Standalone Software Packages

This software is free. You can redistribute and/or modify it under the terms of the GNU General Public License, as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed with helpful intent, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

Please give credit where credit is due. If you use functions from Mayo Clinic, please acknowledge the original contributor of the material.

Packages

hweStrata

Calculates an exact stratified test for HWE for diallelic markers, such as single nucleotide polymorphisms (SNPs), exact tests for HWE within each stratum, and an exact test for homogeneity of Hardy Weinberg disequilbrium. An update for version 1.0 verifies if the exact test for homogeneity can be computed; if not, the program calculates the p-value using an asymptotic test. Written in the C programming language, available as executable for Linux x_86_64 and Solaris, in addition to the source code. [05/2011]

• README.hweStrata
• User Manual (PDF)
• Package Source

SNPPicker

A post-processor to optimize the selection of tag SNPs from common bin-tagging programs. SNPPicker uses a multi-step search strategy in combination with a statistical model to produce optimal genotyping panels. Authors: Hugues Sicotte, David N. Rider, Gregory A. Poland, Neelam Dhiman, Jean-Pierre A. Kocher. [03/2011]

• README_SNPPicker
• SNPPicker2.zip

TREAT

A Targeted RE-sequencing Annotation Tool that offers an comprehensive, open framework, end-to-end solution for analyzing and interpreting targeted re-sequencing data. TREAT encompasses sequence alignment, variant calling, variant annotation, variant filtering, and visualization in one comprehensive analytic workflow. The rich set of annotations provided by TREAT enables the filtering of detected variants based on their functional characteristics, and visualizations at the variant positions allow the investigators to closely examine the identified variants of interest. An Amazon Cloud Image of TREAT is provided for researchers with no access to local bioinformatics infrastructure with instructions given in the tutorial below. The source code for local installation is available via the link below. Authors: Yan W. Asmann, Sumit Middha, Asif Hossain, Saurabh Baheti, Ying Li, High-Seng Chai, Zhifu Sun, Patrick H. Duffy, Ahmed A. Hadad, Asha Nair, Xiaoyu Liu, Yuji Zhang, Eric W. Klee, Jean-Pierre A. Kocher. [06/2011]

• TREATAmazonCloudTutorial.pdf
• User Manual (PDF)
• TREAT_1.0.1.tar.gz
  Note: This software package is over 10GB and may take substantial time to download.

SnowsShoes-FD

A bioinformatics tool to identify fusion transcripts from paired-end transcriptome sequencing data. The tool employs multiple steps of false positive filtering and nominates the fusion candidates with high confidence (approaching 100% true positive rate). The unique features of SnowShoes-FD include: (i) the ability to discover multiple fusion isoforms in which the two gene partners give rise to transcripts with different junctions; (ii) prediction of potential fusion mechanisms including inversion, translocation, and/or interstitial deletions; (iii) identification of whether the junction point in a fusion transcript occurs at the boundaries of known exons which implies the fusion events might have happened inside an intron in DNA and transcribed to the fusion transcript. Furthermore, the SnowShoes-FD greatly simplifies the validation process of the fusion candidates by giving a 5’ to 3’ oriented template region spanning fusion junction point which is long enough for designing primers for PCR validation of the fusion candidates. The SnowShoes-FD also predicts the protein sequences of the fusion genes using known transcript sequences of fusion partners and identifies in-frame vs. out-of-frame fusion products. In addition, the mutations including non-synonymous single amino acid changes and insertions at the fusion junction points for the in-frame fusion proteins are identified. The source codes of SnowShoes-FD are provided in two formats: one configured to run on the Sun Grid Engine for parallelization with shorter run time, and the other formatted to run on a single LINUX node.

Please contact the author, Dr. Yan Asmann, to gain access to the software.

SAAP-RRBS

Reduced representation bisulfite sequencing (RRBS) is a cost-effective approach for genome-wide methylation pattern profiling. Analyzing RRBS sequencing data is challenging and specialized alignment/mapping programs are needed. Although such programs have been developed, a comprehensive solution that provides researchers with good quality and analyzable data is still lacking.

To address this need, we have developed a Streamlined Analysis and Annotation Pipeline for RRBS data (SAAP-RRBS) that integrates read quality assessment/clean-up, alignment, methylation data extraction, annotation, reporting, and visualization. With this package, bioinformaticians or investigators can start from sequencing reads and get a fully annotated CpG methylation report quickly allowing more time for biological interpretation. The SAAP-RRBS program:

• Conducts read quality check, adapter trimming, alignment, methylation extraction, annotation and visualization for sequence reads in a fastq format (single or pair end RRBS).
• Conducts further downstream analyses for aligned BAM files from other RRBS aligners (single end RRBS).
• Conducts comprehensive annotations for a CpG list with chromosome and location.
• Is highly automatic and fast. To run the whole pipeline for a RRBS sample with 50 million of reads takes 4-6 hours.
• Offers two modes of run. For users without a cluster environment, it can be run in a single Linux machine, one sample at time (non-sge mode).
• Allows users with a cluster environment to submit jobs to the cluster to run multiple samples simultaneously for fast processing (sge mode).
• Can handle both single end and pair end sequencing.
• Provides summary reports for all samples in a run so users can quickly grasp their data.
• Adapts for a different aligner and is extensible to the whole genome sequencing data.

SAAP-RRBS_1.0.1.tar.gz

Contact: Baheti.Saurabh@mayo.edu; Sun.Zhifu@mayo.edu