From the breseq manual pages:
breseq (pronounced: breeze-seq) is a computational pipeline for the analysis of short-read re-sequencing data (e.g. 454, Illumina, SOLiD, etc.).It uses reference-based alignment approaches to predict mutations in a sample relative to an already sequenced genome. breseq is intended for microbial genomes (<10 Mb) and re-sequenced samples that are only slightly diverged from the reference sequence (<1 mutation per 1000 bp).breseq‘s primary advantages over other existing software programs are that it can:Predict new sequence junctions, such as those associated with mobile element insertions, from single-end read data.Reliably identify short indel mutations by appropriately masking the ends of read alignments.Produce annotated output describing biologically relevant mutational events.
module load breseq
This loads breseq, bowtie and R.
>>>breseq -r NC_012967.gbk SRR030257_1.fastq SRR030257_2.fastq
libsequence is a C++ library designed to aid writing applications for genomics and evolutionary genetics. A large amount of the library is dedicated to the analysis of "single nucleotide polymorphism", or SNP data. The library is intended to be viewed as a "BioC++" akin to the bioperl project, although the scope of libsequence is limited in comparison. Much of the bioperl project concerns parsing the output of various bioinformatics programs, and the management of databases of biological data. perl is a good language for such things, and libsequence tries not to re-invent the wheel. Rather, the focus is on biological computation, such as the analysis of SNP data and sequence divergence, and the analysis of data generated from coalescent simulation.
From the Tensorflow website:
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.
Tensorflow is available for use on MSI's Mesabi k40 nodes. To load tensorflow into your environment, use the following command:
module load tensorflow
Tensorflow is frequently used via its python interface. To use tensorflow in this manner after loading in the module, use the following procedure:
python >>> import tensorflow as tf
There are a variety of tutorials available for using tensorflow on the official website.
RStudio provides open source and enterprise-ready professional software for the R statistical computing environment. RStudio is an IDE for the R programming language.
To run this software interactively in a Linux environment run the commands:
module load rstudio rstudio
RStudio depends on the R package. This being the case, loading rstudio will by default load some version of R. If you wish to use a different version with RStudio, try something like the following:
module load rstudio module unload R module load R/2.15.1
Note that not all installed versions of R are compatible with rstudio.
Several versions of rstudio are available. To see a list, run the following command:
module avail rstudio
RStudio home page
Additional documentation is available within the program through the help menu.
HyPhy stands for hypothesis testing using phylogenies. It is an open-source software package for the analysis of genetic sequences using techniques in phylogenetics, molecular evolution, and machine learning. It also features a complete graphical user interface (GUI) and a rich scripting language for limitless customization of analyses. Additionally, HyPhy features support for parallel computing environments (via message passing interface) and it can be compiled as a shared library and called from other programming environments such as Python or R.