MBCluster.Seq 1.0 – Model-Based Clustering for RNA-seq Data

MBCluster.Seq 1.0

:: DESCRIPTION

MBCluster.Seq : Cluster genes based on Poisson or Negative-Binomial model for RNA-Seq or other digital gene expression (DGE) data

::DEVELOPER

Yaqing Si <siyaqing at gmail.com>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R

:: DOWNLOAD

 MBCluster.Seq

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Jan 15;30(2):197-205. doi: 10.1093/bioinformatics/btt632. Epub 2013 Nov 4.
Model-based clustering for RNA-seq data.
Si Y1, Liu P, Li P, Brutnell TP.

BCseq – Accurate Single Cell RNA-seq Quantification with Bias Correction

BCseq

:: DESCRIPTION

BCseq (bias-corrected sequencing analysis) is a software tool to quantify gene expression from scRNA-seq.

:: DEVELOPER

Liang Chen’s Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/Windows
  • R

:: DOWNLOAD

BCseq

:: MORE INFORMATION

Citation:

BCseq: accurate single cell RNA-seq quantification with bias correction.
Chen L, Zheng S.
Nucleic Acids Res. 2018 Aug 21;46(14):e82. doi: 10.1093/nar/gky308.

WemIQ – Isoform Quantification method for RNA-seq data

WemIQ

:: DESCRIPTION

WemIQ is a software tool to quantify isoform expression and exon splicing ratios from RNA-seq data accurately and robustly.

::DEVELOPER

Liang Chen’s Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 WemIQ

:: MORE INFORMATION

Citation

WemIQ: An accurate and robust isoform quantification method for RNA-seq data.
Zhang J, Kuo CC, Chen L.
Bioinformatics. 2014 Nov 17. pii: btu757.

DaPars 0.9.1 – Dynamic analysis of Alternative PolyAdenylation from RNA-seq

DaPars 0.9.1

:: DESCRIPTION

DaPars is a novel bioinformatics algorithm for the de novo identification of dynamic APAs from standard RNA-seq.

::DEVELOPER

Li Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

 DaPars

:: MORE INFORMATION

Citation:

Xia, Z., Donehower, L.A., Wheeler, D.A., Cooper, T.A., Neilson, J.R., Wagner E.J., Li, W. 2014.
Dynamic Analyses of Alternative Polyadenylation from RNA-Seq Reveal 3′-UTR Landscape Across 7 Tumor Types.
Nature Communications, 5:5274.

RSeQC v3.0.1 – RNA-seq Quality Control package

RSeQC v3.0.1

:: DESCRIPTION

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput sequence data especially RNA-seq data. “Basic modules” quickly inspect sequence quality, nucleotide composition bias, PCR bias and GC bias, while “RNA-seq specific modules” investigate sequencing saturation status of both splicing junction detection and expression estimation, mapped reads clipping profile, mapped reads distribution, coverage uniformity over gene body, reproducibility, strand specificity and splice junction annotation

::DEVELOPER

Li Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX
  • Python

:: DOWNLOAD

 RSeQC

:: MORE INFORMATION

Citation:

Bioinformatics. 2012 Aug 15;28(16):2184-5. doi: 10.1093/bioinformatics/bts356. Epub 2012 Jun 27.
RSeQC: quality control of RNA-seq experiments.
Wang L, Wang S, Li W.

SINC – Scale-invariant Deep Neural-network Classifier for Bulk and Single-Cell RNA-seq.

SINC

:: DESCRIPTION

SINC is a deep-neural-network Classifier for Bulk and Single-Cell RNA-seq.

::DEVELOPER

Jun Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX/  Linux / WIndows
  • Python

SINC

:: MORE INFORMATION

Citation

Bioinformatics, 36 (6), 1779-1784 2020 Mar 1
SINC: A Scale-Invariant Deep-Neural-Network Classifier for Bulk and Single-Cell RNA-seq Data
Chuanqi Wang , Jun Li

mseq 1.2 – Modeling non-uniformity in Short-read Rates in RNA-Seq data

mseq 1.2

:: DESCRIPTION

mseq is an R package for modeling non-uniformity in short-read rates in RNA-Seq data.

::DEVELOPER

Jun Li

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX/  Linux / WIndows
  • R Package

:: DOWNLOAD

 mseq

:: MORE INFORMATION

Citation

Jun Li, Hui Jiang, and Wing H Wong (2010)
Modeling non-uniformity in short-read rates in RNA-Seq data.
Genome Biology 11(5): R50.

PSGInfer 1.2.1 – Inference of Alternative Splicing from RNA-Seq data with probabilistic Splice Graphs

PSGInfer 1.2.1

:: DESCRIPTION

PSGInfer (Probabilistic Splice Graph Inference) analyzes RNA-Seq data with probabilistic splice graph models of alternative RNA processing (transcription initiation, splicing, and polyadenylation).

::DEVELOPER

Laura H. LeGault , Colin Dewey

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

PSGInfer

:: MORE INFORMATION

Citation

Laura H. LeGault and Colin N. Dewey. (2013)
Inference of alternative splicing from RNA-Seq data with probabilistic splice graphs.
Bioinformatics. 29(18):2300-2310.

RobiNA 1.2.4 – Open Source Microarray and RNA-Seq Processing

RobiNA 1.2.4

:: DESCRIPTION

RobiNA is an integrated solution that consolidates all steps of RNA-Seq-based differential gene-expression analysis in one user-friendly cross-platform application featuring a rich graphical user interface. RobiNA accepts raw FastQ files, SAM/BAM alignment files and counts tables as input. It supports quality checking, flexible filtering and statistical analysis of differential gene expression based on state-of-the art biostatistical methods developed in the R/Bioconductor projects. In-line help and a step-by-step manual guide users through the analysis.

::DEVELOPER

Max Planck Institute for Molecular Plant Physiology

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

 RobiNA

:: MORE INFORMATION

Citation

Lohse M, Bolger AM, Nagel A, Fernie AR, Lunn JE, Stitt M, Usadel B. (2012)
RobiNA: A user-friendly, integrated software solution for RNA-Seq-based transcriptomics.
Nucleic Acids Res. 2012 Jul;40(Web Server issue):W622-7.

NVT 1.0 – R package for the Assessment of RNA-Seq Normalization methods

NVT 1.0

:: DESCRIPTION

NVT (NORMALIZATION VISUALIZATION TOOL) is an R package for the assessment of RNA-Seq normalization methods.

::DEVELOPER

CUBE – Bioinformatics and Computational Systems Biology, University of Vienna

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R

:: DOWNLOAD

NVT

:: MORE INFORMATION

Citation:

Bioinformatics, 32 (23), 3682-3684 2016 Dec 1
NVT: A Fast and Simple Tool for the Assessment of RNA-seq Normalization Strategies
Thomas Eder, Florian Grebien, Thomas Rattei