Overview
The Pairwise Sequentially Markovian Coalescent (PSMC) method uses the genome sequence of a single individual to estimate demographic history covering a time span of thousands of generations.
Using
Use the module name psmc to discover versions available and to load the application.
Example
[]$ psmc
Program: psmc (Pairwise SMC Model)
Version: 0.6.5-r67
Contact: <http://hengli.uservoice.com/>
Usage: psmc [options] input.txt
Options: -p STR pattern of parameters [4+5*3+4]
-t FLOAT maximum 2N0 coalescent time [15]
-N INT maximum number of iterations [30]
-r FLOAT initial theta/rho ratio [4]
-c FILE CpG counts generated by cntcpg [null]
-o FILE output file [stdout]
-i FILE input parameter file [null]
-T FLOAT initial divergence time; -1 to disable [-1]
-b bootstrap (input be preprocessed with split_psmcfa)
-S simulate sequence
-d perform decoding
-D print full posterior probabilities
[]$ calD
Usage: calD [options] <U.fa> <V.fa> <X.fa> <Y.fa>
Options:
-w INT window size for block Jack-Knife [1000000]
-q INT quality threshold [0]
-M FILE mask regions in BED FILE [null]
-s INT step size (effective with -b) [100]
-b binary output
[]$ cntcpg
Usage: cntcpg [-b] [-s 100] [-n 0.9] <in.fa>
Output: 5 numbers: #CpG #CpG-ts #nonCpG #nonCpG-ts+tv #tv
[]$ fq2psmcfa
Usage: fq2psmcfa [-cnvx] [-q 10] [-g 10000] [-s 100] <in.fq>
[]$ mutDiff
Usage: mutDiff [-bl] [-s 100] <1.fa> <2.fa> <outgroup.fa>
[]$ splitfa
Usage: splitfa <in.fa> [trunk_size=500000]