MiRGator 3.0 – microRNA portal in Deep Sequencing era

MiRGator 3.0

:: DESCRIPTION

miRGator aims to be the microRNA (miRNA) portal encompassing microRNA diversity, expression profiles, target relationships, and various supporting tools.

::DEVELOPER

Ewha Research Center for Systems Biology (ERCSB)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 Jan;41(Database issue):D252-7. doi: 10.1093/nar/gks1168. Epub 2012 Nov 27.
MiRGator v3.0: a microRNA portal for deep sequencing, expression profiling and mRNA targeting.
Cho S1, Jang I, Jun Y, Yoon S, Ko M, Kwon Y, Choi I, Chang H, Ryu D, Lee B, Kim VN, Kim W, Lee S.

rSW-seq – Detection of Copy Number Alterations in Deep Sequencing data

rSW-seq

:: DESCRIPTION

rSW-seq is designed to identify copy number alterations between tumor-vs-matched normal genomes (or between normal-vs-normal genomes for CNV detection) from deep sequencing data generated by next-generation sequencing. Compared to other algorithms (BreakDancer or MoDIL) using PEM (paired-end mapping) signatures, rSW-seq uses ‘read-depth’ as primary measure, which can be applied to single-end sequencing read set.

::DEVELOPER

Tae-Min Kim . , Peter Park’s lab at CBMI, Harvard Medical School

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / MacOsX / Windows

:: DOWNLOAD

rSW-seq

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2010 Aug 18;11:432.
rSW-seq: algorithm for detection of copy number alterations in deep sequencing data.
Kim TM, Luquette LJ, Xi R, Park PJ.

EstMoi 1.03 – Estimating Multiplicity of Infection using Parasite Deep Sequencing data

EstMoi 1.03

:: DESCRIPTION

estMOI is a per-based software developed to estimate Multiplicity of Infection (MOI) in parasite genomic sequence data. It is primarily developed to address the limitations of current laboratory (PCR) based estimates of multiplicity using high throughput sequence data.

::DEVELOPER

PathogenSeq

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

EstMoi

:: MORE INFORMATION

Citation

Bioinformatics. 2014 May 1;30(9):1292-4. doi: 10.1093/bioinformatics/btu005. Epub 2014 Jan 17.
estMOI: estimating multiplicity of infection using parasite deep sequencing data.
Assefa SA1, Preston MD, Campino S, Ocholla H, Sutherland CJ, Clark TG.

MutationTaster 2021 – Mutation Prediction for the Deep-sequencing Age

MutationTaster 2021

:: DESCRIPTION

MutationTaster is a free web-based application to evaluate DNA sequence variants for their disease-causing potential. The software performs a battery of in silico tests to estimate the impact of the variant on the gene product / protein.

::DEVELOPER

MutationTaster team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

Steinhaus R, Proft S, Schuelke M, Cooper DN, Schwarz JM, Seelow D.
MutationTaster2021.
Nucleic Acids Res. 2021 Jul 2;49(W1):W446-W451. doi: 10.1093/nar/gkab266. PMID: 33893808; PMCID: PMC8262698.

Schwarz JM, Cooper DN, Schuelke M, Seelow D.
MutationTaster2: mutation prediction for the deep-sequencing age.
Nat Methods. 2014 Apr;11(4):361-2. doi: 10.1038/nmeth.2890. PMID: 24681721.

deepTools 3.5.1 – Tools for Exploring Deep Sequencing data

deepTools 3.5.1

:: DESCRIPTION

deepTools is a suite of python tools particularly developed for the efficient analysis of high-throughput sequencing data, such as ChIP-seq, RNA-seq or MNase-seq.

::DEVELOPER

he Bioinformatics Facility at the Max Planck Institute for Immunobiology and Epigenetics, Freiburg.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/ Linux / MacOsX
Python

:: DOWNLOAD

deepTools

:: MORE INFORMATION

Citation:

Ramírez F, Ryan DP, Grüning B, Bhardwaj V, Kilpert F, Richter AS, Heyne S, Dündar F, Manke T.
deepTools2: a next generation web server for deep-sequencing data analysis.
Nucleic Acids Res. 2016 Jul 8;44(W1):W160-5. doi: 10.1093/nar/gkw257. Epub 2016 Apr 13. PMID: 27079975; PMCID: PMC4987876.

Ramírez F, Dündar F, Diehl S, Grüning BA, Manke T.
deepTools: a flexible platform for exploring deep-sequencing data.
Nucleic Acids Res. 2014 Jul;42(Web Server issue):W187-91. doi: 10.1093/nar/gku365. Epub 2014 May 5. PMID: 24799436; PMCID: PMC4086134.

GenomeGems 3.0 – Evaluation of Genetic Variability from Deep Sequencing Data

GenomeGems 3.0

:: DESCRIPTION

GenomeGems’ aim is to provide investigators with a simple tool for sorting, analyzing, prioritizing and visualizing the Single Nucleotide Polymorphisms (SNPs) provided by bioinformatics analysis of data acquired by Deep Sequencing experiments. The key design feature is to facilitate the final steps of Deep Sequencing data analysis thus leading to a rapid shift to the next step of experimental mutation validation.

::DEVELOPER

Shomron Lab

:: SCREENSHOTS

:: REQUIREMENTS

Windows
MCR

:: DOWNLOAD

GenomeGems

:: MORE INFORMATION

Citation:

BMC Res Notes. 2012 Jul 2;5:338. doi: 10.1186/1756-0500-5-338.
GenomeGems: evaluation of genetic variability from deep sequencing data.
Ben-Zvi S1, Givati A, Shomron N.

CPSS 2.0 – Computational Platform for analysis of Small RNA Deep Sequencing data

CPSS 2.0

:: DESCRIPTION

CPSS is a web server which provides a comprehensively and systemically integrated pipeline for analyzing small RNA deep sequencing data.

::DEVELOPER

BioStaCs group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Web Browser

:: DOWNLOAD

:: MORE INFORMATION

Citation

CPSS: a computational platform for the analysis of small RNA deep sequencing data.
Zhang Y, Xu B, Yang Y, Ban R, Zhang H, Jiang X, Cooke HJ, Xue Y, Shi Q.
Bioinformatics. 2012 Jul 15;28(14):1925-7. doi: 10.1093/bioinformatics/bts282

MPFE 1.28.0 – Estimation of Methylation Pattern Distribution from Deep Sequencing data

MPFE 1.28.0

:: DESCRIPTION

MPFE is an R Bioconductor package for calculation of the estimated distribution over methylation patterns.

::DEVELOPER

Peijie Lin, Sylvain Foret, Conrad Burden <conrad.burden at anu.edu.au>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Linux/ MacOsX
R
BioConductor

:: DOWNLOAD

MPFE

:: MORE INFORMATION

Citation

Estimation of the methylation pattern distribution from deep sequencing data.
Lin P, Forêt S, Wilson SR, Burden CJ.
BMC Bioinformatics. 2015 May 6;16(1):145.

ONCOCNV 6.9 – Detection of Copy Number Changes in Deep Sequencing data

ONCOCNV 6.9

:: DESCRIPTION

ONCOCNV is a package to detect copy number changes in Deep Sequencing data developed by OncoDNA

::DEVELOPER

Boeva lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / MacOsX/ Windows
R
Perl
SAMtools

:: DOWNLOAD

ONCOCNV

:: MORE INFORMATION

Citation

Multi-factor data normalization enables the detection of copy number aberrations in amplicon sequencing data.
Boeva V, Popova T, Lienard M, Toffoli S, Kamal M, Le Tourneau C, Gentien D, Servant N, Gestraud P, Frio TR, Hupé P, Barillot E, Laes JF.
Bioinformatics. 2014 Jul 12. pii: btu436.

LayerCake 20171023 – Visual Comparison of Viral Deep Sequencing data

LayerCake 20171023

:: DESCRIPTION

LayerCake is a tool created for visualizing viral variation from next generation sequencing data

::DEVELOPER

collaboration between labs associated with UW Computer Sciences andUW Pathology & Laboratory Medicine Departments.

:: SCREENSHOTS

:: REQUIREMENTS

Windows / MacOsX
Java

:: DOWNLOAD

LayerCake

:: MORE INFORMATION

Citation

LayerCake: a tool for the visual comparison of viral deep sequencing data.
Correll M, Bailey AL, Sarikaya A, O’Connor DH, Gleicher M.
Bioinformatics. 2015 Jul 7. pii: btv407.