yamet: Yet Another Methylation Entropy Tool

yamet is a command line tool written in C++ for computing entropies from methylation data.

yamet takes cell methylation data, reference site definitions and intervals of interest as input, then computes sample entropy and 2-mer shannon entropy. The sample entropy metric is computed for every cell at every interval of interest and also aggregated per cell. It is a measure of the entropy within individual cells. The 2-mer shannon entropy metric is computed for every interval of interest and is a measure of the entropy across cells. Both metrics take into account missing/uncovered positions in the methylation files using a reference file of positions.

Please also check (probably side branches of):

• https://github.com/emsonder/MethQuant
• https://github.com/emsonder/MethQuant-analysis

Note

yamet is currently under development! 🎊

Installation

Brew

yamet can be installed via brew on MacOS and Ubuntu

brew tap atchox/brew

# stable version
brew install yamet

# or build latest version from source
brew install --HEAD yamet

Compiled binaries

Compiled binaries can be downloaded from the releases page.

Build from source

git clone https://github.com/imallona/yamet.git
cd yamet/method
bash build.sh
./build/yamet --help

Usage

yamet processes (covered CpG) DNA methylation report(s), a reference file listing all CpG positions in a genome, and a bedfile specifying the genomic regions to calculate scores for (e.g. promoters, genes, etc). Full CLI args:

yamet

input:
  -c [ --cytosine_report ] arg          Per-cell cytosine report file(s) 
                                        (Bismark-like for covered cytosines). 
                                        Synonyms: --cytosine_report, --cell, 
                                        -c.
                                        Tab-separated, sorted by chromosome and
                                        position:
                                          chr   pos   meth_reads   total_reads 
                                          rate
  -r [ --cytosine_locations ] arg       Genomic locations of all cytosines 
                                        (typically CpGs). Synonyms: 
                                        --cytosine_locations, --reference, -r.
                                        Required to reconstruct contiguous CpG 
                                        sequences.
                                        Columns:
                                          chr   pos
  -i [ --regions ] arg                  BED file defining genomic regions where
                                        entropies will be computed. Synonyms: 
                                        --regions, --features, --target, 
                                        --intervals, -i.
                                        Columns:
                                          chr   start   end
  --skip-header-all [=arg(=1)]          Header lines to skip in all input files
                                        (default: 0). Synonyms: 
                                        --skip-header-all, --skip-header.
  --skip-header-cytosine_report [=arg(=1)]
                                        Header lines to skip in 
                                        cytosine_report/cell files (default: 
                                        0).
  --skip-header-cytosine_locations [=arg(=1)]
                                        Header lines to skip in 
                                        cytosine_locations/reference file 
                                        (default: 0).
  --skip-header-regions [=arg(=1)]      Header lines to skip in 
                                        regions/features/target/intervals file 
                                        (default: 0).

output:
  -d [ --det-out ] arg                  (optional) path to detailed output file
  -n [ --norm-det-out ] arg             (optional) path to detailed normalized 
                                        output file
  -m [ --meth-out ] arg                 (optional) path to average methylation 
                                        output file
  --all-meth [=arg(=true)] (=false)     If true, include all CpGs in 
                                        methylation summaries, including those 
                                        not used for template construction 
                                        (default: false).
  -o [ --out ] arg                      (optional) path to simple output file

resource utilisation:
  --cores arg (=0)                      number of cores used for simultaneously
                                        parsing methylation files
  --chunk-size arg (=64K)               size of the buffer (per file) used for 
                                        reading data. Can be specified as a 
                                        positive integer (bytes) or with a 
                                        suffix: B, K, M, G.

verbose:
  --print-intervals                     print parsed intervals file
  --print-reference                     print parsed reference file
  --print-sampens [=arg(=true)] (=true) print computed sample entropies

misc:
  -h [ --help ]                         print help message
  --version                             current version information

Repository

• .github/workflows and test: testing and build automations
• method: yamet code. See our releases (including binaries)
• simulations: yamet simulations
• workflow: yamet applications, except simulations
• yamet-r: yamet R package

You might want to browse the issues and PRs to explore current developments.

Running the analysis / reproducible figures

For simulations:

cd simulations
snakemake --use-conda --cores NUM_CORES

For other analysis (mind the slow data download):

cd workflow
snakemake --use-conda --cores NUM_CORES

License

GPLv3

Contact

izaskun.mallona at gmail.com

Acknowledgements

We thank Mark D. Robinson at UZH for partly funding this project.

We thank the Swiss National Science Foundation and the Graduate Campus at the University of Zurich for their support.

yamet builds on great FOSS components, including snakemake, and uses public data from epigenomic atlases and scientific publications. Thank you!