GIIRA 01_3 – RNA-Seq driven Gene Finding Incorporating Ambiguous Reads

GIIRA 01_3

:: DESCRIPTION

GIIRA is a gene prediction method that identifies potential coding regions exclusively based on the mapping of reads from an RNA-Seq experiment.

::DEVELOPER

Bernhard Y. Renard

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java
  • Python

:: DOWNLOAD

 GIIRA

:: MORE INFORMATION

Citation

Bioinformatics. 2014 Mar 1;30(5):606-13. doi: 10.1093/bioinformatics/btt577. Epub 2013 Oct 11.
GIIRA–RNA-Seq driven gene finding incorporating ambiguous reads.
Zickmann F1, Lindner MS, Renard BY.

R-SAP 1.1 – RNA-Seq Analysis pipeline

R-SAP 1.1

:: DESCRIPTION

 R-SAP is a user-friendly and fully automated bioinformatics pipeline that analyzes and quantitates high-throughput RNA-Seq datasets. R-SAP accurately characterizes various classes of transcripts resulted from aberrant splicing and chimeric transcripts. Expression level estimates are reported as RPKM (reads per kilobase of exon model per million mapped reads) values.

::DEVELOPER

McDonald Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Perl

:: DOWNLOAD

 R-SAP

:: MORE INFORMATION

Citation:

Mittal VK, McDonald JF. 2012.
R-SAP: a multi-threading computational pipeline for the characterization of high-throughput RNA-sequencing data.
Nucleic Acid Reseaech. Jan. 28;

scRNABatchQC v0.10.3 – multi-samples Quality Control for single cell RNA-seq data

scRNABatchQC v0.10.3

:: DESCRIPTION

scRNABatchQC is an R package for generating a HTML QC report to check and compare quality of multiple single cell RNA-seq datasets. scRNABatchQC supports multiple types of inputs, including gene-cell count matrices, 10x genomics, SingleCellExperiment or Seurat v3 objects.

::DEVELOPER

scRNABatchQC team

:: REQUIREMENTS

  • Linux
  • R

:: DOWNLOAD

scRNABatchQC

:: MORE INFORMATION

Citation

Liu Q, Sheng Q, Ping J, Ramirez MA, Lau KS, Coffey RJ, Shyr Y.
scRNABatchQC: multi-samples quality control for single cell RNA-seq data.
Bioinformatics. 2019 Dec 15;35(24):5306-5308. doi: 10.1093/bioinformatics/btz601. PMID: 31373345; PMCID: PMC6954654.

Yanagi – Segment-based RNA-seq analysis

Yanagi

:: DESCRIPTION

Yanagi is a tool which segments a transcriptome into disjoint regions to create a segments library from a complete transcriptome annotation that preserves all of its consecutive regions of a given length L while distinguishing annotated alternative splicing events in the transcriptome.

::DEVELOPER

HCBravo Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R
  • Python

:: DOWNLOAD

Yanagi

:: MORE INFORMATION

Citation

Gunady MK, Mount SM, Corrada Bravo H.
Yanagi: Fast and interpretable segment-based alternative splicing and gene expression analysis.
BMC Bioinformatics. 2019 Aug 13;20(1):421. doi: 10.1186/s12859-019-2947-6. PMID: 31409274; PMCID: PMC6693274.

consexpression – Tool for RNA-Seq analysis

consexpression

:: DESCRIPTION

The consexpression approach is a pipeline for expression analysis that adopts the identification of DEGs from the joint analysis of nine tools.

::DEVELOPER

consexpression team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows /Linux / MacOs
  • R
  • Python

:: DOWNLOAD

consexpression

:: MORE INFORMATION

Citation:

Costa-Silva J, Domingues D, Lopes FM.
RNA-Seq differential expression analysis: An extended review and a software tool.
PLoS One. 2017 Dec 21;12(12):e0190152. doi: 10.1371/journal.pone.0190152. PMID: 29267363; PMCID: PMC5739479.

AltAnalyze 2.1.4.3 – Microarry and RNA-Seq Analysis

AltAnalyze 2.1.4.3

:: DESCRIPTION

AltAnalyze is an easy-to-use application for microarry and RNA-Seq analysis. For splicing sensitive platforms (RNA-Seq or Affymetrix Exon, Gene and Junction arrays), AltAnalyze will assess alternative exon expression along protein isoforms, domain composition and microRNA targeting. In addition to splicing-sensitive platforms, AltAnalyze provides comprehensive methods for conventional arrays (RMA summarization, QC, statistics, annotation, clustering, lineage characterization and gene-set enrichement).

::DEVELOPER

the Nathan Salomonis laboratory at Cincinnati Children’s Hosptial Medical Center and the University of Cincinnati.

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Linux / MacOsX
  • Python

:: DOWNLOAD

 AltAnalyze

:: MORE INFORMATION

Citation:

Nucleic Acids Res. 2010 Jul;38(Web Server issue):W755-62. Epub 2010 May 31.
AltAnalyze and DomainGraph: analyzing and visualizing exon expression data.
Emig D, Salomonis N, Baumbach J, Lengauer T, Conklin BR, Albrecht M.

netSmooth v0.1.0 – A Network smoothing based method for single cell RNA-seq

netSmooth v0.1.0

:: DESCRIPTION

netSmooth is an R package for network smoothing of single cell RNA sequencing data. Using gene interaction networks such as protein- protein interactions as priors for gene co-expression, netsmooth improves cell type identification from noisy, sparse scRNA-seq data.

::DEVELOPER

Bioinformatics & Omics Data Science platform

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R
  • BioConductor

:: DOWNLOAD

netSmooth

:: MORE INFORMATION

Citation

Ronen J, Akalin A.
netSmooth: Network-smoothing based imputation for single cell RNA-seq.
F1000Res. 2018 Jan 3;7:8. doi: 10.12688/f1000research.13511.3. PMID: 29511531; PMCID: PMC5814748.

Spanki 0.5.0 – Analysis of Alternative Splicing from RNA-Seq data

Spanki 0.5.0

:: DESCRIPTION

Spanki (Splicing Analysis Kit) is a set of tools to facilitate analysis of alternative splicing from RNA-Seq data. Spanki compiles quantitative and qualitative information about junction alignments from input BAM files, and analyzes junction-level splicing along with pairwise-defined splicing events. A simulator is also included to evaluate junction detection performance.

::DEVELOPER

The University of Maryland Center for Bioinformatics and Computational Biology (CBCB)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Linux
  • Python
  • BioPython

:: DOWNLOAD

 Spanki

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2013 Nov 9;14:320. doi: 10.1186/1471-2105-14-320.
Design of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki).
Sturgill D1, Malone JH, Sun X, Smith HE, Rabinow L, Samson ML, Oliver B.

TIGAR 2.1 – Estimate Transcript Isoform abundances from RNA-Seq data

TIGAR 2.1

:: DESCRIPTION

TIGAR : Transcript isoform abundance estimation method with gapped alignment of RNA-Seq data by variational Bayesian inference

::DEVELOPER

Nagasaki Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/windows/MacOsX
  • Java

:: DOWNLOAD

 TIGAR

:: MORE INFORMATION

Citation

TIGAR2: sensitive and accurate estimation of transcript isoform expression with longer RNA-Seq reads
Naoki Nariai, Kaname Kojima, Takahiro Mimori, Yukuto Sato, Yosuke Kawai, Yumi Yamaguchi-Kabata and Masao Nagasaki
BMC Genomics, accepted (2014).

Bioinformatics. 2013 Jul 26. [Epub ahead of print]
TIGAR: transcript isoform abundance estimation method with gapped alignment of RNA-Seq data by variational Bayesian inference.
Nariai N, Hirose O, Kojima K, Nagasaki M.

DiffSplice 0.1.2beta – Discover Alternative Splicing Variants present in an RNA-seq dataset

DiffSplice 0.1.2beta

:: DESCRIPTION

DiffSplice is a novel tool for discovering and quantitating alternative splicing variants present in an RNA-seq dataset, without relying on annotated transcriptome or pre-determined splice pattern. For two groups of samples, DiffSplice further utilizes a non-parametric permutation test to identify significant differences in expression at both gene level and transcription level. DiffSplice takes as input the SAM files that supply the alignment of the RNA-seq reads on the reference genome, obtained from an RNA-seq aligner like MapSplice. The results of DiffSplice are summarized as a decomposition of the genome and can be visualized using the UCSC genome browser.

::DEVELOPER

Bioinformatics Lab @CS.UKy.edu

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux

:: DOWNLOAD

 DiffSplice

:: MORE INFORMATION

Nucleic Acids Res. 2013 Jan;41(2):e39. doi: 10.1093/nar/gks1026. Epub 2012 Nov 15.
DiffSplice: the genome-wide detection of differential splicing events with RNA-seq.
Hu Y, Huang Y, Du Y, Orellana CF, Singh D, Johnson AR, Monroy A, Kuan PF, Hammond SM, Makowski L, Randell SH, Chiang DY, Hayes DN, Jones C, Liu Y, Prins JF, Liu J.