considered a match with the name of an allele if the search term

is a prefix of the allele name. For example, if the search term in Box B is DRB1*01 then

it would be considered to be DRB1*01%. In this case, all alleles that start with DRB1*01

are considered to be matching.



The output of the search will be displayed in Box H. Each row displays the sample

name, if there is genotype data, barcode ID, project name, the date of project creation,

and the name of the user who created the project. Double-clicking on a row will display

the review panel of that sample and project.

Figure 7-3: Search window. A, Select Allele or Sample for search criteria; B, Box to enter search

term; C, Find button; D and E, Select the desired date range; F, when this box is checked the search term is case sensitive; G, when this box is checked the search term is exactly matched to

the names of alleles or samples and % and _ are not considered wildcard characters; H, the output of the search

The content in the search results table is clickable to directly open the appropriate review panel.

Click on the NMDP button to open a wizard and view instructions for updating the

NMDP ambiguity code (Figure 7-4, Figure 7-5, Figure 7-6, Figure 7-7)

Figure 7-4: Welcome page for NMDP ambiguity code wizard

Figure 7-5: Filled file input page of NMDP ambiguity code wizard. Users need to download the file

from the HLA resource page: https://bioinformatics.bethematchclinical.org/HLA-Resources/Allele-Codes/Allele-Code-Lists/Allele-Code-List-in-Numerical-Order



Figure 7-6: Sample of input file for the NMDP ambiguity code wizard

Figure 7-7: Upon clicking Finish, the NMDP ambiguity code wizard asks to verify the input



SironaQuant

Click on the SironaQuant button to open the wizard to compute balancing metrics used

in the MIA FORA NGS HLA Typing Kit (Figure 7-8). The SironaQuant program is

designed to seamlessly balance a sample plate so amplicons from all loci are

represented in sufficient quantity in the pooled library during sequencing.

Figure 7-8: Welcome page for the SironaQuant wizard

Each sample is amplified individually for all genes. The user first quantifies the

concentration of the sample with the Picogreen quantification assay, and then

generates a file containing the fluorescence data for each well. The dialog window is


The file names are expected to have three or four parts – project name, column name,

and user comments - separated by underscores (“_”). For example, the following two

file names are acceptable:

Project01_COLUMN1_Date.txt

Project_01_COLUMN1_Date.txt

Once a file for each of the three-sample plates has been uploaded into the SironaQuant

program, the user chooses a picomole value for normalization. The program then

extracts the fluorescence data from the files and balances the genes, if possible with the

chosen picomole amount.

Figure 7-9: Filled information page of the SironaQuant wizard



The input files need to be text tab delimited if you are using Windows operating system,

or Windows Formatted Text if you are using Mac OSX operating system. The sixth

column contains the fluorescence values ordered as shown by the well location as

shown in Figure 7-10. If the user uses the Victor X3 system, the file is automatically

generated in the proper format. For other fluorescence readers the user must load the

data into the template file provided with the MIA FORA NGS system.

Figure 7-10: Sample input files for the SironaQuant wizard

The fluorescence data for the standard curve is first extracted from the first sample data

file. The slope, y-intercept and r-squared value are calculated using an average of the

fluorescence data for all replicates of each standard. The concentration of each sample

is calculated by applying the standard curve values to the fluorescence value. Then, the

molarity of the sample is calculated and the volume needed to pool at the desired

picomole value is calculated.

This process repeats for all genes. After all of the transfer volumes have been

calculated, the volume is calculated to verify that the total volume for all genes for each

sample does not exceed 55 µL, the maximum volume dictated by the protocol. After the

individual pooling volumes are determined, the volume of buffer needed to bring the

total volume to 55 µL is calculated.



Figure 7-11: Conclusion page for the SironaQuant wizard

Once the transfer volumes have been calculated for all genes, the program outputs a

summary file (Figure 7-12) that contains, the normalization transfer volume for

normalization, the dilution volume (if any), the picomole(pmol) value that the gene was

normalized to, the total amount of pooled amplicons in nanogram (ng), the length of the

gene in base pairs, and identifiers for samples that have been excluded from the

average for each locus. The summary file also displays the standard curve slope, y-

intercept, and r-squared value, and the volume of buffer required to bring the total

pooled volume to 55 µL. Thus the balancing program provide a way for all the

amplicons to be represented in the sequencing to facilitate HLA typing of all loci, even

the ones that have allelic imbalance. It also serves to warn the user of failures early in

the sample-preparation process so that adjustments can be made prior to sequencing.

Warnings Display:

1. If the total volume exceeds the limit (55ul), an alert is displayed to the user and

the program does not proceed. The user then chooses a lower picomole value.

The minimum recommended picomole value is 0.0009 and the maximum is

0.0035.

2. If there are more than 8 samples with very low fluorescence values, an alert is

displayed to the user Figure 7-13. This alert is only as a warning to the user that

there are many failures in the plate and can be bypassed if the user choses to

proceed by clicking on the “Ignore warnings” option. If there are fewer than 8

samples with a low concentration failure, but more than 1, they are listed as

outliers in the output file. If the user chooses, they can redo the PCR for the

failed loci with remaining reagents in the kit. There is sufficient reagent to redo at

least 4 PCR reactions per locus.

3. If fluorescence values are not 25% larger than the negative control of the

corresponding gene, a warning message suggests user to redo PCR before

proceeding with library construction.



These warning messages should not be ignored in order to get a good

representation of all the loci. Ignoring warnings may result in “insufficient data”

for these loci.

Figure 7-12: Sample output file for the Sirona Quant wizard

Figure 7-13: Sample Warning Message from the Sirona Quant wizard; click OK to get back to the

input page, and input a different pmole value or check “Ignore Warnings“ to continue

Figure 7-14: Filled information page of the Sirona Quant wizard with checked “Ignore Warnings”



Appendix A: Software Color Codes Description

Several color codes are used throughout the software. Below is a description of different

color codes.

A.1. Variants Table

Amber colored boxes in the Variants table may appear in the Contig or Block columns.

In Contig1 and Contig2 columns the amber colored boxes indicate that the ratio of the

two alleles is outside the expected standard deviation (Figure A1-B). In the Block

column the amber colored box indicates the first polymorphism in a phasing block

(Figure A1-A).

A B

Figure A1: Variants table colors. A, amber box in block column showing the beginning of a phasing block; B, amber boxes showing three polymorphisms that have a ratio outside the

standard deviation.

A.2. Genotype Table

The PC column in the genotype table displays an indicator of the number of alleles

detected by phasing consensus (PC.) A green circle indicates that the number of PC

alleles matches the number of computed alleles. An amber circle indicates that the

number of PC alleles does not match the number of computed alleles. Regardless of

color, the reviewer should verify all genes with only a single allele listed.



Figure A2: Display of Genotype Table colors. Numbers in PC column are the number of alleles detected

by phasing consensus, green means the PC number matches the computed allele number while amber

means the two numbers do not match. The pink highlighted boxes show alleles that should be manually

reviewed.

A.3. LD Suggestion Table

The yellow highlights indicate alleles that are listed in the genotype assignment table.

Figure A3: Highlight use within the LD Suggestion Table

A.4. Allele Candidate table

The check symbol in the candidate table could be either green or amber. The amber

check symbol suggests that the locus requires manual review and the reason is given in

the smart guide.



Figure A4-1: Allele Candidate Table with green check marks.

Figure A4-2: Allele Candidate Table with amber check marks.

A.5. Smart Guide

Smart Guide provides guidelines for reviewing the HLA typing results. In the review

window, Smart Guide is shown in the lower left panel as a tab together with “Variants”

and “LD Info” tabs. Recommended actions are described to give instructions of review

and reasons may be given to explain why a user should check the specified information

in the review window.

Figure A5: Smart guide with listed reasons and actions



Appendix B: Glossary

Allele: An allele is a variant form of a gene.

Assembly: The genome assembly is simply the genome sequence produced after

chromosomes have been fragmented, those fragments have been sequenced, and the

resulting sequences have been put back together.

Central Read: Central Reads are empirically defined as mapped reads for which the

ratio between the length of the left arm and that of the right arm related to a particular

point is between 0.5 and 2. When reads are mapped onto a correct reference

sequence, they form a continuous tiling pattern over the entire sequenced region.

Contig: A contig (from contiguous) is a set of overlapping DNA segments that together

represent a consensus region of DNA.

Coverage: the percentage of bases called at predetermined depth for a genomic region

of interest.

eRead: The number of unique reads mapped to the partial cDNA sequence containing

only Exons 2 and 3 for class I loci and only Exon 2 for Class II loci.

FASTQ File: A text based format for sequences data with corresponding quality

indicators for each base.

gRead: The number of unique reads mapped to the genomic reference

sequences.HLA: The human leukocyte antigen (HLA) system is the locus of genes

that encode for proteins on the surface of cells that are responsible for regulation of the

immune system in humans. HLAs corresponding to MHC class I (A, B, and C) present

peptides from inside the cell. HLAs corresponding to MHC class II (DP, DQ, and DR)

present antigens from outside of the cell to T-lymphocytes.

Locus: A locus (plural loci), in genetics, is the specific location or position of a gene,

DNA sequence, on a chromosome.

Mismatched Exon (MME): The number of mismatched nucleotides in the exon region

after comparing the best-matched contig. For DRB1, DRB3, DRB4 and DRB5, exon 1

is excluded in the calculation because the region may not have sufficient amplification

product.

Mismatched Intron (MMI): The number of mismatched nucleotides in the intron region

after comparing the best-matched contig.



Q score (Q30): Q scores measures the probability of wrong base call which is

logarithmically related to the base calling error probabilities. A Q score of 30 (Q30) is

equivalent to the probability of an incorrect base call 1 in 1000 times.

Paired-end read mapping: A set of independent reads that are derived from the same

library fragment which can be used to identify structural rearrangements.

Phasing: Historically, whole-genome sequencing generated a single consensus

sequence without distinguishing between variants on homologous chromosomes.

Phased sequencing, or genome phasing, addresses this limitation by identifying alleles

on maternal and paternal chromosomes. This information is often important for

understanding gene expression patterns for genetic disease research.

Read Alignment: Position DNA sequence reads along the genome in relation to a

reference sequence.

Reference Sequence: A fully sequenced and assembled genome that acts as a

scaffold against which new sequence reads are aligned and compared.

xRead: The number of unique reads mapped to partial genomic reference sequences

except Exons 2 and 3 for Class I and Exon 2 for Class II.



Appendix C: Best Practices

1. To mitigate the risk of any mismatch between a sample sheet and the MiSeq

data, the name of the corresponding fastq files must begin with the unique

complete project name created in the MIA FORA software. Users must create

complete project name before initiating the MiSeq sequence run.

2. Once Analysis indicator is green, first navigate to Statistics window to review

quality of run (a) invalid read percentage should be less than 10% (b) average

total read for entire project should be >200,000 (c) the quality score should be

above Q30. Due to the complex nature of HLA typing, qualified personnel should

review data interpretation and typing assignments.

3. After reviewing Statistics, navigate to the Summary window to review genotype

calls for HLA genes for each sample in the project. Alleles require manual review

if highlighted pink in the summary table. A Smart Guide tooltip window will show

when users hover the mouse cursor over the highlighted allele call.

4. When reviewing genotype results, any homozygous locus must be reviewed.

Recommended review process includes but not limited to (a) review candidate

pair table for top ranked candidate pair for presence of second allele, (b) review

status of PC indicator for inconsistency (c) if possible second allele is present,

select Allele 1 and Allele 2 and click both coverage plot and central read

coverage plot to confirm uniform coverage above baseline (d) if coverage plot of

second allele display uniform coverage, review mapped sequence using

alignment browser and phased resolved de novo contig for second allele using

the consensus browser.

5. When reviewing genotype results, review any samples that have amber diamond

indicating non-CWD alleles. Recommended review process includes but not

limited to (a) click both coverage plot and central read coverage plot to confirm

uniform coverage above baseline (b) if coverage plot of allele display uniform

coverage, then review mapped sequence using alignment browser and phased

resolved de novo contig for second allele using the consensus browser.

6. When reviewing genotype results, review any samples that have amber hexagon

indicating inconsistency in LD data. Recommended review process includes but

not limited to (a) click both coverage plot and central read coverage plot to

confirm uniform coverage above baseline (b) if coverage plot of allele display

uniform coverage, then review mapped sequence using alignment browser and

phased resolved de novo contig for allele using the consensus browser.

7. When reviewing genotype results, review any samples that have amber circle

containing a ? symbol indicating discordance between the automatic allele call

and phase resolved consensus. Recommended review process includes but not

limited to (a) review MME column for selected allele (b) identify the mismatched

position(s) between the select allele and reference sequence in the exon region

using consensus alignment browser (c) then review mapped sequence using



alignment browser and phased resolved de novo contig allele using the

consensus browser.

8. When reviewing genotype results, review any samples that have amber circle in

the PC column indicating inconsistency in phase resolved consensus and

mapped sequence. Recommended review process includes but not limited to (a)

review candidate pair table for top ranked candidate pair (b) click both coverage

plot and central read coverage plot to confirm uniform coverage above baseline

(c) if coverage plot of allele display uniform coverage, then review mapped

sequence using alignment browser and phased resolved de novo contig for allele

using the consensus browser.

9. When navigating the allele candidate table, users should pay attention to the

minimum coverage column (Cov) and minimum central read coverage column

(Cen) of cDNA (cRead).

10. After manual review of each sample, select Approve and Confirm in order to

activate the Report feature. The sample must be Confirmed for the Approval

Status to display on Project window.



Appendix D: Clickable Functions

C.1. Main MIA FORA NGS Project Window:

# Action Intention

1. Left Click on any heading; i.e. Project Name, Created On, Analyzed On, Lot, Received on, or Operator

Organize project list by the specific criteria clicked on

2. Left Click on the up or down arrows in the extreme top right corner of the frame

Maximize or minimize MIA FORA NGS window

3. Mouse over the top center of the VNC frame

Reveals dropdown menu for specifying destination file for transferring files, maximizing the window, exiting, etc.

4. Right Click on VNC icon at the bottom right corner of VNC frame

Shortcut to the VNC file transfer menu

C.2. Statistics Window:

# Action Intention

1. Right click on any Graph or Chart Option to Print appears, and the graph or chart can be saved or printed

2. Left click on any tab at the top of the statistics graphs/charts

Open specified tab

C.3. Review Window:

# Action Intention

1. Left Click on any heading in the Candidate Allele Table

Organize table by specified column

2. Right Click on any Table Option to save the table appears

3. Left Double-Click on Call column Toggle allele call on/off

4. Left Double-Click on Cmt column Comment window appears

5. Shift Left Click on Coverage Graphs Displays the allele sequence at the clicked region

6. Shift Left Double-Click on Coverage Graphs

Loads the Genomic or cDNA Alignment Browser for the region clicked on

7. Left Click, hold and drag cursor on Coverage Graphs

Zoom in on a specific region of Coverage Graphs (Double left click to zoom out)

8. Ctrl Left Click on Coverage Graphs Centers and displays selected region in contig alignment browser

9. Right Click on Coverage Graphs Option to save the graphs appears

10. Left Click on a polymorphism position (first column)

Open specified polymorphism location in the contig alignment browser

11. Hover over any grab bar of a window and left click, hold and drag

Increase or decrease the size of a window



C.4. Summary Window:

# Action Intention

1. Right click anywhere on summary table Options to export and save the summary table are displayed

2. Hover over pink highlighted allele in summary table

A Smart Guide tooltip window will show when users hover the mouse cursor over the highlighted allele call.



Appendix E: Additional Resources

MIA FORA NGS algorithm and coverage statistics: Chunlin Wang, Sujatha

Krishnakumar, Julie Wilhelmy, Farbod Babrzadeh, Lilit Stepanyan, Laura F. Su,

Douglas Levinson, Marcelo A. Fernandez-Viña, Ronald W. Davis, Mark M. Davis, and

Michael Mindrinos. High-throughput, high-fidelity HLA genotyping with deep

sequencing. PNAS 2012 109(22):8678-8681.

Relative proportions of DRB1-DRB3/4/5-DQB1 haplotypes in major ethnic groups of the

U.S. (selected, not random): Burdett L, Smith K, Tu B , Guiterrez M , Buck K. , Maiers

M., Ng J., Hartzman R. and Fernandez-Vina M. DRB-DQB1 diversity in the analysis of

4727 donors typed by SBT. (abstract) Hum Immunol. 2003 Oct;64(10 Suppl):S6.

HLA CWD allele Database: http://igdawg.org/cwd.html

International HLA and Immunogenetics Workshops: http://ihiws.org/

International Immunogenetics Information System: http://www.imgt.org

Online alignment tool: http://www.ebi.ac.uk/ipd/imgt/hla/align.html

Haplotype frequency table: https://bioinformatics.bethematchclinical.org/HLA-

Resources/Haplotype-Frequencies/

Online allele nomenclature lookup tool: http://www.marrow-donor.org/cgi-

bin/DNA/dnatyp.pl

VNC Viewer User Guide:

realvnc.com/products/vnc/documentation/5.2/guides/user/VNC_User_Guide.pdf



Appendix F: Third Party Libraries’ Licenses

Trademark and Copyright Information

MIA FORA™ is a registered trademark of Sirona Genomics Inc. MIA FORA is copyright © Sirona

Genomics Inc, 2016. All rights reserved.

Sirona Genomics Inc.

1916A Old Middlefield Way, Mountain View, CA 94043

[email protected] +1 650-396-2409

http://www.sironagenomics.com

Other programs mentioned in this software are trademarked and copyrighted by their respective owners.

Portions of this software use Klib; Klib is a standalone and lightweight C library distributed under

MIT/X11 license.

Copyright (c) 2008, 2009, 2011 by Attractive Chaos <[email protected]>

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and

associated documentation files (the "Software"), to deal in the Software without restriction, including

without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies

of the Software, and to permit persons to whom the Software is furnished to do so, subject to the

following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial

portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR

IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS

FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS

OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,

WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN

CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Portions of this software use SSW; SSW is a fast implementation of the Smith-Waterman

algorithm distributed under MIT license.

Copyright (c) 2012-2015 Boston College

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and

associated documentation files (the "Software"), to deal in the Software without restriction, including

without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies

of the Software, and to permit persons to whom the Software is furnished to do so, subject to the

following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial

portions of the Software.



THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR

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WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN

CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Portions of this software use the work of the FreeType Project, copyright © 2015 The FreeType

Project.

The FreeType Project LICENSE

2006-Jan-27

Copyright 1996-2002, 2006 by

David Turner, Robert Wilhelm, and Werner Lemberg

Introduction

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This library is provided with all faults, and the entire risk of satisfactory quality, performance, accuracy,

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Tim Wegner

The PNG Reference Library is supplied "AS IS". The Contributing Authors and Group 42, Inc. disclaim all

warranties, expressed or implied, including, without limitation, the warranties of merchantability and of

fitness for any purpose. The Contributing Authors and Group 42, Inc. assume no liability for direct,

indirect, incidental, special, exemplary, or consequential damages, which may result from the use of the

PNG Reference Library, even if advised of the possibility of such damage.

Permission is hereby granted to use, copy, modify, and distribute this source code, or portions hereof, for

any purpose, without fee, subject to the following restrictions:



1. The origin of this source code must not be misrepresented.

2. Altered versions must be plainly marked as such and must not be misrepresented as being the original source.

3. This Copyright notice may not be removed or altered from any source or altered source distribution.

The Contributing Authors and Group 42, Inc. specifically permit, without fee, and encourage the use of

this source code as a component to supporting the PNG file format in commercial products. If you use

this source code in a product, acknowledgment is not required but would be appreciated.

Portions of this software use PCRE; PCRE is a library of functions to support regular expressions

whose syntax and semantics are as close as possible to those of the Perl 5 language. THE BASIC

LIBRARY FUNCTIONS were written by Philip Hazel [email protected]. Copyright © 1997-2012

University of Cambridge. All rights reserved.

PCRE2 LICENCE

PCRE2 is a library of functions to support regular expressions whose syntax and semantics are as close

as possible to those of the Perl 5 language.

Release 10 of PCRE2 is distributed under the terms of the "BSD" license, as specified below. The

documentation for PCRE2, supplied in the "doc" directory, is distributed under the same terms as the

software itself. The data in the testdata directory is not copyrighted and is in the public domain.

The basic library functions are written in C and are freestanding. Also included in the distribution is a just-

in-time compiler that can be used to optimize pattern matching. This is an optional feature that can be

omitted when the library is built.

THE BASIC LIBRARY FUNCTIONS

Written by: Philip Hazel

Email local part: ph10

Email domain: cam.ac.uk

University of Cambridge Computing Service, Cambridge, England.

Copyright (c) 1997-2015 University of Cambridge All rights reserved.

PCRE2 JUST-IN-TIME COMPILATION SUPPORT

Written by: Zoltan Herczeg

Email local part: hzmester

Email domain: freemail.hu

Copyright(c) 2010-2015 Zoltan Herczeg All rights reserved.



STACK-LESS JUST-IN-TIME COMPILER

Written by: Zoltan Herczeg

Email local part: hzmester

Email domain: freemail.hu

Copyright(c) 2009-2015 Zoltan Herczeg All rights reserved.

THE "BSD" LICENCE

Redistribution and use in source and binary forms, with or without modification, are permitted provided

that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

Neither the name of the University of Cambridge nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND

ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED

WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE

DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE

FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL

DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR

SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER

CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR

TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF

THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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