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Software

The following is a categorized list of software available through the UT GSAF and/or TACC's life sciences group. Each page lists a summary of the software, the hardware it is currently installed on, links to user documentation, and helpful tips.

Many of these are available via the TACC module system (use module keyword or module spider to search).

The current listing of modules and versions available on Lonestar is also posted here.

In addition, the BioITeam maintains executables in /corral-repl/utexas/BioITeam/bin; we advise adding this directory to your path.

Contents

Galaxy Workflows

General purpose tools

Microarray data analysis tools

NGS Data Quality Control Tools

Mappers/Aligners

  • mapreads SOLiD data only, ungapped alignment
  • MAQ - best for short-read SNP calling; ungapped alignment
  • muscle - "old school" aligner - good for 454 amplicons
  • SOAP - very fast and versatile: any read length, gapped, paired-end, SNP calling
  • SSAHA & SSAHA2 - like Maq, fast for ungapped mapping - SNP calling, contig placement to reference, etc.
  • Bowtie - very fast, ungapped alignment. Does not support color space data
  • SHRiMP - A sensitive and accurate mapper. Supports color space data and gapped alignment.
  • BFAST - BLAT-like short read mapper. Natively supports SOLiD colorspace short reads.
  • BWA - The successor to MAQ; a BW mapper, but which allows for gaps and handles colorspace natively.
  • GMAP and GSNAP - Mappers for cDNA and very sensitive detection of short indels.
  • Mosaik - A suite of alignment and reference-guided assembly tools.
  • See Category:Mapper for more details.

Gene prediction tools

SNP discovery and Annotation

RNA-Seq Analysis

Splice Junction discovery


Genome Alignment and Visualization


De novo assembly

Transcriptome de novo assembly

ABI pipelines

454 Analysis tools
Current Roche/454 software versions on Fourierseq are all 2.5.3. Tarballs of various 454 software versions are available at /home/daras/454sw*


Useful scripts


Software users group meetings

  • Small-rna data analysis - Lessons learned during Sullivan data analysis
  • Mapping of short reads - Comparison of few publicly available mapping tools
  • No labels