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Summary of Commands to Call Somatic SNVs in Tumor/Normal-Paired Samples

(Last updated: 8/29/2013)

  1. Summary of recently published somatic SNV-calling tools

Tool

Version

URL

SNV

Indel

CNV

Ref.

EBCall

2

https://github.com/friend1ws/EBCall


[1]

JointSNVMix

0.8(b2)

http://compbio.bccrc.ca



[2]

MuTect

1.1.4

http://www.broadinstitute.org/cancer/cga/mutect



[3]

SomaticSniper

1.0.2

http://genome.wustl.edu/software/somaticsniper



[4]

Strelka

0.4.10.2

ftp://strelka@ftp.illumina.com/


[5]

VarScan

2.3.5

http://varscan.sourceforge.net/

[6]


SNV: single nucleotide variant. Indel: insertion and deletion. CNV: copy number variation.

  1. EBCall

2.1 Installation

wget https://github.com/friend1ws/EBCall/archive/master.zip

unzip EBCall-master.zip

cd EBCall-master

vi config.sh ///change the path to SAMtools and R

make

chmod +x ebCall_v2.sh

2.2 Variant calling

///The following command line is from URL: https://github.com/friend1ws/EBCall

./ebCall_v2.sh

  1. JointSNVMix

3.1 Installation

Download JointSNVMix (http://code.google.com/p/joint-snv-mix/downloads/detail?name=JointSNVMix-0.8-b2.tar.gz&can=2&q=)

tar xzvf JointSNVMix-0.8-b2.tar.gz

setpkgs -a python ///Set the path to python. ‘setpkgs' is a special command provided in ACCRE (Vanderbilt Advanced Computing Center for Research & Education).

python setup.py build

python setup.py install --home=/mylocaldir/JointSNVMix-0.8-b2

cp jsm.py jsm2.py

vi jsm2.py ///add these two lines: import sys

///sys.path.append('/mylocaldir/JointSNVMix-0.8-b2/lib/python')

3.2 Variant calling

setpkgs –a python

python jsm2.py train hg19.fa normal.bam tumor.bam JointSNVMix.cfg --model=snvmix2 --skip_size=100

///Suggest to use skip_size=1000 for whole genome sequencing (WGS).

python jsm2.py classify hg19.fa normal.bam tumor.bam --parameters_file=JointSNVMix.cfg --out_file=JointSNVMix.output --post_process --somatic_threshold=0.2

3.3 Filtering

awk '{if(NR>1 && $10+$11>0.999 && $18>0.6)print}' JointSNVMix.output > JointSNVMix.output.hc

  1. MuTect

4.1 Installation

Download MuTect, dbSNP version 132 and COSMIC version 54 from Broad Institute: http://www.broadinstitute.org/cancer/cga/mutect_download

4.2 Variant calling

///Set Java1.6 environment

setpkgs -a java_1.6

///Run MuTect

java -Xmx20g -jar muTect-1.1.4.jar --num_threads 8 --analysis_type MuTect -R hg19.fa -cosmic chr.hg19_cosmic_v54_120711.vcf -dbsnp chr.dbsnp_132_b37.leftAligned.vcf --input_file:normal nomal.bam --input_file:tumor tumor.bam --out cal_stats.out --vcf mutation.vcf -cov coverage.wig.txt --enable_extended_output

///For WES data, provide genomic intervals to MuTect

java -Xmx20g -jar muTect-1.1.4.jar --num_threads 8 --analysis_type MuTect -R hg19.fa -cosmic chr.hg19_cosmic_v54_120711.vcf -dbsnp chr.dbsnp_132_b37.leftAligned.vcf --input_file:normal nomal.bam --input_file:tumor tumor.bam --out cal_stats.out --vcf mutation.vcf -cov coverage.wig.txt --enable_extended_output --intervals exome_target_regions.bed

  1. SomaticSniper

5.1 Installation

///Install somatic-sniper

git clone --recursive git://github.com/genome/somatic-sniper.git

cd somatic-sniper

export SAMTOOLS_ROOT=/mylocaldir/samtools-0.1.6

cmake .

make

///Install bam-readcount

git clone --recursive git://github.com/genome/bam-readcount.git

export SAMTOOLS_ROOT=/mylocaldir/samtools-0.1.17

cmake .

make

5.2 Variant calling

/mylocaldir/bam-somaticsniper -q 1 -Q 15 -F classic -f hg19.fa tumor.bam normal.bam snp.classic

5.3 Filtering

///The following filtering steps were suggested by tool developers (https://sites.google.com/site/kchengenomics/software/somaticsniper).

/mylocaldir/samtools-0.1.6/samtools pileup -sivf tumor.bam > indel.pileup

perl /mylocaldir/somatic-sniper/src/scripts/snpfilter.pl --snp-file snp.classic --indel-file indel.pileup --out-file snp.SNPfilter

perl /mylocaldir/somatic-sniper/src/scripts/prepare_for_readcount.pl --snp-file snp.SNPfilter

/mylocaldir/bam-readcount/bin/bam-readcount -b 15 -f hg19.fa -l snp.SNPfilter.pos tumor.bam > snp.SNPfilter.pos.rc

perl /mylocaldir/somatic-sniper/src/scripts/fpfilter.pl --snp-file snp.SNPfilter --readcount-file snp.SNPfilter.pos.rc

perl /mylocaldir/somatic-sniper/src/scripts/highconfidence.pl --snp-file snp.SNPfilter.fp_pass

  1. Strelka

6.1 Installation

wget ftp://strelka@ftp.illumina.com/v0.4.10.2/strelka_workflow-v0.4.10.2.tar.gz

tar xzvf strelka_workflow-v0.4.10.2.tar.gz

mv strelka_workflow-v0.4.10.2 strelka_workflow

cd strelka_workflow

make

///Create two configuration files, strelka_config_bwa_WGS.ini (isSkipDepthFilters = 0) and strelka_config_bwa_WES.ini (isSkipDepthFilters = 1) for WGS and WES data, respectively – suppose you use BWA for alignment.

6.2 Variant calling

/mylocaldir/strelka_workflow/configureStrelkaWorkflow.pl --tumor=tumor.bam --normal=normal.bam --ref=hg19.fa --config=/mylocaldir/strelka_workflow/strelka/etc/strelka_config_bwa_targeted.ini

cd strelkaAnalysis

make -j 8 ///Using 8 cores on the local machine

///Alternatively, use command: make –j 8 –C

  1. VarScan

7.1 Installation

wget http://sourceforge.net/projects/varscan/files/VarScan.v2.3.5.jar/download

7.2 Variant calling

samtools mpileup -C50 -Bf hg19.fa nomal.bam > normal.bam.mpileup

samtools mpileup -C50 -Bf hg19.fa tumor.bam > tumor.bam.mpileup

java -jar VarScan.v2.3.5.jar somatic normal.bam.mpileup tumor.bam.mpileup --output-snp snp --output-indel indel

7.3 Filtering

java -jar VarScan.v2.3.5.jar somaticFilter snp --indel-file indel --output-file snp.filtered

java -jar VarScan.v2.3.5.jar processSomatic snp.filtered

java -jar VarScan.v2.3.5.jar processSomatic indel

References

1. Shiraishi Y, Sato Y, Chiba K, Okuno Y, Nagata Y, Yoshida K, Shiba N, Hayashi Y, Kume H, Homma Y, Sanada M, Ogawa S, Miyano S: An empirical Bayesian framework for somatic mutation detection from cancer genome sequencing data. Nucleic Acids Res 2013.

2. Roth A, Ding J, Morin R, Crisan A, Ha G, Giuliany R, Bashashati A, Hirst M, Turashvili G, Oloumi A, Marra MA, Aparicio S, Shah SP: JointSNVMix: a probabilistic model for accurate detection of somatic mutations in normal/tumour paired next-generation sequencing data. Bioinformatics 2012, 28:907–913.

3. Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, Gabriel S, Meyerson M, Lander ES, Getz G: Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol 2013, 31:213–219.

4. Larson DE, Harris CC, Chen K, Koboldt DC, Abbott TE, Dooling DJ, Ley TJ, Mardis ER, Wilson RK, Ding L: SomaticSniper: identification of somatic point mutations in whole genome sequencing data. Bioinformatics 2012, 28:311–317.

5. Saunders CT, Wong W, Swamy S, Becq J, Murray LJ, Cheetham RK: Strelka: Accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics 2012.

6. Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, Miller CA, Mardis ER, Ding L, Wilson RK: VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res 2012, 22:568–576.


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