RRedon:Protocols/Variation pipeline

=get Reference Genome=

See main article: RRedon:Protocols/Variation_pipeline/Reference_genome

=Tools=
 * SAMTOOLS http://samtools.sourceforge.net/
 * MAQ
 * BWA

=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.

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."

=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:

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

=Coverage=

=SNP Calling=

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
 * Snp quality score >= 25
 * 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

 * http://www.broadinstitute.org/gsa/wiki/index.php/Indel_Genotyper_V2.0
 * PINDEL
 * Dindel http://sites.google.com/site/keesalbers/soft/dindel

=View the content of a BAM=

samtools view output.sorted.bam chr1 | more

=Consequences=

Simple tool developed by Pierre.

Internal Sanger tool.

Ensembl

 * problems with track at UCSC: see https://lists.soe.ucsc.edu/pipermail/genome/2010-May/022391.html

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

=Other tools=
 * FASTX-Toolkit:a collection of command line tools for Short-Reads FASTA/FASTQ files preprocessing