MISO 0.5.4 – RNA-Seq Experiments for Identifying Isoform Regulation

MISO 0.5.4

:: DESCRIPTION

MISO (Mixture of Isoforms) is a probabilistic framework that quantitates the expression level of alternatively spliced genes from RNA-Seq data, and identifies differentially regulated isoforms or exons across samples. By modeling the generative process by which reads are produced from isoforms in RNA-Seq, the MISO model uses Bayesian inference to compute the probability that a read originated from a particular isoform.

::DEVELOPER

Christopher Burge Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  MISO

:: MORE INFORMATION

Citation

Yarden Katz, Eric T. Wang, Edoardo M. Airoldi*, Christopher B. Burge*.
Analysis and design of RNA sequencing experiments for identifying isoform regulation
Nature Methods 2010 (7, 1009-1015)

deFuse 0.8.1 – Gene Fusion Discovery using RNA-Seq Data

deFuse 0.8.1

:: DESCRIPTION

deFuse is a software package for gene fusion discovery using RNA-Seq data. The software uses clusters of discordant paired end alignments to inform a split read alignment analysis for finding fusion boundaries. A classifier trained on real fusions and false positives is applied to the assembled sequences. The software produces a fully annotated output for each predicted fusion. The software is designed to be run out of the box with little configuration, and is compatible SGE, PBS and LSF compute clusters.

::DEVELOPER

Shah Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 deFuse

:: MORE INFORMATION

Citation

McPherson A, Hormozdiari F, Zayed A, Giuliany R, Ha G, et al. (2011)
deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data
PLoS Comput Biol 7(5): e1001138. doi:10.1371/journal.pcbi.1001138

ARCHS4 – All RNA-seq and CHIP-seq Signature Search Space

ARCHS4

:: DESCRIPTION

ARCHS4 is a web resource that makes the majority of published RNA-seq data from human and mouse available at the gene and transcript levels.

::DEVELOPER

Ma’ayan Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nat Commun. 2018 Apr 10;9(1):1366. doi: 10.1038/s41467-018-03751-6.
Massive mining of publicly available RNA-seq data from human and mouse.
Lachmann A, Torre D, Keenan AB, Jagodnik KM, Lee HJ, Wang L, Silverstein MC, Ma’ayan A.

BioJupies – Automatically Generates RNA-seq Data Analysis Notebooks

BioJupies

:: DESCRIPTION

BioJupies is a web application that enables the automated creation, storage, and deployment of Jupyter Notebooks containing RNA-seq data analyses.

::DEVELOPER

Ma’ayan Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Cell Syst. 2018 Nov 28;7(5):556-561.e3. doi: 10.1016/j.cels.2018.10.007. Epub 2018 Nov 14.
BioJupies: Automated Generation of Interactive Notebooks for RNA-Seq Data Analysis in the Cloud.
Torre D, Lachmann A, Ma’ayan A.

QAPA 1.3.0 – RNA-seq Quantification of Alternative Polyadenylation

QAPA 1.3.0

:: DESCRIPTION

QAPA (Quantification of APA) is a method that infers APA from conventional RNA-seq data.

::DEVELOPER

Morris Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R
  • Python

:: DOWNLOAD

QAPA

:: MORE INFORMATION

Citation

Genome Biol. 2018 Mar 28;19(1):45. doi: 10.1186/s13059-018-1414-4.
QAPA: a new method for the systematic analysis of alternative polyadenylation from RNA-seq data.
Ha KCH, Blencowe BJ, Morris Q

VASC – Variational Autoencoder for Single Cell RNA-seq datasets

VASC

:: DESCRIPTION

VASC (deep Variational Autoencoder for SCRNA-seq data) is a deep multi-layer generative model, for the dimension reduction and visualization. It can do nonlinear hierarchical feature representations and model the dropout events of scRNA-seq data. Tested on more than twenty datasets, VASC show better performances in most cases and higher stability compared with several dimension reduction methods. VASC successfully re-establishes the embryo pre-implantation cell lineage and its associated genes based on the 2D representation of a large-scale scRNA-seq from human embryos.

::DEVELOPER

Bioinformatics & Intelligent Information Processing Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python 3.5+
  • numpy 1.12.1
  • h5py 2.7.0
  • sklearn 0.18.1
  • tensorflow 1.1.0
  • keras 2.0.6

:: DOWNLOAD

VASC

:: MORE INFORMATION

Citation

VASC: dimension reduction and visualization of single cell RNA sequencing data by deep variational autoencoder.
Genomics, Proteomics & Bioinformatics 2018, 16(5):320-331.
Dongfang Wang, Jin Gu

DEGseq 1.38.0 – Differentially Expressed Gene Identification for RNA-seq data

DEGseq 1.38.0

:: DESCRIPTION

DEGseq is an R package to identify differentially expressed genes or isoforms for RNA-seq data from different samples

::DEVELOPER

DEGseq team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R package
  • Bioconductor

:: DOWNLOAD

  DEGseq

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Jan 1;26(1):136-8. doi: 10.1093/bioinformatics/btp612. Epub 2009 Oct 24.
DEGseq: an R package for identifying differentially expressed genes from RNA-seq data.
Wang L, Feng Z, Wang X, Wang X, Zhang X.

NLDMseq – Expression Calculation at both Gene and Isoform levels from RNA-seq data given a Reference Transcriptom

NLDMseq

:: DESCRIPTION

NLDMseq is a bioinformatics tool for expression calculation at both gene and isoform levels from RNA-seq data by considering isoform- and exon-specific read sequencing rate.

::DEVELOPER

Xuejun Liu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ MacOsX
  • Python

:: DOWNLOAD

 NLDMseq

:: MORE INFORMATION

Citation

Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate.
Liu X, Shi X, Chen C, Zhang L.
BMC Bioinformatics. 2015 Oct 16;16(1):332. doi: 10.1186/s12859-015-0750-6.

SNAPR – Scalable Nucleotide Alignment Program RNA-seq

SNAPR

:: DESCRIPTION

SNAPR is a new method for RNA-seq analysis, optimized for hundreds or even thousands of RNA-seq libraries. SNAPR reads from and writes to BAM format, automatically generates read counts, and accurately identifies viral/bacterial infections and gene fusions.

::DEVELOPER

The Hood-Price Lab for Systems Biomedicine

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ WIndows/ MacOsX
  • C++

:: DOWNLOAD

 SNAPR

:: MORE INFORMATION

CRAC 2.5.2 – An Integrated RNA-Seq Read Analysis

CRAC 2.5.2

:: DESCRIPTION

CRAC is designed to find splice junctions, fusion junctions, SNVs, indels in reads. It focuses on the unique location of a read. It performs particularly well on long reads. It is designed for resequencing projects and is therefore able to map reads coming from the same species or a close one.

::DEVELOPER

Bonsai Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Linux

:: DOWNLOAD

 CRAC

:: MORE INFORMATION

Citation

Genome Biol. 2013 Mar 28;14(3):R30.
CRAC: an integrated approach to the analysis of RNA-seq reads.
Philippe N, Salson M, Commes T, Rivals E.