Difference between revisions of "PGDSpider"

From UFRC
Jump to navigation Jump to search
m (Text replacement - "#uppercase" to "uc")
 
Line 21: Line 21:
  
 
<!--Modules-->
 
<!--Modules-->
==Required Modules==
+
==Environment Modules==
 
+
Run <code>module spider {{#var:app}}</code> to find out what environment modules are available for this application.
===Serial===
 
* {{#var:app}}
 
<!--
 
===Parallel (OpenMP)===
 
* intel
 
* {{#var:app}}
 
===Parallel (MPI)===
 
* intel
 
* openmpi
 
* {{#var:app}}
 
-->
 
 
==System Variables==
 
==System Variables==
 
* HPC_{{uc:{{#var:app}}}}_DIR - installation directory
 
* HPC_{{uc:{{#var:app}}}}_DIR - installation directory

Latest revision as of 19:04, 10 June 2022

Description

pgdspider website  

PGDSpider is a powerful automated data conversion tool for population genetic and genomics programs. It facilitates the data exchange possibilities between programs for a vast range of data types (e.g. DNA, RNA, NGS, microsatellite, SNP, RFLP, AFLP, multi-allelic data, allele frequency or genetic distances). Besides the conventional population genetics formats, PGDSpider integrates population genomics data formats commonly used to store and handle next-generation sequencing (NGS) data. Currently, PGDSpider is not meant to convert very large NGS files as it loads into memory the whole input file, whose size may exceed available RAM. However, since PGDSpider allows one to convert specific subsets of these NGS files into any other format, one could use this feature to calculate parameters or statistics for specific regions, and thus perform sliding window analysis over large genomic regions.

Environment Modules

Run module spider pgdspider to find out what environment modules are available for this application.

System Variables

  • HPC_PGDSPIDER_DIR - installation directory




Citation

If you publish research that uses pgdspider you have to cite it as follows:

Lischer HEL and Excoffier L (2012) PGDSpider: An automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics 28: 298-299.