snpEnrichR – Automating Enrichment analysis of GWAS SNPs

snpEnrichR

:: DESCRIPTION

snpEnrichR is an R package to analyze co-localization of SNPs and their proxies in genomic regions

::DEVELOPER

Computational systems biology group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R

:: DOWNLOAD

snpEnrichR

:: MORE INFORMATION

Citation

Bioinformatics, 34 (23), 4112-4114 2018 Dec 1
snpEnrichR: Analyzing Co-Localization of SNPs and Their Proxies in Genomic Regions
Kari Nousiainen , et al.

PC-select – Calculation of GWAS Association Statistics

PC-select

:: DESCRIPTION

PC-select calculates GWAS association statistics using a data-adaptive GRM that improves power over standard mixed models while simultaneously avoiding confounding from population stratification.

::DEVELOPER

Berger Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

PC-select

:: MORE INFORMATION

Citation:

Genetics. 2014 Jul;197(3):1045-9. doi: 10.1534/genetics.114.164285. Epub 2014 Apr 29.
Improving the power of GWAS and avoiding confounding from population stratification with PC-Select.
Tucker G, Price AL, Berger B

SNPAssociation – Detecting Two-locus Associations allowing for Interactions in GWAS

SNPAssociation

:: DESCRIPTION

SNPAssociation is a code for testing associations allowing for interactions in genome-wide association studies.

::DEVELOPER

Laboratory for Bioinformatics and Computational Biology, HKUST

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 SNPAssociation

:: MORE INFORMATION

Citation:

Bioinformatics. 2010 Oct 15;26(20):2517-25. doi: 10.1093/bioinformatics/btq486. Epub 2010 Aug 24.
Detecting two-locus associations allowing for interactions in genome-wide association studies.
Wan X1, Yang C, Yang Q, Xue H, Tang NL, Yu W.

PSIKO v2 – Infer Population Stratification on various levels in GWAS

PSIKO v2

:: DESCRIPTION

PSIKO (Population Structure Inference using Kernel-pca and Optimisation) is a software tool written in C++ for quick and accurate estimation of individual ancestry coefficients of a dataset exhibiting population structure.

::DEVELOPER

The UEA Computational Biology Laboratory at the University of East Anglia (UEA)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • g++

:: DOWNLOAD

PSIKO

:: MORE INFORMATION

Citation

PSIKO2: a fast and versatile tool to infer population stratification on various levels in GWAS.
Popescu AA, Huber KT.
Bioinformatics. 2015 Jul 2. pii: btv396.

B-LORE – Bayesian multiple logistic Regression for GWAS Meta-analysis

B-LORE

:: DESCRIPTION

B-LORE (Bayesian LOgistic REgression) is a command line tool that creates summary statistics from multiple logistic regression on GWAS data, and combines the summary statistics from multiple studies in a meta-analysis. It can also incorporate functional information about the SNPs from other external sources. Several genetic regions, or loci are preselected for analysis with B-LORE.

::DEVELOPER

Söding Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOs
  • C Compiler
  • Python
:: DOWNLOAD

B-LORE

:: MORE INFORMATION

Citation:

PLoS Genet. 2018 Dec 31;14(12):e1007856. doi: 10.1371/journal.pgen.1007856. eCollection 2018 Dec.
Bayesian multiple logistic regression for case-control GWAS.
Banerjee S, Zeng L, Schunkert H, Söding J.

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.

SNPfold 1.01 – Identify RiboSNitches by leveraging GWAS data and an Analysis of the mRNA Structural Ensemble

SNPfold 1.01

:: DESCRIPTION

SNPfold evaluates the effects of SNPs (Single Nucleotide Polymorphisms) on the ensemble structure of an RNA. It takes as input an RNA sequence and one or more SNPs, and then evaluates the structural consequences of the mutation by computing a WT/SNP correlation coefficient. The smaller the correlation the larger the structural effects of the SNP.

::DEVELOPER

The Laederach Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Python

:: DOWNLOAD

 SNPfold

:: MORE INFORMATION

Citation

PLoS Genet. 2010 Aug 19;6(8):e1001074. doi: 10.1371/journal.pgen.1001074.
Disease-associated mutations that alter the RNA structural ensemble.
Halvorsen M, Martin JS, Broadaway S, Laederach A.

fGWAS 2.0 – Functional GWAS software

fGWAS 2.0

:: DESCRIPTION

The fGWAS (Function Genome-wide association study) is a new concept to evaluate additive and dominant effect for every SNP and identify the significant SNPs from huge SNP data

::DEVELOPER

Center for Statistical Genetics, Penn State University

:: SCREENSHOTS

fGWAS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 fGWAS

:: MORE INFORMATION

Citation

Hum Genet. 2011 Jun;129(6):629-39. doi: 10.1007/s00439-011-0960-6. Epub 2011 Feb 4.
A dynamic model for genome-wide association studies.
Das K, Li J, Wang Z, Tong C, Fu G, Li Y, Xu M, Ahn K, Mauger D, Li R, Wu R.

HyperLasso – Simultaneous analysis of GWAs

HyperLasso

:: DESCRIPTION

HyperLasso is a software of simultaneous analysis of many SNPs and covariates

::DEVELOPER

BARGEN

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • C Compiler

:: DOWNLOAD

 HyperLasso

:: MORE INFORMATION

Citation

Genet Epidemiol. 2010 Dec;34(8):879-91. doi: 10.1002/gepi.20543.
SNP selection in genome-wide and candidate gene studies via penalized logistic regression.
Ayers KL, Cordell HJ.

EIGENSOFT plus 1.0 – Principal Components Analysis for Performing GWAS QC and primary analysis.

EIGENSOFT plus 1.0

:: DESCRIPTION

EIGENSOFTplus is a software for enhanced use of Principal Components Analysis for performing GWAS QC and primary analysis.

::DEVELOPER

 Dr Michael Weale’s Group

:: SCREENSHOTS

N/A

::REQUIREMENTS

:: DOWNLOAD

 EIGENSOFTplus

:: MORE INFORMATION

Citation

Weale ME (2010),
“Quality Control for Genome-Wide Association Studies”,
in Genetic Variation: Methods and Protocols, Methods in Molecular Biology, vol. 628, pp.341-372 (Eds. M. R. Barnes and G. Breen). Humana Press.

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