RRedon:Protocols/Variation pipeline: Difference between revisions

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{{RRedon}}
{{RRedon}}
=get Reference Genome=
=get Reference Genome=
Download the hg18/build36 from UCSC: [http://hgdownload.cse.ucsc.edu/goldenPath/hg18/chromosomes/ http://hgdownload.cse.ucsc.edu/goldenPath/hg18/chromosomes]
=get SamTools=
[http://samtools.sourceforge.net/ http://samtools.sourceforge.net/]
==Index the genome for samtools==


  samtools faidx hg18.fa
See '''main article''': [[RRedon:Protocols/Variation_pipeline/Reference_genome]]


=Tools=
* SAMTOOLS [http://samtools.sourceforge.net/ http://samtools.sourceforge.net/]
* [[RRedon:Protocols/Variation_pipeline/MAQ|MAQ]]
* [[RRedon:Protocols/Variation_pipeline/BWA|BWA]]


=Align FASTQs vs the reference=
=Align FASTQs vs the reference=
'''Mapping quality''' =30 = '''GOOD'''
Mapping quality is
  p(alignment is incorrect)* phred_qual)
function of
* repeats on refseq
* base qual of the read
* alignment parameters
* paired read are better
==BWA vs MAQ==
==BWA vs MAQ==
* '''repeat''' : (citing [http://biostar.stackexchange.com/questions/661 Biostarts]) "Maq maps a repeat read randomly"
* '''repeat''' : (citing [http://biostar.stackexchange.com/questions/661 Biostarts]) "Maq maps a repeat read randomly"
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==With BWA==
==With BWA==
See main article: [[RRedon:Protocols/Variation_pipeline/BWA|BWA]]
See main article: [[RRedon:Protocols/Variation_pipeline/BWA|BWA]]


==With MAQ==
==With MAQ==
* [http://maq.sourceforge.net/ http://maq.sourceforge.net/]
See main article about [[RRedon:Protocols/Variation pipeline/MAQ|MAQ]]
 
index the reference genome
 
  maq fasta2bfa hg18.fa hg18.bfa
 
* split fastq files in to chunks of 1 million PE reads {{fix-this|why?}}
** foreach fastq file :
 
  maq fastq2bfq $fq $bfq
  maq map -e 70 -a max_insert_size_for_lane -u $unmapped $mapped $bfa $bfq_1 $bfq_2
 
custom convert $unmapped > $unmapped.sam
 
  samtools view $unmapped.sam > $unmapped.bam
  samtools view $mapped > $mapped.bam
 
{{fix-this|what shall we do with unmapped ? look for indels ?}}
 
merge @bam using picardtools v1.08 MergeSamFiles.jar > $final.bam
 
  samtools sort -n $final.bam $final.nameSort
  samtools fixmate $final.nameSort.bam $final.fm.bam
  samtools sort $final.fm.bam $final.fm_coordSort


=Recalibrate=
=Recalibrate=
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  java -jar MarkDuplicates.jar I=chr1.sorted.bam  O=chr.markdup.bam METRICS_FILE=jeter.metrics
  java -jar MarkDuplicates.jar I=chr1.sorted.bam  O=chr.markdup.bam METRICS_FILE=jeter.metrics


=Coverage=
{{fix-this|With GATK ?}}
{{fix-this|'min depth': how do we use it , when ?}}


=SNP Calling=
=SNP Calling=
{{to-do|}}
{{to-do|}}
==samtools==
  samtools pileup -vcf ${HG18}.fa file.bam |\
  samtools/misc/samtools.pl varFilter -d 4 -D 1200 -Q 25
* d: Minimum depth is 4x    (around 8x is recommended)
* D: Maximum depth is 1200x (but no more than around 3x mean is recommended)
* Genotype quality score >= 20 {{fix-this|in varFilter ?}}
* Snp quality score >= 25 {{fix-this|in varFilter ?}}
* Q: RMS mapping quality >= 25 (Root Mean Square)
varFilter can also be used to keep one SNP in a 10pb window: cf. option in samtools/misc/samtools.pl varFilter
==Varscan==
see http://varscan.sourceforge.net/using-varscan.html
==Create the VCF==
==Create the VCF==


   java -jar GenomeAnalysisTK.jar -T UnifiedGenotyper -I markdup.bam -R hg18.fa  -varout markdup.bam.vcf -vf VCF  -pl SOLEXA
   java -jar GenomeAnalysisTK.jar -T UnifiedGenotyper -I markdup.bam -R hg18.fa  -varout markdup.bam.vcf -vf VCF  -pl SOLEXA
==Indels==
* http://www.broadinstitute.org/gsa/wiki/index.php/Indel_Genotyper_V2.0
* [[RRedon:Protocols/PINDEL|PINDEL]]
* [[RRedon:Protocols/DINDEL|Dindel]] http://sites.google.com/site/keesalbers/soft/dindel
=View the content of a BAM=
=View the content of a BAM=


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==KG==
==KG==
==PhdSNP==
==Panther==


==Ensembl==
==Ensembl==
* problems with track at UCSC: see [https://lists.soe.ucsc.edu/pipermail/genome/2010-May/022391.html https://lists.soe.ucsc.edu/pipermail/genome/2010-May/022391.html]
* problems with track at UCSC: see [https://lists.soe.ucsc.edu/pipermail/genome/2010-May/022391.html https://lists.soe.ucsc.edu/pipermail/genome/2010-May/022391.html]
==SIFT==
==SIFT==
See main article [[RRedon:Protocols/SIFT|SIFT]]


==Polyphen==
==Polyphen==
 
See main article [[RRedon:Protocols/Polyphen|Polyphen]]
==With SamTools==
==With SamTools==
   samtools pileup -vcf hg18.fa  markdup.bam
   samtools pileup -vcf hg18.fa  markdup.bam


=Abbreviations=
=Abbreviations=
* '''PTR''': Primary target region: exons.  Regions that we wanted to target  
* '''PTR''': Primary target region: exons.  Regions that we wanted to target  
* '''CTR''': Capture target region (baits). Regions actually covered by baits
* '''CTR''': Capture target region (baits). Regions actually covered by baits
* '''PCCR''' : Union of CTR and PTR regions
* '''CTRplus''' :Capture Target Regions ± 100bp flank
=References=
=References=
==InDels==
==InDels==

Latest revision as of 01:58, 18 June 2010

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get Reference Genome

See main article: RRedon:Protocols/Variation_pipeline/Reference_genome

Tools

Align FASTQs vs the reference

Mapping quality =30 = GOOD Mapping quality is

  p(alignment is incorrect)* phred_qual)

function of

  • repeats on refseq
  • base qual of the read
  • alignment parameters
  • paired read are better


BWA vs MAQ

  • repeat : (citing Biostarts) "Maq maps a repeat read randomly"
  • Mapping quality: (citing [ Biostars]):"If you want to find the SNPs, you do not really need to care about this. Maq will consider the mapping quality in genotype calling. If you want to pinpoint the structual variations with paired end reads, you should only pick up abnormal pairs with high mapping qualities (30, for example). If you are analysing ChIP-Seq data, setting a threshold on mapping quality may also be necessary."
  • dans le papier de Li and Durbin "Fast and Accurate Short Read Alignment with Burrows-Wheeler Transform" il est dit que MAQ surestime la mapping quality = proba(alignement incorrect) . BWA=a true hit can always be found. ← Fix this! english

With BWA

See main article: BWA

With MAQ

See main article about MAQ

Recalibrate

(citing)"After recalibration, the quality scores in the QUAL field in each read in the output BAM are more accurate in that the reported quality score is closer to its actual probability of mismatching the reference genome." ← Fix this! parameters, command line ?↓TODO


Remove Duplicates

(From Biostars:)Removing duplicates refers to multiple reads that match at the same position in the genome. This is different than one read (or read pair) mapping to multiple genome locations. MarkDuplicates finds sequence pairs that map to the same position, marking or removing the duplicates so you can work with unique pairs in downstream analyses. If you want them removed, use the REMOVE_DUPLICATES=true flag when running the program:


← Fix this! command line

java -jar MarkDuplicates.jar I=chr1.sorted.bam  O=chr.markdup.bam METRICS_FILE=jeter.metrics


Coverage

← Fix this! With GATK ?

← Fix this! 'min depth': how do we use it , when ?

SNP Calling

↓TODO

samtools

 samtools pileup -vcf ${HG18}.fa file.bam |\
  samtools/misc/samtools.pl varFilter -d 4 -D 1200 -Q 25
  • d: Minimum depth is 4x (around 8x is recommended)
  • D: Maximum depth is 1200x (but no more than around 3x mean is recommended)
  • Genotype quality score >= 20 ← Fix this! in varFilter ?
  • Snp quality score >= 25 ← Fix this! in varFilter ?
  • Q: RMS mapping quality >= 25 (Root Mean Square)

varFilter can also be used to keep one SNP in a 10pb window: cf. option in samtools/misc/samtools.pl varFilter

Varscan

see http://varscan.sourceforge.net/using-varscan.html

Create the VCF

 java -jar GenomeAnalysisTK.jar -T UnifiedGenotyper -I markdup.bam -R hg18.fa  -varout markdup.bam.vcf -vf VCF  -pl SOLEXA

Indels

View the content of a BAM

   samtools view output.sorted.bam chr1 | more

Consequences

Simple tool developed by Pierre.

Internal Sanger tool.

KG

PhdSNP

Panther

Ensembl

SIFT

See main article SIFT

Polyphen

See main article Polyphen

With SamTools

  samtools pileup -vcf hg18.fa  markdup.bam

Abbreviations

  • PTR: Primary target region: exons. Regions that we wanted to target
  • CTR: Capture target region (baits). Regions actually covered by baits
  • PCCR : Union of CTR and PTR regions
  • CTRplus :Capture Target Regions ± 100bp flank

References

InDels

  • ParMap, an algorithm for the identification of small genomic insertions and deletions in nextgen sequencing data. Khiabanian H, Van Vlierberghe P, Palomero T, Ferrando AA, Rabadan R. BMC Res Notes. 2010 May 27;3(1):147. PMID: 20507604

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