MSIsensor is a C++ program for automatically detecting somatic and germline variants at microsatellite regions. It computes length distributions of microsatellites per site in paired tumor and normal sequence data, subsequently using these to statistically compare observed distributions in both samples. Comprehensive testing indicates MSIsensor is an efficient and effective tool for deriving MSI status from standard tumor-normal paired sequence data.
Version 0.2
Usage: msisensor <command> [options]
Key commands:
scan scan homopolymers and miscrosatelites
msi msi scoring
msisensor scan [options]:
-d <string> reference genome sequences file, *.fasta format
-o <string> output homopolymer and microsatelites file
-l <int> minimal homopolymer size, default=5
-c <int> context length, default=5
-m <int> maximal homopolymer size, default=50
-s <int> maximal length of microsatellite, default=5
-r <int> minimal repeat times of microsatellite, default=3
-p <int> output homopolymer only, 0: no; 1: yes, default=0
-h help
msisensor msi [options]:
-d <string> homopolymer and microsatellites file
-n <string> normal bam file ( bam index file is needed )
-t <string> tumor bam file ( bam index file is needed )
-o <string> output distribution file
-e <string> bed file, to select a few resions
-f <double> FDR threshold for somatic sites detection, default=0.05
-r <string> choose one region, format: 1:10000000-20000000
-l <int> mininal homopolymer size, default=5
-p <int> mininal homopolymer size for distribution analysis, default=10
-m <int> maximal homopolymer size for distribution analysis, default=50
-q <int> mininal microsatellites size, default=3
-s <int> mininal number of repeats in microsatellites for distribution analysis, default=5
-w <int> maximal microsatellites size for distribution analysis, default=40
-u <int> span size around window for extracting reads, default=500
-b <int> threads number for parallel computing, default=1
-x <int> output homopolymer only, 0: no; 1: yes, default=0
-y <int> output microsatellite only, 0: no; 1: yes, default=0
-h help
The Makefile assumes that you have the samtools source code in an environment variable $SAMTOOLS_ROOT.
you don't know what that means, then simply follow these steps from any directory that you have permissions to write into: Install some prerequisite packages if you are using Debian or Ubuntu:
sudo apt-get install git libbam-dev zlib1g-dev
If you are using Fedora, CentOS or RHEL, you'll need these packages instead:
sudo yum install git samtools-devel zlib-devel
Download the samtools-0.1.19 from SOURCEFORGE (http://sourceforge.net/projects/samtools/files/samtools/0.1.19):
tar jxf samtools-0.1.19.tar.bz2
cd samtools-0.1.19
make
export SAMTOOLS_ROOT=$PWD
Clone the msisensor repos, and build the msisensor binary:
git clone https://github.com/ding-lab/msisensor.git
cd msisensor
make
Now you can put the resulting binary where your $PATH can find it. If you have su permissions, then
I recommend dumping it in the system directory for locally compiled packages:
sudo mv msisensor /usr/local/bin/
We have also provided pre-build binary distributions for Linux x86_64 and Mac OS X in directory: ./binary
msisensor_Linux_x86_64: for Linux x86_64
msisensor_Mac_OS_X : for Mac OS X
-
Scan microsatellites from reference genome:
msisensor scan -d referen.fa -o microsatellites.list -
Msi scorring:
msisensor msi -d microsatellites.list -n normal.bam -t tumor.bam -e bed.file -o output.prefix -l 1 -q 1 -b 2Note: normal and tumor bam index files are needed in the same directory as bam files
There will be one microsatellite list output in "scan" step. Msi scorring step will give 4 output files based on given output prefix:
output.prefix
output.prefix_dis
output.prefix_germline
output.prefix_somatic
-
microsatellites.list: microsatellite list output ( columns with *_binary means: binary conversion of DNA bases based on A=00, C=01, G=10, and T=11 )
chromosome location repeat_unit_length repeat_unit_binary repeat_times left_flank_binary right_flank_binary repeat_unit_bases left_flank_bases right_flank_bases 1 10485 4 149 3 150 685 GCCC AGCCG GGGTC 1 10629 2 9 3 258 409 GC CAAAG CGCGC 1 10652 2 2 3 665 614 AG GGCGC GCGCG 1 10658 2 9 3 546 409 GC GAGAG CGCGC 1 10681 2 2 3 665 614 AG GGCGC GCGCG -
output.prefix: msi score output
Total_Number_of_Sites Number_of_Somatic_Sites % 640 75 11.72 -
output.prefix_dis: read count distribution (N: normal; T: tumor)
1 10529896 CTTTC 15[T] GAGAC N: 0 0 0 0 0 0 0 1 0 0 8 9 1 7 17 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 T: 0 0 0 0 0 0 0 0 0 1 19 14 17 9 32 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -
output.prefix_somatic: somatic sites detected ( FDR: false discovery rate )
chromosome location left_flank repeat_times repeat_unit_bases right_flank difference P_value FDR rank 1 16200729 TAAGA 10 T CTTGT 0.55652 2.8973e-15 1.8542e-12 1 1 75614380 TTTAC 14 T AAGGT 0.82764 5.1515e-15 1.6485e-12 2 1 70654981 CCAGG 21 A GATGA 0.80556 1e-14 2.1333e-12 3 1 65138787 GTTTG 13 A CAGCT 0.8653 1e-14 1.6e-12 4 1 35885046 TTCTC 11 T CCCCT 0.84682 1e-14 1.28e-12 5 1 75172756 GTGGT 14 A GAAAA 0.57471 1e-14 1.0667e-12 6 1 76257074 TGGAA 14 T GAGTC 0.66023 1e-14 9.1429e-13 7 1 33087567 TAGAG 16 A GGAAA 0.53141 1e-14 8e-13 8 1 41456808 CTAAC 14 T CTTTT 0.76286 1e-14 7.1111e-13 9 -
output.prefix_germline: germline sites detected
chromosome location left_flank repeat_times repeat_unit_bases right_flank genotype 1 1192105 AATAC 11 A TTAGC 5|5 1 1330899 CTGCC 5 AG CACAG 5|5 1 1598690 AATAC 12 A TTAGC 5|5 1 1605407 AAAAG 14 A GAAAA 1|1 1 2118724 TTTTC 11 T CTTTT 1|1
We provided one small sized sample data (tumor and matched normal bam files) for user to try msi scoring step. It is very simple to run this test using sample data:
cd ./test
bash run.sh
Please contact Beifang Niu by bniu@genome.wustl.edu and Kai Ye by kye@genome.wustl.edu if you have any questions.