automated analysis of proteomics data on tap

8/14/2019 Automated Analysis of Proteomics Data on Tap

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Automated Analysis ofProteomics Data

on TapSimon Chiang

Wednesday, April 8, 2009


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Tap (Task Application)

a b1

b c1

c2

c

?

x

x1

x2

y

y1 z



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MS/MS IdentificationProtein Mixture

Digest to Peptides

Measure PeptideMass (MS)

Fragment, MeasureFragment Masses

(MSMS)

Identify Peptides

Correlate to Proteins



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Peptide Identification

Peptide Mass

Fragmentation Spectrum (match/score)

Experimental Predicted from DBWednesday, April 8, 2009


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Peptide Identification

Peptide Mass (filter)

Fragmentation Spectrum

Experimental Predicted from DbWednesday, April 8, 2009


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PTM Identification

Variable Modification



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Crosslinks

An unusual post-translational modification(modification by another peptide)

Same process, scoring algorithms

Main difference is prediction of crosslinkedspectrum



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Search Space



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Iterative Searching

Search normally

Harvest strong peptide identifications Generate subset database

Search unidentified for crosslinks vs subset



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Iterative Searching

Strong Ids

Subset(identified proteins)

Crosslink Db



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Variation

Search normally


Search unidentified for PTMs vs subset



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Variation

Search normally


Search unidentified for PTMs vs subset



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Variation

Search normally Harvest strong peptide identifications

Repeat (different search engine)



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Variation

Search normally Harvest strong peptide identifications



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Searching



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A Practical Matter

Not (mostly) an issue of having software

Time, complexity, configuration Processing of results

Mostly an issue ofusingsoftware



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Web Applications

Basis for most search engines/tools

Primarily a human interface Hard to automate a human*



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Tap-Mechanize

Mechanize - a library for running websites

Used to redirect/resubmit HTTP



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Tap-Mechanize

User Application



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Tap-Mechanize

User

Application



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Advantages

Utilizes native web interface

Robust and adaptable Multi-page requests supported

Lowest common denominator(works for most web apps)



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Tap (Task Application)

A framework to automate workflows

Define computational tasks

Join tasks into workflows



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Tasks

Submit data to a search engine

Download results

Convert a file format Perform a calculation

Generate a report ...



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Sequence

a b c



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Fork

a b

c



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Merge

a

b

c



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What Tap Does...

Programmers:

make/test, document, distribute Users:

install, learn, configure/use



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Usage

Standard command line Web interface in development



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Internals

Written in Ruby DSL for docs, configs

Distribution with RubyGems



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Examples



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Searching Perfect Data

Digest Protein(ALBU_HUMAN, Trypsin)

Generate Predicted Spectra(b,y ions, peptides n > 3 residues)

Search



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Workflow

Digest Predict Search

Protein [Spectra] Result URL[Peptides]



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Peptide Fragmentation



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Protein Identification



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Unassiged Peptide?



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Peptide Mass Error?



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Explanations

Unassigned peptides due to a serverconfiguration

Peptide mass error due to rounding(algorithm precision)

MinPepLenInSearch 5



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Classify Results by GO

Terms Search with Mascot

Search with GPM Extract Intersection of Results

Map Accessions to Entrez (PIR)

Classify with GoGetter



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Workflow

Load Data

mgf



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Workflow

Search/Export Mascot

Search/Export GPM



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Workflow

Intersect Results

Map Accessionsto Entrez

GoGetter

Graph



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Gene Ontology, GO Slims : Biological Process - Weighted (Dataset 1 name)

Biological process (go:0008150) (16.35%)

Cellular process (go:0009987) (16.18%)

Macromolecule metabolic process (go:0043170) (15.98%

Metabolic process (go:0008152) (15.70%)

Nucleobase, nucleoside, nucleotide and nucleic aci..Cell communication (go:0007154) (8.73%)

Regulation of biological process (go:0050789) (6.46%

Transport (go:0006810) (4.14%)

Response to stimulus (go:0050896) (2.48%)

Multicellular organismal development (go:0007275) (2Biosynthetic process (go:0009058) (0.67%)

Cell differentiation (go:0030154) (0.56%)

Cell death (go:0008219) (0.48%)

Electron transport (go:0006118) (0.48%)

Secretion (go:0046903) (0.33%)

Membrane fusion (go:0006944) (0.33%)

ALBU_HUMAN



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Recyling



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Digest Predict Search



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Digest Predict Load Search/Export Mascot

Search/Export GPM



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Simple Iterative Search

Search Partition Search (+ PTMs)



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Data Preparation

SearchConvertFormatExtract Data

.RAW [.dta] .mgf Result URL



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Mspire

ms-mascot

ms-uniprot

ms-in_silico

ms-gpm

ms-fasta

ms-unimod

ms-xcalibur

ms-prots

ms-data_explorer

constants

molecules

external



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Anticipated Usage

Programmer makes tasks

Researchers make workflows from tasks Definition

Configuration

Execution



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Importance

Expedited analysis, reproducibiliy

Evaluation studies (swap x for y) Teaching/Learning

Performance is not secondary. It affecteverything you do, it affects how you usean application. - Linus Torvalds



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Context



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TPP, TOPP, CPAS

Various pipeline suites

Pipeline in the sense of sequence

Relatively hard to install, use, extend

Many similarities, but only sequences



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Ongoing Research

Iterative searching - Nesvizhskii, 2006 Crosslink id via subsetting - Rinner, 2008 Subsetting search engine - Li, 2009

Enhancing peptide identification confidence bycombining search methods - Alves, 2008

Improving sensitivity by probabilistically combiningresults from multiple MS/MS search methodologies- Searle, 2008



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Future Directions

Web interface, cleanup

Implement iterative searching with subsets Development of crosslink search algorithm

(if necessary)



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Acknowledgments

Kirk Hansen

Hansen Lab

Ashley Zurawel Lauren Kiemele

Ahn Lab John Prince

Thesis Committee

Bob Hodges

Paul Fennessey Christine Wu Larry Hunter Brad Bendiak

Mark Duncan

automated analysis of proteomics data on tap

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