Tutorial 6

High Throughput Sequencing

HTS tools and analysis

• Review of resequencing pipeline

• Visualization - IGV

• Analysis platform – Galaxy

• Tuning up the pipelines

Review of resequencing pipeline

Demultiplexing

LaneUnknown inserts

Reference Genome

SampleMapping

Demultiplexing

Example of mapping parameters:• Number of mismatches per read • Scores for mismatch or gaps

Mapping parameters affect the rest of the analysis

Removing duplicates and non-unique mappings

Mapping

Demultiplexing

Reference Genome

Reference Genome

?

Resequencing/ Exome Pipeline

Coverage profile and variant calling

Removing duplicates and non-unique mappings

Mapping

Demultiplexing

Reference Genome

…ACTTCGTCGAAAGG…

G

Coverage profile and variant calling

Removing duplicates and non-unique mappings

Mapping

Demultiplexing

Variant filtering

Reference Genome

…ACTTCGTCGAAAGG…

Reference Genome

…ACTTCGTCGAAAGG…

Frequency >= 20%

Coverage >= 5

Variant calling

Removing duplicates and non-unique mappings

Mapping

Demultiplexing

Variant filtering

Genes and known variants

Reference Genome

…ACTTCGTCGAAATG… …GTCCCGTGATACTCCGT…

GA

rs230985Gene X

Resequencing results

Working with IGV:// . . / /http www broadinstitute org igv

Integrative Genome Viewer

IGV is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.

Genome used for mapping

Name of sample (BAM file)

Lowest resolution of the genome (zoomed out)

Zooming in

Zooming inCoverage track

Alignment track

Zoomed in until we get to the base pair value

SNP

Hover over the coverage track in order to see details regarding all bases in a specific position

Can we trust this SNP?

Hover over the alignment track in order to see details regarding a specific read

What is the quality of this read and its mapping?

Right-click on alignment track to change view of this track

Color reads by strand to verify there is no strand bias

Why and how to work with IGV

Base qualities, comparison between samples

False positive indels

Same mapping statistics – different meaning

What might cause this low percentage of mapping?

The sample contains a high percentage of contamination

The sample is very different from the reference genome

One image is worth a thousand words…

Structural Variations

Large deletion in the sample compared to the reference genome

Galaxy

:// . 2. . .https main g bx psu edu

/

Use your account name and password to login to Galaxy:

Uploading data to Galaxy

Use the “eye” icon to view the contents of a file

Mapping, filtering and conversion to BAM

Mapping

Filter SAM file

Convert SAM to BAM

Variant calling

Create pileup

Find variants

Tuning up the pipelines

1 mismatch per read

5 mismatches per read

How can mapping parameters affect the results

False positives vs. true negatives

3-bases insertion

One pipeline for all projects?

How can you tune your analysis?Try different programs.

Mapping:– Change mapping parameters– Use non-unique mappings– Don’t filter duplicates

Variants:– Change variant filtration – Change variant merging – penetrance, different heredity, low coverage in

one individual…– Look for bigger variants: big insertions/ deletions, inversions, copy number

variations etc.