copynumber 1.12.0 – Segmentation of Single- and multi-track Copy Number data by penalized least Squares Regression

copynumber 1.12.0

:: DESCRIPTION
The R package copynumber is a software suite for segmentation of single- and multi-track copy number data using algorithms based on coherent least squares principles.

::DEVELOPER

Research Group for Biomedical Informatics (BMI)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • R / BioCOnductor

:: DOWNLOAD

 copynumber

:: MORE INFORMATION

Citation:

BMC Genomics. 2012 Nov 4;13:591. doi: 10.1186/1471-2164-13-591.
Copynumber: Efficient algorithms for single- and multi-track copy number segmentation.
Nilsen G1, Liestøl K, Van Loo P, Moen Vollan HK, Eide MB, Rueda OM, Chin SF, Russell R, Baumbusch LO, Caldas C, Børresen-Dale AL, Lingjaerde OC.

RABIT – Regression Analysis with Background InTegration

RABIT

:: DESCRIPTION

RABIT is a very efficient feature selection algorithm. It was applied to find tumor associated regulators in diverse cancer types.

::DEVELOPER

X. Shirley Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 RABIT

:: MORE INFORMATION

Citation

Inference of transcriptional regulation in cancers.
Jiang P, Freedman ML, Liu JS, Liu XS.
Proc Natl Acad Sci U S A. 2015 Jun 23;112(25):7731-6. doi: 10.1073/pnas.1424272112.

care 1.1.8 – High-Dimensional Regression and CAR Score Variable Selection

care 1.1.8

:: DESCRIPTION

The “care” package a novel multivariate algorithm for large scale SNP selection using CAR score regression, a promising new approach for prioritizing biomarkers.  CAR scores measure the correlation between the response and the Mahalanobis-decorrelated predictors. The squared CAR score is a natural measure of variable importance and provides a canonical ordering of variables. This package provides functions for estimating CAR scores, for variable selection using CAR scores, and for estimating corresponding regression coefficients. Both shrinkage as well as empirical estimators are available.

::DEVELOPER

Strimmer Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 care

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2012 Oct 31;13:284. doi: 10.1186/1471-2105-13-284.
A novel algorithm for simultaneous SNP selection in high-dimensional genome-wide association studies.
Zuber V, Duarte Silva AP, Strimmer K.

rrBLUP 4.3 – Ridge Regression and other kernels for Genomic Selection

rrBLUP 4.3

:: DESCRIPTION

rrBLUP is an R package for genomic selection and association mapping.

::DEVELOPER

Endelman Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R

:: DOWNLOAD

 rrBLUP

:: MORE INFORMATION

Citation

Jeffrey B. Endelman
Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP
The Plant Genome Vol. 4 No. 3, p. 250-255 doi:10.3835/plantgenome2011.08.0024

BLR 1.4 – Bayesian Linear Regression

BLR 1.4

:: DESCRIPTION

BLR (Bayesian Linear Regression) was designed to fit parametric regression models using different types of shrinkage methods. Linear regression with high-dimensional predictors (e.g. SNP) and pedigree.

::DEVELOPER

Gustavo de los Campos

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 BLR

:: MORE INFORMATION

Citation:

Gustavo de los Campos, Hugo Naya , Daniel Gianola , José Crossa , Andrés Legarra , Eduardo Manfredi , Kent Weigel and José Miguel Cotes
Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree.
Genetics. 182;375-385, 2009. (doi:10.1534/genetics.109.101501)

POME – Possion Mixed-Effects Regression for RNA-seq Data

POME

:: DESCRIPTION

POME (Poisson mixed-effects model) implement a novel method specifically designed for quantifying exon-level gene expression in RNA-Seq.

::DEVELOPER

Michael Yu Zhu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 POME

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Jan 1;28(1):63-8. doi: 10.1093/bioinformatics/btr616. Epub 2011 Nov 8.
Using Poisson mixed-effects model to quantify transcript-level gene expression in RNA-Seq.
Hu M, Zhu Y, Taylor JM, Liu JS, Qin ZS.

IsoLasso 2.6.1 – A LASSO Regression Approach to RNA-Seq Based Transcriptome Assembly

IsoLasso 2.6.1

:: DESCRIPTION

IsoLasso is an algorithm to assemble transcripts and estimate their expression levels from RNA-Seq reads.

::DEVELOPER

Wei Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • MatLab
  • C Compiler

:: DOWNLOAD

  IsoLasso

:: MORE INFORMATION

Citation

J Comput Biol. 2011 Nov;18(11):1693-707. doi: 10.1089/cmb.2011.0171. Epub 2011 Sep 27. IsoLasso: a LASSO regression approach to RNA-Seq based transcriptome assembly. Li W1, Feng J, Jiang T.

RAPID – Regression-based Accurate Prediction of protein Intrinsic Disorder Content

RAPID

:: DESCRIPTION

RAPID is a server providing fast and accurate sequence based prediction of protein disorder content.

::DEVELOPER

Kurgan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Biochim Biophys Acta. 2013 Aug;1834(8):1671-80. doi: 10.1016/j.bbapap.2013.05.022. Epub 2013 Jun 1.
RAPID: fast and accurate sequence-based prediction of intrinsic disorder content on proteomic scale.
Yan J1, Mizianty MJ, Filipow PL, Uversky VN, Kurgan L.

SIMreg 1.32 – Gene-trait Similarity Regression for Marker-set Association Analysis

SIMreg 1.32

:: DESCRIPTION

SIMreg is a tool to perform maker-set association analysis. Association analysis at gene, pathway, or exon levels (here by marker-set analysis) hold great promise in evaluating modest etiological effects of genes with GWAS or sequence data.

::DEVELOPER

Jung-Ying Tzeng

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX/Linux
  • R

:: DOWNLOAD

 SIMreg

 :: MORE INFORMATION

Citation

Am J Hum Genet. 2011 Aug 12;89(2):277-88. doi: 10.1016/j.ajhg.2011.07.007.
Studying gene and gene-environment effects of uncommon and common variants on continuous traits: a marker-set approach using gene-trait similarity regression.
Tzeng JY1, Zhang D, Pongpanich M, Smith C, McCarthy MI, Sale MM, Worrall BB, Hsu FC, Thomas DC, Sullivan PF.

MRHMMs 2 – Multivariate Regression Hidden Markov Models and the variantS

MRHMMs 2

:: DESCRIPTION

MRHMMs accommodates a variety of HMMs that can be flexibly applied to many biological studies and beyond.

::DEVELOPER

MRHMMs team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/ WIndows
  • C Compiler

:: DOWNLOAD

 MRHMMs

:: MORE INFORMATION

Citation:

Bioinformatics. 2014 Feb 27. [Epub ahead of print]
MRHMMs: Multivariate Regression Hidden Markov Models and the variantS.
Lee Y1, Ghosh D, Hardison RC, Zhang Y.