Tag: Differential Expression

EBSeq 1.33.0 / EBSeq-HMM 1.26.0 – RNA-Seq Differential Expression Analysis

EBSeq 1.33.0 / EBSeq-HMM 1.26.0

:: DESCRIPTION

R/EBSeq is an R package for identifying genes and isoforms differentially expressed (DE) across two or more biological conditions in an RNA-seq experiment.

EBSeq-HMM is a Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments.

::DEVELOPER

Kendziorski Lab

:: SCREENSHOTS

EBSeq

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • R package
  • BioConductor

:: DOWNLOAD

 R/EBSeq , EBSeq-HMM

:: MORE INFORMATION

Citation

EBSeq-HMM: A Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments.
Leng N, Li Y, Mcintosh BE, Nguyen BK, Duffin B, Tian S, Thomson JA, Dewey C, Stewart R, Kendziorski C.
Bioinformatics. 2015 Apr 5. pii: btv193.

Leng, N., J.A. Dawson, J.A. Thomson, V. Ruotti, A.I. Rissman, B.M.G. Smits, J.D. Haag, M.N. Gould, R.M. Stewart, and C. Kendziorski.
EBSeq: An empirical Bayes hierarchical model for inference in RNA-seq experiments,
Bioinformatics. 2013 Apr 15;29(8):1035-43.

BGmix 1.52.0 – Bayesian Mixture Model for Differential Expression

BGmix 1.52.0

:: DESCRIPTION

BGmix is a fully Bayesian mixture models for differential gene expression

::DEVELOPER

Dr Alexandra M Lewin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 BGmix

:: MORE INFORMATION

Citation

Lewin, A., Bochkina, N. and Richardson, S (2007)
Fully Bayesian mixture model for differential gene expression: simulations and model checks.
Statistical Applications in Genetics and Molecular Biology Vol. 6 : Iss. 1, Article 36.

deGPS 2.0 – Detecting Differential Expression in RNA-sequencing Studies

deGPS 2.0

:: DESCRIPTION

deGPS is a powerful and robust tool for detecting differential expression in RNA-Seq data.

::DEVELOPER

Chen Chu (chuchen.blueblues@gmail.com)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX / Windows
  • R

:: DOWNLOAD

 deGPS

:: MORE INFORMATION

Citation

deGPS is a powerful tool for detecting differential expression in RNA-sequencing studies.
Chu C, Fang Z, Hua X, Yang Y, Chen E, Cowley AW Jr, Liang M, Liu P, Lu Y.
BMC Genomics. 2015 Jun 13;16:455. doi: 10.1186/s12864-015-1676-0.

SC2P 1.0 – Two-phase differential Expression for single-cell RNA-seq

SC2P 1.0

:: DESCRIPTION

SC2P is a package designed for testing differential expression (DE) for data from single-cell RNA-seq experiment.

::DEVELOPER

Hao Wu, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows /Linux/ MacOsX
  • R

:: DOWNLOAD

SC2P

:: MORE INFORMATION

Citation

Wu Z, Zhang Y, Stitzel ML, Wu H.
Two-phase differential expression analysis for single cell RNA-seq.
Bioinformatics. 2018 Oct 1;34(19):3340-3348. doi: 10.1093/bioinformatics/bty329. PMID: 29688282; PMCID: PMC6157076.

compcodeR 1.26.1 – Benchmarking Differential Expression Methods for RNA-seq data

compcodeR 1.26.1

:: DESCRIPTION

compcodeR is an R package for comparing the results of multiple differential expression analysis methods applied to a common RNAseq data set. It also contains functionalities for simulating realistic count matrices and interfaces to several of the most widely used differential expression analysis methods for RNAseq data.

::DEVELOPER

Charlotte Soneson <Charlotte.Soneson at isb-sib.ch>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R package
  • BioConductor

:: DOWNLOAD

 compcodeR

:: MORE INFORMATION

Citation

Bioinformatics. 2014 May 9. [Epub ahead of print]
compcodeR – an R package for benchmarking differential expression methods for RNA-seq data.
Soneson C.

NOISeq 2.30.0 – Differential Expression in RNA-seq

NOISeq 2.30.0

:: DESCRIPTION

NOISeq is a non-parametric approach for the identification of differentially expressed genes from count data. NOISeq empirically models the noise distribution of count changes by contrasting fold-change differences (M) and absolute expression differences (D) for all the features in samples within the same condition.

::DEVELOPER

The Genomics of Gene Expression Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R Package
  • BioConductor

:: DOWNLOAD

 NOISeq

:: MORE INFORMATION

Citation

Tarazona S., García-Alcalde F., Ferrer A., Dopazo J., and Conesa A.
Differential expression in RNA-seq: a matter of depth.
Genome Res. 2011.

RNASeqPowerCalculator – Calculate the Power and Sample size for RNA-Seq Differential Expression

RNASeqPowerCalculator

:: DESCRIPTION

RNASeqPowerCalculator captures the dispersion in the data and can serve as a practical reference under the budget constraint of RNA-Seq experiments.

::DEVELOPER

Lana Garmire Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • R

:: DOWNLOAD

 RNASeqPowerCalculator

:: MORE INFORMATION

Citation

RNA. 2014 Nov;20(11):1684-96. doi: 10.1261/rna.046011.114. Epub 2014 Sep 22.
Power analysis and sample size estimation for RNA-Seq differential expression.
Ching T, Huang S, Garmire LX

ASC 0.1.4 – Empirical Bayes method to detect Differential Expression

ASC 0.1.4

:: DESCRIPTION

ASC (Analysis of Sequence Counts) borrows information across sequences to establish prior distribution of sample variation, so that biological variation can be accounted for even when replicates are not available. Compared current approaches that simply tests for equality of proportions in two samples, ASC is less biased towards highly expressed sequences and can identify more genes with a greater log fold change at lower overall abundance.

::DEVELOPER

Zhijin Wu PhD

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R package

:: DOWNLOAD

 ASC

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2010 Nov 16;11:564. doi: 10.1186/1471-2105-11-564.
Empirical bayes analysis of sequencing-based transcriptional profiling without replicates.
Wu Z, Jenkins BD, Rynearson TA, Dyhrman ST, Saito MA, Mercier M, Whitney LP.