CORA 1.1.5b – compressive-acceleration tool for NGS Read Mapping methods

CORA 1.1.5b

:: DESCRIPTION

CORA is a compressive-acceleration tool for NGS read mapping methods. When plugged into existing mapping tools, CORA achieves substantial runtime improvement through the use of compressive representation of the reads and a comprehensive homology map of the reference genome.

::DEVELOPER

Bonnie Berger 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

CORA

:: MORE INFORMATION

Citation:

Deniz Yorukoglu, Y. William Yu, Jian Peng, Bonnie Berger.
Compressive Mapping for Next-generation Sequencing
Nature Biotechnology 34, 374-376 (2016) doi:10.1038/nbt.3511.

NGSTools 2.0.0 – Analysis of Next Generation Sequencing (NGS) data

NGSTools 2.0.0

:: DESCRIPTION

NGSTools package provides an object model to enable different types of analyses of Next Generation Sequencing (NGS) data, and some utility programs to process reads aligned to different reference genomes. The most important tools in this package are SNVQ, an accurate Single Nucleotide Variants (SNV) detection and genotyping algorithm from base calls and quality scores and a rule set to merge read alignments to a CCDS transcripts library with alignments of the same reads to a reference assembly.

::DEVELOPER

Bioinformatics Lab , Computer Science & Engineering Dept. University of Connecticut

:: SCREENSHOTS

Command Line

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

NGSTools

:: MORE INFORMATION

Citation:

J. Duitama and P.K. Srivastava and I.I. Mandoiu,
Towards Accurate Detection and Genotyping of Expressed Variants fromWhole Transcriptome Sequencing Data
Proc. 1st IEEE International Conference on Computational Advances in Bio and Medical Sciences, pp. 87-92, 201

NGS QC Toolkit v2.3.3 – Toolkit for the Quality Control (QC) of Next Generation Sequencing (NGS) data.

NGS QC Toolkit v2.3.3

:: DESCRIPTION

NGS QC Toolkit comprises of user-friendly stand alone tools for quality control of the sequence data generated using Illumina and Roche 454 platforms with detailed results in the form of tables and graphs, and filtering of high-quality sequence data. It also includes few other tools, which are helpful in NGS data quality control and analysis.

::DEVELOPER

Mukesh Jain (mjain@nipgr.ac.in); Ravi Patel (ravi_patel_4@yahoo.co.in) @ National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, India

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Perl

:: DOWNLOAD

 NGS QC Toolkit

:: MORE INFORMATION

Citation

PLoS One. 2012;7(2):e30619. doi: 10.1371/journal.pone.0030619. Epub 2012 Feb 1.
NGS QC Toolkit: a toolkit for quality control of next generation sequencing data.
Patel RK1, Jain M.

SESAME 1.0 – Analyze Amplicon Sequences obtained through NGS Technologies

SESAME 1.0

:: DESCRIPTION

SESAME (SEquence Seeker and AMplicon Explorer)is a user friendly web application package for analyzing amplicon sequences obtained through NGS technologies. It was tested extensively with Mozilla Firefox 3.5 and Chrome web browsers. It is designed to provide individual amplicon alignments so the user(s) can easily validate alleles and distinguish them from sequencing errors and artifacts. It includes automatic sequence assignation to multiple loci and samples via oligonucleotides tags. An assistant guides the user for input data upload and through the automatic sequence analysis steps. It provides an intuitive point-and-click interface to validate sequences as alleles from amplicon sequences alignments. All data are stored in a relational database, that user can query or filter through an intuitive interface. The results are exported as genotypes or sequences of genetic variants.

::DEVELOPER

 the Next Generation Sequencing @ CBGP.

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 SESAME

:: MORE INFORMATION

Citation

Meglécz E., Piry S., Desmarais E., Galan M., Gilles A., Guivier E., Pech N. and Martin J.-F. (2010).
SESAME (SEquence Seeker & AMplicon Explorer): Genotyping based on high-throughput multiplex amplicon sequencing.
Bioinformatics. 2011 Jan 15;27(2):277-8

BM-Map 2.0.1 – Refining Next-Generation Sequencing (NGS) Read Mapping

BM-Map 2.0.1

:: DESCRIPTION

BM-Map is a powerful NGS genomic loci mapping refiner. It improves the mapping of the multireads (reads mapped to more than one genomic location with similar fidelities), as a refinement step after the general read-alignment is completed.

::DEVELOPER

Yuan Ji Lab  and Dr. Han Liang’s group.

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX

:: DOWNLOAD

 BM-Map

:: MORE INFORMATION

Citation

BMC Genomics. 2012;13 Suppl 8:S9. doi: 10.1186/1471-2164-13-S8-S9. Epub 2012 Dec 17.
BM-Map: an efficient software package for accurately allocating multireads of RNA-sequencing data.
Yuan Y1, Norris C, Xu Y, Tsui KW, Ji Y, Liang H.

Biometrics. 2011 Dec;67(4):1215-24. doi: 10.1111/j.1541-0420.2011.01605.x. Epub 2011 Apr 22.
BM-map: Bayesian mapping of multireads for next-generation sequencing data.
Ji Y, Xu Y, Zhang Q, Tsui KW, Yuan Y, Norris C Jr, Liang S, Liang H.

NGS++ 1.2.1 – C++ library for Manipulating Next Generation Sequencing data

NGS++ 1.2.1

:: DESCRIPTION

NGS++ is a programming library in C++11 specialized in manipulating both next-generation sequencing (NGS) datasets and genomic information files.

::DEVELOPER

NGS++ team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • C++ Compiler

:: DOWNLOAD

 NGS++

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Aug 1;29(15):1893-4. doi: 10.1093/bioinformatics/btt312. Epub 2013 Jun 4.
NGS++: a library for rapid prototyping of epigenomics software tools.
Nordell Markovits A1, Joly Beauparlant C, Toupin D, Wang S, Droit A, Gevry N.

STATegraEMS v0.9 – Experiment Management System (EMS) designed for Storage and Annotation of NGS experiments.

STATegraEMS v0.9

:: DESCRIPTION

The STATegra EMS is an experiment oriented management system designed for storage and annotation of complex NGS and omics experiments.

::DEVELOPER

The Genomics of Gene Expression Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Apache Tomcat
  • Java

:: DOWNLOAD

 STATegraEMS

:: MORE INFORMATION

Citation

BMC Syst Biol. 2014;8 Suppl 2:S9. doi: 10.1186/1752-0509-8-S2-S9. Epub 2014 Mar 13.
STATegra EMS: an Experiment Management System for complex next-generation omics experiments.
Hernández-de-Diego R, Boix-Chova N, Gómez-Cabrero D, Tegner J, Abugessaisa I, Conesa A.

NGLess 0.6.1 / NG-meta-profiler 0.9.1 – NGS Processing with Less Work

NGLess 0.6.1 / NG-meta-profiler 0.9.1

:: DESCRIPTION

NGLess is a domain-specific language for NGS (next-generation sequencing data) processing.

NG-meta-profiler is a collection of predefined pipelines for processing shotgun metagenomes.

::DEVELOPER

Bork Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

NGLess , NG-meta-profiler

:: MORE INFORMATION

Citation

Microbiome. 2019 Jun 3;7(1):84. doi: 10.1186/s40168-019-0684-8.
NG-meta-profiler: fast processing of metagenomes using NGLess, a domain-specific language.
Coelho LP, Alves R, Monteiro P, Huerta-Cepas J, Freitas AT, Bork P

InteMAP 1.0 – Integrated Metagenomic Assembly pipeline for NGS Short Reads

InteMAP 1.0

:: DESCRIPTION

InteMAP is a pipeline which integrates individual assemblers for assembling metagenomic short sequencing reads.

::DEVELOPER

ZhuLab, Peking Uiniversity, Beijing

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

  InteMAP

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2015 Aug 7;16:244. doi: 10.1186/s12859-015-0686-x.
InteMAP: Integrated metagenomic assembly pipeline for NGS short reads.
Lai B, Wang F, Wang X, Duan L, Zhu H

SNPGenie – Estimating Evolutionary parameters to Detect Natural Selection using pooled NGS data

SNPGenie

:: DESCRIPTION

SNPGenie is a program to estimate evolutionary parameters from pooled next-generation sequencing (NGS) data.

::DEVELOPER

Chase W. Nelson

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Perl

:: DOWNLOAD

 SNPGenie

:: MORE INFORMATION

Citation

SNPGenie: estimating evolutionary parameters to detect natural selection using pooled next-generation sequencing data.
Nelson CW, Moncla LH, Hughes AL.
Bioinformatics. 2015 Jul 29. pii: btv449.