/multipool

This fork contains an update of the MULTIPOOL High-resolution genetic mapping for pooled sequencing with Python 2 code updated to Python 3

Primary LanguagePythonMIT LicenseMIT

Multipool 0.10.3

See the wiki page for more details, including usage examples and installation instructions.

To use this fork, pull with the command:

git clone https://github.com/clstacy/multipool.git

Note: this fork has been updated for use with Python3

Usage and options:

usage: mp_inference.py [-h] -n N [-m {replicates,contrast}] [-r RES] [-c CM]
                       [-t FILTER] [-np] [-o OUTFILE] [-v]
                       countfile [countfile ...]
    
Multipool: Efficient multi-locus genetic mapping with pooled sequencing,
version 0.10.3. See http://cgs.csail.mit.edu/multipool/ for more details.

positional arguments:
  countfile             Input file[s] of allele counts

optional arguments:
  -h, --help            show this help message and exit
  -n N, --individuals N
                        Individuals in each pool (required)
  -m {replicates,contrast}, --mode {replicates,contrast}
                        Mode for statistical testing. Default: replicates
  -r RES, --resolution RES
                        Bin size for discrete model. Default: 100 bp
  -c CM, --centimorgan CM
                        Length of a centimorgan, in base pairs. Default: 3300
                        (yeast average)
  -t FILTER, --truncate FILTER
                        Truncate possibly fixated (erroneous) markers.
                        Default: true
  -np, --noPlot         Turn off plotting output.. Default: false
  -o OUTFILE, --output OUTFILE
                        Output file for bin-level statistics
  --plotFile PLOTFILE   Write plot as png file.
  -v, --version         show program's version number and exit

Count file format:

A whitespace delimited file with a row for each marker (SNP or small indel). The first column reports the locus position in base pairs (used with the --centimorgan parameter to compute crossover probabilities). The second column reports the number of sequencing reads from the first analyzed strain and the third column reports the read count from the second strain.