final%project% %week%13,%lecture%25%€¦ · 11/27/12% 1%...

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11/27/12 1 2012 ' BMMB 597D: Analyzing Next Genera<on Sequencing Data Week 13, Lecture 25 István Albert Biochemistry and Molecular Biology and Bioinforma<cs Consul<ng Center Penn State Final Project Will account for 50% of your the grade. It will consist of one or more datasets and a number of hypotheses that need to be tested Project given out Thursday, Dec 6 th and is due Tuesday, Dec 11 th Data and scripts for this lecture Data, code and scripts are packaged in lec25.tar.gz have to master too many tools and it is easy to get stuck Use it as a guide ' don’t just copy/paste Develop your own mini libraries of tools, shell scripts and methods Chip'Seq peak'caller Recap 1. A peak caller transforms aligned read coverages to intervals of enrichment

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Page 1: Final%Project% %Week%13,%Lecture%25%€¦ · 11/27/12% 1% 2012%'%BMMB%597D:%Analyzing%Next%Genera

11/27/12%

1%

2012%'%BMMB%597D:%Analyzing%Next%Genera<on%Sequencing%Data%

%%Week%13,%Lecture%25%

István'Albert''

Biochemistry%and%Molecular%Biology%%and%Bioinforma<cs%Consul<ng%Center%

%Penn%State%

Final%Project%

•  Will%account%for%50%%of%your%the%grade.%

•  It%will%consist%of%one%or%more%datasets%and%a%number%of%hypotheses%that%need%to%be%tested%

•  Project%given%out%Thursday,%Dec%6th%and%is%due%Tuesday,%Dec%11th%

%

Data%and%scripts%for%this%lecture%

•  Data,%code%and%scripts%are%packaged%in%lec25.tar.gz'

•  have%to%master%too%many%tools%and%it%is%easy%to%get%stuck%

•  Use%it%as%a%guide%'%%don’t%just%copy/paste%%

•  Develop%your%own%mini%libraries%of%tools,%shell%scripts%and%methods%%

Chip'Seq%peak'caller%Recap%

1.%A%peak%caller%transforms%aligned%read%coverages%to%intervals%of%enrichment%

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2%

The%most%common%misconcep<on%Cau<on:%this%a%personal%opinion%that%others%disagree%with%

Most'confusion'in'peak'calling'arises'from'combining'the'peak'calling'with'sta>s>cal'tes>ng'%•  A%peaks%means%a%region%that%appears%to%have%an%enrichment.%%

%•  The%opposite%of%peak%is%a%region%with%no'data'

%•  Some%peaks%may%be%caused%by%random%agglomera<on%of%data%–%but%that%

those%are%s<ll%peaks%–%only%that%they%are%peaks%occurring%by%random%chance%%

•  Most%published%peak%callers%will%o]en%remove%peaks%based%on%o]en%non'obvious%reasons%–%%

Crazy%peaks%by%MACS%

Understanding%peak%calling%

•  We%don’t%need%to%use%the%en<re%read!%Only%the%5’%end%ma`ers.%%

•  Transform%your%data%into%reads%that%are%1%bp%long%around%the%start%sites!%

•  See%the%README.txt%for%step%by%step%instruc<ons%

%

README.txt%in%the%data%

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Effects%of%increase%of%smoothing%Isolate%peak%calling%by%strands%

•  Tools%that%merge%strands%always%need%to%make%assump<ons%on%the%data%–%some<mes%it%is%not%obvious%what%these%are%

•  The%best%approach%is%to%operate%on%strand%individually,%then%combine%the%results%

•  Caveat:%low%coverage,%error%prone%data%will%be%even%more%difficult%to%analyze%once%split%%

Inves<ga<ng%two%error%models%%

Fidng%and%predic<ons%smoothing=5%

Fidng%and%predic<ons%smoothing=20%

DNA%fragment%length%=%factor%footprint%

Peaks%with%no%exclusion%zone%around%them%

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How%to%get%the%average%fragment%size?%

1.  Need%to%find%peak%pairs%2.  Compute%distance%between%their%limits%%Step%by%step:%•  Expand%each%fragment%to%the%le]%by%a%limit%•  Intersect%fragment%on%the%opposite%strand%•  Compute%distances%

Homework%25%

•  Run%the%pipeline%described%in%README.txt%%

•  Report%the%average%fragment%size%that%it%generates.%