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Sigflow: Streamline Analysis Workflows for Mutational Signatures

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Sigflow provides useful mutational signature analysis workflows. It can auto-extract mutational signatures, fit mutation data to all/specified COSMIC reference signatures (SBS/DBS/INDEL) and run bootstrapping analysis for studying signature stability.

Any bugs or suggestions please report to GitHub issues, I will respond as soon as possible.

Table of content

Installation

If you would like to use Docker, skip the following installation step and go to PART 'Use Sigflow docker image' directly.

Using Sigflow Docker image is recommended for users without experiences in programming, especially in R.

Requirements:

Steps:

  1. Install R - follow the instructions at https://cran.r-project.org/.
  2. Install R packages, run

install.packages("docopt") install.packages("BiocManager") BiocManager::install("sigminer", dependencies = TRUE)

Update Sigminer version

install.packages("remotes") remotes::install_github("ShixiangWang/sigminer")

Install specific version by

remotes::install_github("ShixiangWang/sigminer@v1.0.17")

  1. Clone this repository, run

$ git clone https://github.com/ShixiangWang/sigflow

  1. Link the R script as a executable file (command)

$ cd sigflow $ ln -s $PWD/sigflow.R /usr/local/bin/sigflow # You can choose another place instead of /usr/bin/sigflow

  1. Try calling sigflow

Maybe you need to restart your terminal.

Use Sigflow docker image

Use specified version (recommended way):

docker pull shixiangwang/sigflow:version, e.g.

$ docker pull shixiangwang/sigflow:1.0

NOTE: Sigflow version has no prefix v.

Current available tag versions:

Use latest version:

$ docker pull shixiangwang/sigflow:latest

The latest version uses the latest (successful build) commit from GitHub, so it may have not been prepared or fully tested. So, be careful!

Run the docker by:

$ docker run shixiangwang/sigflow

See test/test_docker.sh for examples.

If you want to go into the docker container terminal, run

$ docker run --rm --entrypoint /bin/bash -it shixiangwang/sigflow

Usage

Commands and options

All Sigflow commands and options are described as the following.

=================================================================
sigflow: Streamline Analysis Workflows for Mutational Signatures.

Author: Shixiang Wang (wangshx@shanghaitech.edu.cn)
Copyright: AFL@2020 [https://opensource.org/licenses/AFL-3.0]

Desc:
  There are several subcommands.
  ==
  extract - extract signatures by either automatic or semi-automatic way.
            Of note, when you use manual way, you need to run 2 times, 
            firstly you should set --manual to get signature estimation results,
            and secondly you should set --manual --number N to get N signatures.
  ==
  fit     - fit signatures in >=1 samples based on COSMIC reference signatures.
  ==
  bt      - run bootstrap signature fitting analysis in >=1 samples.
  ==
  show    - show some useful information or plots. See README for details.

Usage:
  sigflow extract --input=<file> [--output=<outdir>] [--mode=<class>] [--manual --number <sigs>] [--max <max>] [--genome=<genome>] [--nrun=<runs>] [--cores=<cores>] [--sigprofiler] [--refit] [--hyper] [--verbose]
  sigflow fit --input=<file> [--output=<outdir>] [--index=<index>] [--mode=<class>] [--genome=<genome>] [--verbose]
  sigflow bt  --input=<file> [--output=<outdir>] [--index=<index>] [--mode=<class>] [--genome=<genome>] [--nrun=<runs>] [--verbose]
  sigflow show [--isearch=<keyword>] [--index=<index> --mode=<class>] [--output=<outdir>] [--verbose]
  sigflow (-h | --help)
  sigflow --version

Options:
  -h --help     Show help message.
  --version     Show version.
  -i <file>, --input <file>       input CSV/EXCEL/MAF file or VCF directory path.
  -o <outdir>, --output <outdir>  output directory path [default: ./sigflow_result/].
  --index <index>                 reference signature index separated by comma, e.g. '1,2,3' [default: ALL].
  -m <class>, --mode <class>      extract/fit mode, can be one of SBS, DBS, ID, MAF (for three types), CN (not supported in fit subcommand) [default: SBS].
  --manual                        enable manual extraction, set -N=0 for outputing signature estimation firstly.
  -N <sigs>, --number <sigs>      extract specified number of signatures [default: 0].
  --max <max>                     maximum signature number, default is auto-configured, should >2 [default: -1].
  -g <genome>, --genome <genome>  genome build, can be hg19, hg38 or mm10, [default: hg19].
  -r <runs>, --nrun <runs>        run times of NMF (extract) or bootstrapping (bt) to get results [default: 30].
  -T <cores>, --cores <cores>     cores to run the program, large dataset will benefit from it [default: 1].
  --refit                         refit the de-novo signatures with quadratic programming or nnls (SigProfiler).
  --hyper                         enable hyper mutation handling in COSMIC signatures (not used by SigProfiler approach).
  --sigprofiler                   enable automatic extraction by SigProfiler software.
  --isearch <keyword>             search and how cancer type specific reference signature index by keyword, e.g. breast.
  -v, --verbose                   print verbose message.

=================================================================

Input

Sigflow supports input data in VCF/MAF/CSV/EXCEL format. The file format is auto-detected by Sigflow.

For SBS/DBS/INDEL data in CSV (including TSV) or EXCEL format, the following columns typically described in MAF format are necessary:

For copy number segment data in in CSV (including TSV) or EXCEL format, the following columns are necessary:

Use cases

Example datasets along with many example code are available in clone repository above (you can read it online at here).

The following parts give an example for each command.

Result directory of any command has the following structure.

extract command

$ # Assume you have done the clone step $ # git clone https://github.com/ShixiangWang/sigflow $ cd sigflow/test $ sigflow extract -i tcga_laml.maf.gz -o test_results/test_maf -m MAF -r 10 -T 4 --max 10

This will auto-extract SBS/DBS/INDEL signatures from data toga_laml.maf.gz (a gzipped MAF file from Maftools) by 10 Bayesian NMF runs with 4 computer threads and output results to directory test_results/test_maf. At default, Bayesian NMF approach is used, it starts from 10 signatures (set by --max) and reduces to a optimal signature number. If --sigprofiler is enabled, i.e.

$ sigflow extract -i tcga_laml.maf.gz -o test_results/test_maf -m MAF -r 10 -T 4 --max 10 --sigprofiler

Sigflow will use the SigProfiler to auto-extract signatures, here it will extract 2 to 10 signatures and determine the optimal solution.

NOTE, in practice, set -r to a value >=10 is recommended for auto-extraction with Bayesian NMF, >=100 for semi-automatic extraction with basic NMF and automatic extraction with SigProfiler (enabled by --sigprofiler).

Results of extract command have the following structure:

Here, no DBS records found in input data, so no corresponding result files exist.

fit command

$ # Assume you have done the clone step $ # git clone https://github.com/ShixiangWang/sigflow $ cd sigflow/test $ sigflow fit -i tcga_laml.maf.gz -o test_results/test_fitting -m MAF

This will auto-fit input data tcga_laml.maf.gz to COSMIC SBS/DBS/INDEL signatures. Signature exposure data tables and plots are outputed.

Results of fit command have the following structure:

image-20200909150037803

Here, no DBS records found in input data, so no corresponding result files exist.

legacy represents COSMIC v2 SBS signatures and SBS represents COSMIC v3 SBS signatures.

bt command

Bootstrapping analysis was performed to evaluate the stability of signature exposure. For a tumor, this analysis firstly resamples mutations based on the observed mutation type (component) frequency and then applies signature fitting to the bootstrapping samples. For example, if a tumor harbors 100 mutations and 20 mutations are classified into T[C>T]T, then we resample 100 mutations and the probability to assign these mutation to T[C>T]T is 0.2. If we repeat such process many times, we can estimate the confidence interval of exposure of a signature in this tumor.

More details please read paper Detecting presence of mutational signatures in cancer with confidence.

$ # Assume you have done the clone step $ # git clone https://github.com/ShixiangWang/sigflow $ cd sigflow/test $ sigflow bt -i tcga_laml.maf.gz -o test_results/test_bt -m SBS -r 5

This will resample mutation catalogue of each sample based on observed mutation type frequency and run signature fitting using COSMIC SBS/DBS/INDEL signatures. The process is repeated multiple times and controlled by option -r (here is 5). This bootstrap analysis is used to estimate the instability of signature exposure. Data tables and plots of bootstrap signature exposures, errors and p values under different exposure cutoff are outputed.

NOTE, in practice, set -r to a value >=100 is recommended.

Results of bt command have the following structure:

image-20200909152336875

show command

show command provides extra information to help user analyze signatures. This includes:

  1. Search cancer type specific signature indices, this may help user to set the reference indices in fit and bt commands. This information could read online.
  2. Generate COSMIC reference signature profiles.

For the no.1 task, one could run

$ sigflow show --isearch breast

This will generate the following output:

image-20200918150257473

For the no.2 task, one could run

sigflow show --mode SBS --index 1,2,3,7a -o test_show_sig_profile

This will generate signature profile for signature 1,2,3,7. For SBS, two versions of plots exist.

image-20200918150649303

COSMIC v2:

image-20200918150754770

COSMIC v3:

image-20200918150825289

How to use Docker to run Sigflow

If you use Docker to run Sigflow, you cannot directly call sigflow command. Instead, you should use sudo docker run --rm -v /your_local_path:/docker_path shixiangwang/sigflow to start a Docker container.

For example, if you want to accomplish the same task shown in extract command above, you need to run:

$ sudo docker run --rm -v /your_local_path:/docker_path shixiangwang/sigflow
extract -i /docker_path/tcga_laml.maf.gz
-o /docker_path/test_maf
-m MAF -r 10 -T 4 --max 10

Here,

Updates

Test

There are some example data sets in this repository, you can find how to test different workflows in test/test.sh. It is time consuming to run all tests, just pick an example test similar to your task and see how it works. Before releasing a new version of Sigflow, I would run all tests to make sure they work well.

Troubleshooting

  1. Error like the supplied end is > refwidth. ([#32])

The reference genome for variant calling is not (perfectly) match the specified genome in sig_tally(). If you make sure the reference genome is correct, please try finding the variant records with uncompatible position and removing them before rerun.

Other tools

Citation

If you are using Sigflow fow now in academic field, please cite:

Shixiang Wang, Ziyu Tao, Tao Wu, Xue-Song Liu, Sigflow: An Automated And Comprehensive Pipeline For Cancer Genome Mutational Signature Analysis, Bioinformatics, btaa895, https://doi.org/10.1093/bioinformatics/btaa895

License

This software is released under Academic Free License ("AFL") v.3.0

Copyright 2020 © Shixiang Wang, Xue-Song Liu