Please click here to see more about MSIsensor-pro in Wiki.

Welcome to try our new software MSIsensor-RNA for MSI detection with RNA-seq data!

Contact

If you want to apply the MSIsensor-pro to commercial purposes, please contact Peng Jia ([email protected]) or Kai Ye ([email protected]) for a license and get more services.

Questions

If you have any questions, please open an issue. If you don't get a prompt response(maybe two working day), please contact with Peng Jia ([email protected]).

License

MSIsensor-pro is free for non-commercial use by academic, government, and non-profit/not-for-profit institutions. A commercial version of the software is available and licensed through Xi’an Jiaotong University. For more information, please contact with Peng Jia ([email protected]) or Kai Ye ([email protected]).

Citation

Peng Jia, Xiaofei Yang, Li Guo, Bowen Liu, Jiadong Lin, Hao Liang, et al. MSIsensor-pro: fast, accurate, and matched-normal-sample-free detection of microsatellite instability. Genomics Proteomics Bioinformatics 2020,18(1). PDF

General introduction

MSIsensor-pro is an updated version of msisensor. MSIsensor-pro evaluates Microsatellite Instability (MSI) for cancer patients with next generation sequencing data. It accepts the whole genome sequencing, whole exome sequencing and target region (panel) sequencing data as input. MSIsensor-pro introduces a multinomial distribution model to quantify polymerase slippages for each tumor sample and a discriminative sites selection method to enable MSI detection without matched normal samples. For samples of various sequencing depths and tumor purities, MSIsensor-pro significantly outperformed the current leading methods in terms of both accuracy and computational cost. If you want to know more detail about MSIsensor-pro, please see the MSIsensor-pro Schematics and Internals page.

Scopes of MSIsensor-pro

MSIsensor-pro evaluates MSI status of a given sample with next generation sequencing (NGS) data. If you have normal-tumor paired DNA sequences, you can use msi (inherited from msisensor) module to score MSI status while pro module would be the option if matched normal is not available.

How to install MSIsensor-pro?

Directly using binary version

  wget https://github.com/xjtu-omics/msisensor-pro/raw/master/binary/msisensor-pro
  chmod +x msisensor-pro 
  export PATH=`pwd`:$PATH

Install Using Docker

   docker pull pengjia1110/msisensor-pro   
   docker run pengjia1110/msisensor-pro msisensor-pro

Install Using Bioconda

  conda install msisensor-pro
  

Install from source code

( Recommended For Developers )

Install the dependencies

Dependent packages including zlib, ncurses and nurses-dev are required for MSIsensor-pro. You may already have these prerequisite packages. If not, you need to run the following code to obtain dependent packages.

• For Debian or Ubuntu:

  sudo apt-get install libbz2-dev zlib1g-dev libcurl4-openssl-dev libncurses5-dev libncursesw5-dev
  

• For Fedora, CentOS or RHEL

  sudo yum install bzip2-devel xz-devel zlib-devel ncurses-devel ncurses
  

Build MSIsensor-pro from source code

• colne the repository from our github

  git clone https://github.com/xjtu-omics/msisensor-pro
  

• make

  cd msisensor-pro/
  ./INSTALL
  

• install

  sudo mv msisensor-pro /usr/local/bin/
  

How to use MSI ?

Usage:

  msisensor-pro <command> [options]

Key Commands:

• scan

  scan the reference genome to get microsatellites information
  

• baseline

   build baseline for tumor only detection
  

• msi

   evaluate MSI using paired tumor-normal sequencing data
  

• pro

   evaluate MSI using single (tumor) sample sequencing data 
  

See more detail in the Key Commands page and Best Practices page.

Files format

see details in the Files format page in WiKi.

Frequently asked questions

see details in the Frequently asked questions page in WiKi.

Citation

Peng Jia, Xiaofei Yang, Li Guo, Bowen Liu, Jiadong Lin, Hao Liang, et al. MSIsensor-pro: fast, accurate, and matched-normal-sample-free detection of microsatellite instability. Genomics Proteomics Bioinformatics 2020,18(1). PDF

Contributors

• Peng Jia
• Bowen Liu
• Hao Liang
• Mingzhe Duan