PSE-HMM v1 – Genome-wide CNV detection from Next Generation Sequencing data

PSE-HMM v1

:: DESCRIPTION

PSE-HMM is a tool for the genome-wide CNV detection from Next Generation Sequencing data (mate pair reads). PSE-HMM applies an HMM with Position-Specific Emission probabilities for modeling different aberrations in the mate pairs, after being mapped to the reference genome.

::DEVELOPER

School of Biological Sciences, Iran

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOsX
  • MatLab

:: DOWNLOAD

PSE-HMM

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2016 Nov 3;18(1):30. doi: 10.1186/s12859-016-1296-y.
PSE-HMM: genome-wide CNV detection from NGS data using an HMM with Position-Specific Emission probabilities.
Malekpour SA, Pezeshk H, Sadeghi M

glfMultiples 20100616 – GLF-based Variant Caller for Next-generation Sequencing data

glfMultiples 20100616

:: DESCRIPTION

glfMultiples is a GLF-based variant caller for next-generation sequencing data. It takes a set of GLF format genotype likelihood files as input and generates a VCF-format set of variant calls as output

::DEVELOPER

Abecasis Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler

:: DOWNLOAD

 glfMultiples

:: MORE INFORMATION

AYB 2.11 – Advanced Base Calling for Next Generation Sequencing Machines

AYB 2.11

:: DESCRIPTION

AYB (All your base) is a base caller for the Illumina Genome Analyzer, using an explicit statistical model of how errors occur during sequencing to produce more accurate reads from the raw intensity data.

::DEVELOPER

Goldman Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 AYB

:: MORE INFORMATION

Citation:

Genome Biol. 2012 Feb 29;13(2):R13. [Epub ahead of print]
All your base: a fast and accurate probabilistic approach to base calling.
Massingham T, Goldman N.

CONSERTING – Copy Number Segmentation by Regression Tree in Next Generation Sequencing

CONSERTING

:: DESCRIPTION

CONSERTING (Copy Number Segmentation by Regression Tree in Next Generation Sequencing) is an accurate method for detecting somatic DNA copy number variation in whole genome sequencing data.

::DEVELOPER

Zhang (Jinghui Zhang) Lab,St. Jude Children’s Research Hospital

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • R package

:: DOWNLOAD

 CONSERTING

:: MORE INFORMATION

Olorin 1.0.1 – Interactive Filtering tool for Next Generation Sequencing data

Olorin 1.0.1

:: DESCRIPTION

Olorin is an interactive filtering tool for next generation sequencing data coming from the study of large complex disease pedigrees.

::DEVELOPER

Olorin team

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • Java

:: DOWNLOAD

 Olorin

:: MORE INFORMATION

Citation

Olorin: combining gene flow with exome sequencing in large family studies of complex disease.
Morris JA and Barrett JC
Bioinformatics (Oxford, England) 2012;28;24;3320-1

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

EBVariant 1.0 – An Empirical Bayes Testing Procedure for Variants Detection in Next Generation Sequencing

EBVariant 1.0

:: DESCRIPTION

EBVariant is an optimal empirical Bayes testing procedure to detect variants for NGS study. It exploits the across-site information among vast amount of testing sites in Next Generation Sequencing data, and thus, comparing to conventional Bayesian models or frequestist tests, EBVariant is able to address the multiplicity and testing efficiency issues simultaneously.

:: SCREENSHOTS

N/A

::DEVELOPER

Zhi Wei

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R package/Java

:: DOWNLOAD

 EBVariant

:: MORE INFORMATION

Citation

Zhao Z, Wang W, and Wei Z.
An empirical Bayes testing procedure for detecting variants in analysis of next generation sequencing data.
Annals of Applied Statistics, accepted.

Galaxy LIMS – LIMS for Next-generation Sequencing

Galaxy LIMS

:: DESCRIPTION

Galaxy LIMS is a laboratory information management system (LIMS) for a next-generation sequencing (NGS) laboratory within the existing Galaxy platform. The system provides lab technicians standard and customizable sample information forms, barcoded submission forms, tracking of input sample quality, multiplex-capable automatic flow cell design and automatically generated sample sheets to aid physical flow cell preparation.

::DEVELOPER

The Institute for Translational Oncology and Immunology(TrOn)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 Galaxy LIMS

:: MORE INFORMATION

Citation

Bioinformatics. 2013 May 1;29(9):1233-4. doi: 10.1093/bioinformatics/btt115. Epub 2013 Mar 11.
Galaxy LIMS for next-generation sequencing.
Scholtalbers J, Rößler J, Sorn P, de Graaf J, Boisguérin V, Castle J, Sahin U.

SHOREmap 3.6 – Mutant Mapping with Next Generation Sequencing data

SHOREmap 3.6

:: DESCRIPTION

SHOREmap is an extension of the short read analysis pipeline SHORE. SHOREmap supports genome-wide genotyping and candidate-gene sequencing in a single step through analysis of deep sequencing data from a large pool of recombinants. SHOREmap requires aligned sequence data from a pooled mapping population. Based on the read count at marker positioning distinguishing the parents it regonizes regions with skews in the allele distribution. Annotating the changes within this interval rapidly leads to causal changes.

::DEVELOPER

KS’ Research GroupDW’s Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 SHOREmap 

:: MORE INFORMATION

Citation

Nat Methods. 2009 Aug;6(8):550-1.
SHOREmap: simultaneous mapping and mutation identification by deep sequencing.
Schneeberger K, Ossowski S, Lanz C, Juul T, Petersen AH, Nielsen KL, Jørgensen JE, Weigel D, Andersen SU.

RVD – Rare Single Nucleotide Variant Detection using Next-generation Sequencing

RVD

:: DESCRIPTION

RVD is a standalone algorithm for ultrasensitive rare single nucleotide variant detection using next-generation sequencing. The RVD program takes BAM files of deep sequencing reads in as input. Using a Beta-Binomial model, the algorithm estimates the error rate at each base position in the reference sequence.

::DEVELOPER

Ji Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  MacOsX / Linux
  • MatLab
  • Samtools

:: DOWNLOAD

  RVD

:: MORE INFORMATION

Citation

RVD: a command-line program for ultrasensitive rare single nucleotide variant detection using targeted next-generation DNA resequencing.
Cushing A, Flaherty P, Hopmans E, Bell JM, Ji HP.
BMC Res Notes. 2013 May 23;6:206.