VOGUE 20090520 – Variable Order HMM with Duration

VOGUE 20090520

:: DESCRIPTION

VOGUE is a variable order and gapped HMM with with duration. It uses sequence mining to extract frequent patterns in the data. It then uses these patterns to build a variable order HMM with explicit duration on the gap states, for sequence modeling and classification. VOGUE was applied to model protein sequences, as well as a number of other sequence datasets including weblogs.

::DEVELOPER

Mohammed J. Zaki

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

 VOGUE

:: MORE INFORMATION

Citation

Mohammed J. Zaki, Christopher D. Carothers and Boleslaw K. Szymanski,
VOGUE: A Variable Order Hidden Markov Model with Duration based on Frequent Sequence Mining.
ACM Transactions on Knowledge Discovery in Data, 4(1):Article 5. Jan 2010

N-score – Predict Nucleosome Positions from DNA Sequence information

N-score

:: DESCRIPTION

N-score is a wavelet analysis based model for predicting nucleosome positions from DNA sequence information.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Python/Matlab

:: DOWNLOAD

 N-score

:: MORE INFORMATION

Citation

Genomic sequence is highly predictive of local nucleosome depletion.
Yuan GC, Liu JS.
PLoS Comput Biol. 2008 Jan;4(1):e13

MIM – Motif Independent Metric

MIM

:: DESCRIPTION

MIM calculates a measure of sequence specificity called Motif Independent Metric.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Python

:: DOWNLOAD

 MIM 

:: MORE INFORMATION

Citation

A motif-independent metric for DNA sequence specificity.
Pinello L, Lo Bosco G, Hanlon B, Yuan GC.
BMC Bioinformatics. 2011 Oct 21;12:408.

SVGenes 0.4.1 -SVG Format Genome Browser Style Pictures

SVGenes 0.4.1

:: DESCRIPTION

SVGenes (bio-svgenes) is a Ruby-language library that uses SVG primitives to render typical genomic glyphs through a simple and flexible Ruby interface.

::DEVELOPER

Team MacLean – Bioinformatics @ The Sainsbury Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Mac OsX / Windows
  • Ruby
  • BioRuby

:: DOWNLOAD

 SVGenes

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Aug 1;29(15):1890-2. doi: 10.1093/bioinformatics/btt294. Epub 2013 Jun 6.
SVGenes: a library for rendering genomic features in scalable vector graphic format.
Etherington GJ1, MacLean D.

Biscap and cfdr 0.11 – Scripts for post-alignment Snp-calling and Verification

Biscap and cfdr 0.11

:: DESCRIPTION

Biscap and cfdr is a script for determining homozygous and heterozygous positions from an alignment using binomial probabilities from a predicted error rate (BiSCaP) and a method to benchmark the accuracy of this and other alignment/SNP-calling methods (cFDR)

::DEVELOPER

Biscap and cfdr team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • Perl

:: DOWNLOAD

 Biscap and cfdr

:: MORE INFORMATION

Citation

Sci Rep. 2013;3:1512. doi: 10.1038/srep01512.
Using false discovery rates to benchmark SNP-callers in next-generation sequencing projects.
Farrer RA1, Henk DA, MacLean D, Studholme DJ, Fisher MC.

MosLocator – Identification of Mos1 Insertions in the C.elegans Genome

MosLocator

:: DESCRIPTION

MosLocator is a tool for researchers who wish to look for insertions in or near one or many genes. It sends queries to a local database; depending on the number of queries and connection speeds, it may take a few seconds or even a couple of minutes for the answer to come back.

::DEVELOPER

the Ewbank lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

PLoS One. 2012;7(2):e30482. doi: 10.1371/journal.pone.0030482. Epub 2012 Feb 8.
A genome-wide collection of Mos1 transposon insertion mutants for the C. elegans research community.
Vallin E1, Gallagher J, Granger L, Martin E, Belougne J, Maurizio J, Duverger Y, Scaglione S, Borrel C, Cortier E, Abouzid K, Carre-Pierrat M, Gieseler K, Ségalat L, Kuwabara PE, Ewbank JJ.

SV-Bay – Detection of Structural Variants in Cancer Mate-pair and Paired-end data

SV-Bay

:: DESCRIPTION

SV-Bay is a computational method to detect structural variants from whole genome sequencing mate-pair or paired-end data using a probabilistic Bayesian approach.

::DEVELOPER

Boeva Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • Python

:: DOWNLOAD

 SV-Bay

:: MORE INFORMATION

Citation

SV-Bay: structural variant detection in cancer genomes using a Bayesian approach with correction for GC-content and read map-pability.
Iakovishina D, Janoueix-Lerosey I, Barillot E, Regnier M, Boeva V.
Bioinformatics. 2016 Jan 6. pii: btv751.

HomologMiner 1.00 – Find Homologous Genomic Groups in Whole Genomes

HomologMiner 1.00

:: DESCRIPTION

HomologMiner is a software to identify homologous groups applicable to genome sequences that have been properly marked for low-complexity repeats and annotated interspersed repeats.

::DEVELOPER

Minmei Hou

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler

:: DOWNLOAD

 HomologMiner

:: MORE INFORMATION

Citation

Bioinformatics. 2007 Apr 15;23(8):917-25. Epub 2007 Feb 18.
HomologMiner: looking for homologous genomic groups in whole genomes.
Hou M, Berman P, Hsu CH, Harris RS.

BASELINe 1.3 – Bayesian Estimation of Antigen-Driven Selection in Immunoglobulin Sequences

BASELINe 1.3

:: DESCRIPTION

BASELINe, a new computational framework for Bayesian estimation of Antigen-driven selection in Immunoglobulin sequences, provides a more intuitive means of analyzing selection by actually quantifying it.

::DEVELOPER

Kleinstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R

:: DOWNLOAD

 BASELINe

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2012 Sep 1;40(17):e134. Epub 2012 May 27.
Quantifying selection in high-throughput Immunoglobulin sequencing data sets.
Yaari G1, Uduman M, Kleinstein SH.

pRESTO 0.5.13 – Processing raw reads from high-throughput Sequencing of Lymphocyte Repertoires

pRESTO 0.5.13

:: DESCRIPTION

pRESTO (REpertoire Sequencing TOolkit) is an integrated collection of platform-independent Python modules for processing raw reads from high-throughput (next-generation) sequencing of lymphocyte repertoires.

::DEVELOPER

Kleinstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • Python
  • Biopython
  • MUSCLE

:: DOWNLOAD

 pRESTO

:: MORE INFORMATION

Citation

pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires.
Vander Heiden JA, Yaari G, Uduman M, Stern JN, O’Connor KC, Hafler DA, Vigneault F, Kleinstein SH.
Bioinformatics. 2014 Mar 26.