Tag: Association

multiMiR 1.0.1 – Integration of microRNA-target Interactions along with their Disease and Drug Associations

multiMiR 1.0.1

:: DESCRIPTION

The R package multiMiR is a comprehensive collection of predicted and validated miRNA-target interactions and their associations with diseases and drugs.

::DEVELOPER

Yuanbin Ru at Windber Research Institute & Katerina Kechris at the University of Colorado Denver.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux
  • R

:: DOWNLOAD

 multiMiR

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2014;42(17):e133. doi: 10.1093/nar/gku631. Epub 2014 Jul 24.
The multiMiR R package and database: integration of microRNA-target interactions along with their disease and drug associations.
Ru Y, Kechris KJ, Tabakoff B, Hoffman P, Radcliffe RA, Bowler R, Mahaffey S, Rossi S, Calin GA, Bemis L, Theodorescu D.

LncDisease 1.41 – Predicting lncRNA-disease Associations

LncDisease 1.41

:: DESCRIPTION

LncDisease is a novel computational method and tool to predict the associations between lncRNAs and diseases

::DEVELOPER

the Cui Lab

:: SCREENSHOTS

LncDisease

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 LncDisease

:: MORE INFORMATION

Citation

LncDisease: a sequence based bioinformatics tool for predicting lncRNA-disease associations.
Wang J, Ma R, Ma W, Chen J, Yang J, Xi Y, Cui Q.
Nucleic Acids Res. 2016 Feb 16. pii: gkw093

miRSel – Automated Extraction of Associations between microRNAs and Genes from the Biomedical Literature

miRSel

:: DESCRIPTION

miRSel is resource for miRNA-gene associations. miRSel offers the currently largest collection of literature derived miRNA-gene associations.

::DEVELOPER

Institut für Informatik, Ludwig-Maximilians-Universität München

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2010 Mar 16;11:135. doi: 10.1186/1471-2105-11-135.
miRSel: automated extraction of associations between microRNAs and genes from the biomedical literature.
Naeem H, Küffner R, Csaba G, Zimmer R.

EMMAX Beta – Efficient Mixed-Model Association eXpedited

EMMAX Beta

:: DESCRIPTION

EMMAX is a statistical test for large scale human or model organism association mapping accounting for the sample structure. In addition to the computational efficiency obtained by EMMA algorithm, EMMAX takes advantage of the fact that each loci explains only a small fraction of complex traits, which allows us to avoid repetitive variance component estimation procedure, resulting in a significant amount of increase in computational time of association mapping using mixed model.

::DEVELOPER

Hyun Min Kang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 EMMAX

:: MORE INFORMATION

Citation

Nat Genet. 2010 Apr;42(4):348-54. Epub 2010 Mar 7.
Variance component model to account for sample structure in genome-wide association studies.
Kang HM, Sul JH, Service SK, Zaitlen NA, Kong SY, Freimer NB, Sabatti C, Eskin E.

LBL 1.0 / LBLGXE 1.3 – Bayesian Lasso for detecting Rare Haplotype-Environment Interaction

LBL 1.0 / LBLGXE 1.3

:: DESCRIPTION

LBL (Logistic Bayesian Lasso) is an R package that performs Logistic Bayesian Lasso for finding association of SNP haplotypes with a trait in a case-control setting. Bayesian lasso is used to find the posterior distributions of logistic regression coefficients, which are then used to calculate Bayes Factor to test for association with haplotypes.

LBLGXE expands on the original LBL. Gene-environment interaction (GXE)

::DEVELOPER

Statistical Genetics and Bioinformatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 LBL / LBLGXE

:: MORE INFORMATION

Citation

Genet Epidemiol. 2014 Jan;38(1):31-41. doi: 10.1002/gepi.21773. Epub 2013 Nov 23.
Detecting rare haplotype-environment interaction with logistic Bayesian LASSO.
Biswas S1, Xia S, Lin S.

Biswas S, and Lin, S. (2011)
Logistic Bayesian Lasso for identifying association with rare haplotyp es and application to age-related macular degeneration.
Biometrics. 2011 Sep 28. doi: 10.1111/j.1541-0420.

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

ncPred – ncRNA-Disease Association Prediction

ncPred

:: DESCRIPTION

ncPred is an algorithm for the inference of ncRNA-disease association based on recommendation technique

::DEVELOPER

ncPred team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

ncPred 

:: MORE INFORMATION

Citation:

Front Bioeng Biotechnol. 2014 Dec 12;2:71. doi: 10.3389/fbioe.2014.00071. eCollection 2014.
ncPred: ncRNA-Disease Association Prediction through Tripartite Network-Based Inference.
Alaimo S, Giugno R, Pulvirenti A

GeneSet2Diseases – Calculate Enrichment of Associations to Diseases on sets of human Genes

GS2D

:: DESCRIPTION

GS2D(Gene set to diseases) computes disease enrichment analysis on gene sets using biomedical literature data.

::DEVELOPER

Computational Biology and Data Mining (CBDM) Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Andrade-Navarro MA, Fontaine JF (2016).
Gene Set to Diseases (GS2D): Disease Enrichment Analysis on Human Gene Sets with Literature Data.
Genomics and Computational Biology, 2(1): e33.

GWiS 1.1 – a Gene-based Test of Association

GWiS 1.1

:: DESCRIPTION

GWiS (a novel Gene-Wide Significance) test uses greedy Bayesian model selection to identify the independent effects within a gene, which are combined to generate a stronger statistical signal.

::DEVELOPER

Joel Bader lab

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux

:: DOWNLOAD

 GWiS

:: MORE INFORMATION

Citation

PLoS Genet. 2011 Jul;7(7):e1002177. doi: 10.1371/journal.pgen.1002177. Epub 2011 Jul 28.
Gene-based tests of association.
Huang H, Chanda P, Alonso A, Bader JS, Arking DE.

Genie 2.7.2.1 – Analyze Association and Transmission Disequilibrium (TDT)

Genie 2.7.2.1

:: DESCRIPTION

GENIE (previously PEDGENIE and HAPMC) performs tests of association and transmission disequilibrium (TDT) between genetic markers and traits in studies of arbitrarily-sized families and/or independent individuals using Monte Carlo testing. For dichotomous traits, basic genotype-based or allele-based Chi-square statistics, OR, and a Chi-square trend statistic with user-defined weights, TDT, sib-TDT, combined-TDT are included. For quantitative outcomes, a difference in means test, ANOVA and QTDT are offered. Flexible haplotype testing and meta analysis across multiple centers are available. An automated haplotype building module, hapConstructor, is also offered that data mines multi-locus data for association signals. The Monte Carlo empirical significance assessment accounts for all relatedness between individuals for all tests

::DEVELOPER

Genetic Epidemiology University of Utah

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux/Windows/MacOsX
  • Java

:: DOWNLOAD

 Genie

:: MORE INFORMATION

Citation

Allen-Brady K, Wong J, Camp NJ (2006).
PedGenie: An Analysis Approach for Genetic Association Testing in Extended Pedigrees and Genealogies of Arbitrary Size.
BMC Bioinformatics 2006 7:209

Curtin K, Wong J, Allen-Brady K, Camp NJ (2007).
PedGenie: Meta Genetic Association Testing in Mixed Family and Case-Control Designs.
BMC Bioinformatics 2007 8:448

Curtin K, Wong J, Allen-Brady K, Camp NJ (2007).
Meta-genetic association of rheumatoid arthritis and PTPN22 using PedGenie 2.1
BMC Proc. 2007;1 Suppl 1:S12. Epub 2007 Dec 18