ASSIsT 1.02 – Automated SNP Scoring Tool

ASSIsT  1.02

:: DESCRIPTION

ASSIsT is a tool for the efficient filtering of Illumina Infinium/BeadExpress based SNP markers.

::DEVELOPER

the Computational Biology Center for the community of researchers at FEM

:: SCREENSHOTS

ASSIsT

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 ASSIsT

:: MORE INFORMATION

Citation:

ASSIsT: An Automatic SNP ScorIng Tool for in- and outbreeding species.
Di Guardo M, Micheletti D, Bianco L, Koehorst-van Putten HJ, Longhi S, Costa F, Aranzana MJ, Velasco R, Arús P, Troggio M, van de Weg EW.
Bioinformatics. 2015 Aug 6. pii: btv446

TagMix – Genome-wide Tag SNPs Selection

TagMix

:: DESCRIPTION

TagMix is an integrated cross-populations LD-based, haplotype-based and principal component analysis genome-wide tag SNPs selection algorithm to efficiently identify informative variants, prioritized across multi-populations of low LD and high diversity populations for custom chip array.

::DEVELOPER

Emile CHIMUSA

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 TagMix

:: MORE INFORMATION

VanillaICE 1.46.0 – Hidden Markov model for inferring Copy Number Alterations from SNP Arrays

VanillaICE  1.46.0

:: DESCRIPTION

VanillaICE is a Hidden Markov Models for characterizing chromosomal alterations in high throughput SNP arrays

::DEVELOPER

Division of Biostatistics and Bioinformatics – Johns Hopkins University Oncology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ WIndows/ MacOsX
  • R
  • BioConductor

:: DOWNLOAD

 VanillaICE

:: MORE INFORMATION

Citation

Ann Appl Stat. 2008 Jun 1;2(2):687-713.
Hidden Markov models for the assessment of chromosomal alterations using high-throughput SNP arrays.
Scharpf RB1, Parmigiani G, Pevsner J, Ruczinski I.

GPMAP – Global Haplotype Partitioning for Maximal Associated SNP Pairs

GPMAP

:: DESCRIPTION

GPMAP has been developed based on the open source code of Haploview (ver. 4.1). Therefore GPMAP basically inherits all Haploview functions plus the global partitioning method

::DEVELOPER

School of Biological Sciences, Iran

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux
  • Java

:: DOWNLOAD

GPMAP

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2009 Aug 27;10:269. doi: 10.1186/1471-2105-10-269.
Global haplotype partitioning for maximal associated SNP pairs.
Katanforoush A1, Sadeghi M, Pezeshk H, Elahi E.

GSAA 2.0 / GSAA-SNP / GSAA-Seq – Gene Set Association Analysis / Analysis-SNP / for RNA-Seq

GSAA 2.0 / GSAA-SNP / GSAA-Seq

:: DESCRIPTION

GSAA (Gene Set Association Analysis) is a computational method that integrates gene expression analysis with genome wide association studies to determine whether an a priori defined sets of genes shows statistically significant, concordant differences with respect to gene expression profiles and genotypes between two biological states. Gene sets are generally a group of genes that are putatively functionally related, co-regulated, or tightly linked on the same chromosome.

GSAA-SNP (Gene Set Association Analysis-SNP) is a computational method that determines whether an a priori defined sets of genes shows statistically significant, concordant differences with respect to genotypes between two biological states. Gene sets are generally a group of genes that are putatively functionally related, co-regulated, or tightly linked on the same chromosome.

GSAA-Seq (Gene Set Association Analysis for RNA-Seq) is a computational method that evaluates whether an a priori defined sets of genes shows statistically significant, concordant differences with respect to RNA-Seq gene expression profiles between two biological states. Gene sets are generally a group of genes that are putatively functionally related, co-regulated, or tightly linked on the same chromosome.

::DEVELOPER

Furey Lab at The University of North Carolina at Chapel Hill and Mukherjee Lab at Duke University.

:: SCREENSHOTS

GSAA

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

  GSAA / GSAA-SNP / GSAA-Seq

:: MORE INFORMATION

Citation

GSAASeqSP: a toolset for gene set association analysis of RNA-Seq data.
Xiong Q, Mukherjee S, Furey TS.
Sci Rep. 2014 Sep 12;4:6347. doi: 10.1038/srep06347.

Genome Res. 2012 Feb;22(2):386-97. doi: 10.1101/gr.124370.111. Epub 2011 Sep 22.
Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets.
Xiong Q, Ancona N, Hauser ER, Mukherjee S, Furey TS.

hapassoc 1.2-8 – Inference of Trait Associations with SNP Haplotypes and other attributes using the EM Algorithm

hapassoc 1.2-8

:: DESCRIPTION

The hapassoc R package implementing methods described in Burkett et al. (2004) for likelihood inference of trait associations with SNP haplotypes and other attributes using the EM Algorithm.

::DEVELOPER

SFU Statistical Genetics working group

:: REQUIREMENTS

:: DOWNLOAD

 hapassoc

:: MORE INFORMATION

Citation

Burkett et al. (2004)
A note on inference of trait associations with SNP haplotypes and other attributes in generalized linear models.
Hum Hered. 2004;57(4):200-6.

DIST 1.0.0 / DISTMIX v0.2.0- Direct Imputation of summary STatistics for unmeasured SNPs /from mixed Ethnicity Cohorts

DIST 1.0.0 / DISTMIX v0.2.0

:: DESCRIPTION

DIST is a software program for directly imputing the normally distributed summary statistics of unmeasured SNPs in a GWAS/meta-analysis without first imputing subject level genotypes.

DISTMIX is a very fast and novel software program for Directly Imputing summary STatistics (two-tailed Z-scores) for unmeasured SNPs from MIXed ethnicity cohorts using measured SNP summary data (including cohort allele frequencies) from the cohorts and external reference populations such as 1000 Genomes data.

::DEVELOPER

DIST team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 DIST / DISTMIX

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Nov 15;29(22):2925-7. doi: 10.1093/bioinformatics/btt500. Epub 2013 Aug 28.
DIST: direct imputation of summary statistics for unmeasured SNPs.
Lee D1, Bigdeli TB, Riley BP, Fanous AH, Bacanu SA.

DISTMIX: Direct imputation of summary statistics for unmeasured SNPs from mixed ethnicity cohorts.
Lee D, Bigdeli TB, Williamson VS, Vladimirov VI, Riley BP, Fanous AH, Bacanu SA.
Bioinformatics. 2015 Jun 9. pii: btv348.

SparSNP – Fit Lasso-penalized linear models to SNP data

SparSNP

:: DESCRIPTION

SparSNP is a tool for fitting lasso linear models for massive SNP datasets quickly and with very low memory requirements.

::DEVELOPER

Abraham lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R packages
  • ggplot2 >=0.9.3,
  • scales
  • grid
  • abind
  • ROCR

:: DOWNLOAD

  SparSNP

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2012 May 10;13:88. doi: 10.1186/1471-2105-13-88.
SparSNP: fast and memory-efficient analysis of all SNPs for phenotype prediction.
Abraham G, Kowalczyk A, Zobel J, Inouye M.

BS-SNPer 1.0 – SNP calling in Bisulfite-seq data

BS-SNPer 1.0

:: DESCRIPTION

BS-SNPer is an ultrafast and memory-efficient package, a program for BS-Seq variation detection from alignments in standard BAM/SAM format using approximate Bayesian modeling.

::DEVELOPER

BS-SNPer team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • perl

:: DOWNLOAD

 BS-SNPer

:: MORE INFORMATION

Citation:

BS-SNPer: SNP calling in Bisulfite-seq data.
Gao S, Zou D, Mao L, Liu H, Song P, Chen Y, Zhao S, Gao C, Li X, Gao Z, Fang X, Yang H, Ørntoft TF, Sørensen KD, Bolund L.
Bioinformatics. 2015 Aug 28. pii: btv507.

traseR 1.14.0 – GWAS Trait-associated SNP Enrichment Analyses in Genomic Intervals

traseR 1.14.0

:: DESCRIPTION

traseR performs GWAS trait-associated SNP enrichment analyses in genomic intervals using different hypothesis testing approaches, also provides various functionalities to explore and visualize the results.

::DEVELOPER

li chen<li.chen at emory.edu>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOSX
  • R/ BioConductor

:: DOWNLOAD

 traseR

:: MORE INFORMATION

Citation:

traseR: an R package for performing trait-associated SNP enrichment analysis in genomic intervals.
Chen L, Qin Z.
Bioinformatics. 2015 Dec 18. pii: btv741.