Skip to content

jiujiezz/tsnad

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

TSNAD

An integrated pipeline for neoantigen prediction from NGS data.

Authors: Zhan Zhou, Jingcheng Wu, Xingzheng Lyu, Jianan Ren
Date: July 2021
Version: 2.0.1
License: TSNAD is released under GNU license
System: Linux
Contact: zhanzhou@zju.edu.cn

Introduction

An integrated software for cancer somatic mutation and tumour-specific neoantigen detection.

Installation and usage

There are two ways to install TSNAD:

  1. installed by docker without any other pre-installed tools (strongly recommand, can be used both in linux and windows)

  2. installed by github with all required tools installed (only can be used in linux)

Installed by docker

First, you need to install docker (https://docs.docker.com/)

then, type the following code to install TSNAD:

docker pull biopharm/tsnad:latest

it may take several hours to download because of the large size.

Usage by docker

You need to enter the TSNAD running enviromont with your path of WES/WGS/RNA-seq as the following command (RNA-seq is not necessary to provide):

docker run -it -v [dir of WES/WGS]/:/home/tsnad/samples -v [dir of RNA-seq]:/home/tsnad/RNA-seq -v [output dir]:/home/tsnad/results biopharm/tsnad:latest /bin/bash	

type the following command then the prediction of neoantigen from WES/WGS would start:

cd /home/tsnad

bash uncompress.sh

python TSNAD.py -I samples/ -R RNA-seq/ -V [grch37/grch38] -O results/

All results would be stored in the folder results/, and the final results of neoantigen are stored in the results/deephlapan_results/.

Installed by github

Requirements

TSNAD uses the following software and libraries:

  1. Trimmomatic 0.39 (In Tools/)
  2. BWA 0.7.17 (In Tools/)
  3. SAMtools 1.13 (In Tools/)
  4. GATK 4.2.0.0
  5. VEP 104
  6. hisat2 2.2.1
  7. Stringtie 2.1.6 (In Tools/)
  8. OptiType 1.3.5 (In Tools/)
  9. STAR 2.7 (In Tools/)
  10. Arriba 1.1.0 (In Tools/)
  11. DeepHLApan 1.1 (In Tools/)
  12. JAVA 1.8
  13. Python 2.7
  14. Perl 5.22

1-11 tools are better put in the folder Tools/.

Installation of each module

  1. Trimmomatic

     unzip Trimmomatic-*.zip
    
  2. BWA

     tar -xjvf bwa-*.tar.bz2
     cd bwa-*
     make
     
     vim ~/.bashrc
     export PATH=$PATH:/home/tsnad/Tools/bwa-0.7.17/
     source ~/.bashrc
    
  3. SAMtools

     sudo apt-get install libncurses5-dev
     sudo apt-get install libbz2-dev
     sudo apt-get install liblzma-dev
     tar -xjvf samtools-*.tar.bz2
     cd samtools-*
     ./configure
     make
     sudo make install
    
  4. GATK

     unzip gatk-*.zip
     sudo apt install openjdk-8-jdk-headless
     
     The necessary files for grch37
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/1000G_phase1.snps.high_confidence.b37.vcf.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/1000G_phase1.snps.high_confidence.b37.vcf.idx.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/dbsnp_138.b37.vcf.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/dbsnp_138.b37.vcf.idx.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/Mills_and_1000G_gold_standard.indels.b37.vcf.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/Mills_and_1000G_gold_standard.indels.b37.vcf.idx.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.fasta.gz  
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.fasta.fai.gz  
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.fasta.ann.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.fasta.bwt.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.fasta.amb.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.fasta.pac.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.fasta.sa.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.2bit.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/b37/human_g1k_v37.dict.gz
     
     The necessary files for grch38
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/1000G_phase1.snps.high_confidence.hg38.vcf.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/1000G_phase1.snps.high_confidence.hg38.vcf.gz.tbi
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/dbsnp_146.hg38.vcf.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/dbsnp_146.hg38.vcf.gz.tbi
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/Mills_and_1000G_gold_standard.indels.hg38.vcf.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/Mills_and_1000G_gold_standard.indels.hg38.vcf.gz.tbi
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/Homo_sapiens_assembly38.fasta.gz
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/Homo_sapiens_assembly38.fasta.fai
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/Homo_sapiens_assembly38.fasta.64.alt
     wget ftp://gsapubftp-anonymous@ftp.broadinstitute.org/bundle/hg38/Homo_sapiens_assembly38.dict
    

    uncompress all the downloaded files and put them in the same folder (e.g. gatk-*/b37/)

    to note, the chromosome name in dbsnp file is different from other files, so we need to transform it as follows :

     perl sub/transform.pl dbsnp_138.b37.vcf dbsnp_138.b37_adj.vcf
    
  5. VEP

     unzip ensembl-vep-release-*.zip
     cd ensembl-vep-release-*
     perl INSTALL.pl
    

    download the API, download the cache homo_sapiens_merged_vep_104_GRCh37.tar.gz for grch37, download the cache homo_sapiens_merged_vep_104_GRCh38.tar.gz for grch38.

    if it is not help, try following step:

     cd 
     mkdir src
     cd src
     wget ftp://ftp.ensembl.org/pub/ensembl-api.tar.gz
     wget https://cpan.metacpan.org/authors/id/C/CJ/CJFIELDS/BioPerl-1.6.924.tar.gz
     tar -xvf ensembl-api.tar.gz
     tar -xvf BioPerl-1.6.924.tar.gz
    
     PERL5LIB=${PERL5LIB}:${HOME}/src/BioPerl-1.6.924
     PERL5LIB=${PERL5LIB}:${HOME}/src/ensembl/modules
     PERL5LIB=${PERL5LIB}:${HOME}/src/ensembl-compara/modules
     PERL5LIB=${PERL5LIB}:${HOME}/src/ensembl-variation/modules
     PERL5LIB=${PERL5LIB}:${HOME}/src/ensembl-funcgen/modules
     PERL5LIB=${PERL5LIB}:${HOME}/src/ensembl-io/modules
     PERL5LIB=${PERL5LIB}:${HOME}/src/ensembl-tools
     export PERL5LIB
     
     sudo perl -MCPAN -e shell
     install Bio::PrimarySeqI
     install DBI
    
  6. Hisat2

     unzip hisat2-*.zip
     cd hisat2-*
     
     The necessary files for grch37
     wget https://genome-idx.s3.amazonaws.com/hisat/grch37_genome.tar.gz
     wget http://ftp.ensembl.org/pub/grch37/release-104/gtf/homo_sapiens/Homo_sapiens.GRCh37.87.gtf.gz
     tar -zxvf grch37_genome.tar.gz
     gunzip Homo_sapiens.GRCh37.87.gtf.gz -d
     
     The necessary files for grch38
     wget https://genome-idx.s3.amazonaws.com/hisat/grch38_genome.tar.gz
     wget http://ftp.ensembl.org/pub/release-104/gtf/homo_sapiens/Homo_sapiens.GRCh38.104.gtf.gz
     tar -zxvf grch38_genome.tar.gz
     gunzip Homo_sapiens.GRCh38.104.gtf.gz -d
    
  7. Stringtie

     tar -zxvf stringtie-*.tar.gz
    
  8. OptiType

     unzip OptiType.zip -d OptiType
     
     cd OptiType/glpk-5.0
     ./configure
     make && make install
     
     cd ../OptiType/hdf5-1.12.1
     ./configure
     make && make install
     
     vim /etc/ld.so.conf
     /usr/local/lib
     /sbin/ldconfig -v
     
     pip install numpy
     pip install pyomo
     pip install pysam
     pip install matplotlib
     pip install tables
     pip install pandas
     pip install future
    
  9. STAR

     unzip STAR-master.zip
     cd STAR-master/source
     make STAR
     
     The necessary files for grch37
     wget  ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_19/gencode.v19.annotation.gtf.gz
     
     The necessary files for grch38
     wget  ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_28/gencode.v28.annotation.gtf.gz
    
  10. Arriba

    tar -xvf arriba_v1.1.0.tar.gz
    cd arriba_v1.1.0 && make
    
  11. DeepHLApan

    unzip deephlapan.zip -d deephlapan
    cd deephlapan
    python setup.py install
    

Usage by github

  1. configure the file in the directory /config, take grch38 as example:

     trimmomatic_tool /home/tsnad/Tools/Trimmomatic-0.39/trimmomatic-0.39.jar
     bwa_folder /home/tsnad/Tools/bwa-0.7.17/
     samtools_folder /home/tsnad/Tools/samtools-1.13/
     gatk_tool /home/tsnad/Tools/gatk-4.2.0.0/gatk-package-4.2.0.0-local.jar
     VEP_folder /home/tsnad/Tools/ensembl-vep/
     hisat2_folder /home/tsnad/Tools/hisat2-2.1.0/
     stringtie_tool /home/tsnad/Tools/hisat2-2.1.0/stringtie-1.3.5.Linux_x86_64/stringtie
     Optitype_folder /home/tsnad/Tools/OptiType/
     star_folder	/home/tsnad/Tools/STAR/
     arriba_folder /home/tsnad/Tools/arriba_v1.1.0/
     ref_human_file /home/tsnad/Tools/gatk-4.2.0.0/grch38/Homo_sapiens_assembly38.fasta
     ref_1000G_file /home/tsnad/Tools/gatk-4.2.0.0/grch38/1000G_phase1.snps.high_confidence.hg38.vcf
     ref_Mills_file /home/tsnad/Tools/gatk-4.2.0.0/grch38/Mills_and_1000G_gold_standard.indels.hg38.vcf
     ref_dbsnp_file /home/tsnad/Tools/gatk-4.2.0.0/grch38/dbsnp_144.hg38_adj.vcf
     headcrop 10
     leading 3
     minlen 35
     needRevisedData True
     normal_f 0
     normal_reads 6
     slidingwindow 4:15
     threadNum 6
     trailing 3
     tumor_alt 5
     tumor_f 0.05
     tumor_reads 10
     typeNum 2
     laneNum 1
     partNum 2
    

replace the path of each tool or reference file in your own. The other parameters from headcrop to partNum should not be changed if you don't know their meanings.

  1. After configuration, return to the path where TSNAD.py located:

     python TSNAD.py -I [dir of WES/WGS] -R [dir of RNA-seq] -V [grch37/grch38] -O [dir of outputs]
    

The meaning of parameters in config file

headcrop: Cut the specified number of bases from the start of the read, default 10, used by trimmomatic
leading: Cut bases off the start of a read, if below a threshold quality,default 3, used by trimmomatic
minlen: Drop the read if it is below a specified length, default 35, used by trimmomatic
slidingwindow: Perform a sliding window trimming, cutting once the average quality within the window falls below a threshold, default 4:15, used by trimmomatic
normal_f: The maximum fraction of single nucleotide variant in normal sample, default 0, used for somatic mutation filtering.
normal_reads: The minimum number of sequence reads in normal sample, default 6, used for somatic mutation filtering.
tumor_alt: The minimum number of single nucleotide variant in tumor sample, default 5, used for somatic mutation filtering. tumor_f: The minimum fraction of single nucleotide variant in tumor sample, default 0.05, used for somatic mutation filtering.
tumor_reads: The minimum number of sequence reads in tumor sample, default 10, used for somatic mutation filtering.
typeNum: The number of types of input files(i.e. tumor and normal:2, tumor only :1), default:2. In this tool, it's always 2.
laneNum: The number of lanes when sequencing, default:1.
partNum: Single-read sequencing:1, paired-end sequencing:2, default:2.

As the default parameters, the input WGS/WES files in the input directory should be

	normal_L1_R1.fastq.gz
	normal_L1_R2.fastq.gz
	tumor_L2_R1.fastq.gz
	tumor_L2_R2.fastq.gz

The samples could be downloaded from following links:

normal_L1_R1.fastq.gz
normal_L1_R2.fastq.gz
tumor_L2_R1.fastq.gz
tumor_L2_R2.fastq.gz
rna_L1_R1.fastq.gz
rna_L1_R2.fastq.gz

To generate useable neoantigen predictions, the minimum depth should be 15X for WGS and 50X for WES, the recommended depth should be 30X for WGS and 100X for WES. For sample with WES tumor/normal data and RNA-seq data, it takes about 50 hours to finish neoantigen prediction in the Ubuntu system with 64G memory and 512G hard disk space.

Update log

v2.0.1

2021.07

  1. replace SOAP-HLA and Kourami with OptiType

  2. the version of each tool is listed as follows:

     Trimmomatic 0.39
     BWA 0.7.17
     SAMtools 1.13   
     GATK 4.2.0.0
     VEP 104  
     Hisat2 2.2.1 
     Stringtie 2.1.6
     OptiType 1.3.5
     STAR 2.7
     Arriba 1.1.0
     DeepHLApan 1.1
    

v2.0

2019.09

  1. provide the neoantigen prediction from indel and gene fusion
  2. replace NetMHCpan with DeepHLApan
  3. provide the docker version of TSNAD
  4. provide the web-service of TSNAD (http://biopharm.zju.edu.cn/tsnad/)

v1.2

2019.05

  1. VEP v94 -> v96
  2. Add the selection of grch38 when calling mutations.

v1.1

2018.11

  1. Trimmomatic v0.35 -> v0.38
  2. BWA v0.7.12 -> v0.7.17
  3. SAMtools v1.3 -> v1.9
  4. Picard v1.140 -> embedded in GATK
  5. GATK v3.5 -> v4.0.11.0
  6. Annovar -> VEP v94
  7. NetMHCpan v2.8 -> v4.0
  8. Add the function of RNA-seq analysis for neoantigen filter.

v1.0

2017.04

  1. GUI for neoantigen prediction
  2. Two parts: one for somatic mutation detection, another for HLA-peptide binding prediction.

About

Detecting somatic mutations and predicting tumor-specific neo-antigens

Resources

Stars

Watchers

Forks

Packages

No packages published