Varclus – Detection of Positive Selection in Genes and Genomes through Variation Clusters

Varclus

:: DESCRIPTION

Varclus is a perl utility to identify clusters of amino acid or nucleotide changes in a sequence that are too tightly spaced to have occurred by chance alone.

::DEVELOPER

Andreas Wagner Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • Perl

:: DOWNLOAD

 Varclus

:: MORE INFORMATION

Citation:

Wagner, A. (2007)
Rapid detection of positive selection in genes and genomes through variation clusters.
Genetics 176: 2451–2463

SEGtool 1.3 – Specifically Expressed Gene Detection

SEGtool 1.3

:: DESCRIPTION

SEGtool is an R package with self-adaptive function and high accuracy for specifically expressed gene (SEG, also known as tissue specific gene) detection.

::DEVELOPER

An-Yuan Guo’s Bioinformatics Laboratory

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux
  • R

:: DOWNLOAD

SEGtool

:: MORE INFORMATION

Citation

Zhang Q, Liu W, Liu C, Lin SY, Guo AY.
SEGtool: a specifically expressed gene detection tool and applications in human tissue and single-cell sequencing data.
Brief Bioinform. 2018 Nov 27;19(6):1325-1336. doi: 10.1093/bib/bbx074. PMID: 28981576.

SvABA 1.1.0 – Structural Variation and Indel Detection by local Assembly

SvABA 1.1.0

:: DESCRIPTION

SvABA is a method for detecting structural variants in sequencing data using genome-wide local assembly.

::DEVELOPER

Jeremiah Wala (jwala@broadinstitute.org) — Rameen Berkoukhim lab — Dana Farber Cancer Institute, Boston, MA.

:: SCREENSHOTS

N/a

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

SvABA

:: MORE INFORMATION

Citation

Wala JA, Bandopadhayay P, Greenwald NF, O’Rourke R, Sharpe T, Stewart C, Schumacher S, Li Y, Weischenfeldt J, Yao X, Nusbaum C, Campbell P, Getz G, Meyerson M, Zhang CZ, Imielinski M, Beroukhim R.
SvABA: genome-wide detection of structural variants and indels by local assembly.
Genome Res. 2018 Apr;28(4):581-591. doi: 10.1101/gr.221028.117. Epub 2018 Mar 13. PMID: 29535149; PMCID: PMC5880247.

MSPocket 1.1 – Detection and Graphical Analysis of Protein Surface Pockets

MSPocket 1.1

:: DESCRIPTION

MSPocket is an orientation independent program for the detection and graphical analysis of protein surface pockets.

::DEVELOPER

Zhu, Hongbo.

:: SCREENSHOTS

MSPocket

:: REQUIREMENTS

  • Linux / Windows /Mac OsX
  • Python
  • Biopython
  • MSMS
  • PyMOL

:: DOWNLOAD

 MSPocket

:: MORE INFORMATION

Citation

Zhu H, Pisabarro MT.
MSPocket: an orientation-independent algorithm for the detection of ligand binding pockets.
Bioinformatics. 2011 Feb 1;27(3):351-8.

ORCAtk 1.0.0 – Transcription Factor Binding Site Detection using Phylogenetic Footprinting

ORCAtk 1.0.0

:: DESCRIPTION

The ORCA Toolkit is a system for finding putative regulatory regions and transcription factor binding sites (TFBSs) within those regions.

::DEVELOPER

The Wasserman Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/MacOsX/Linux
  • Perl

:: DOWNLOAD

 ORCAtk

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2009 Jan;37(Database issue):D54-60. doi: 10.1093/nar/gkn783. Epub 2008 Oct 29.
The PAZAR database of gene regulatory information coupled to the ORCA toolkit for the study of regulatory sequences.
Portales-Casamar E, Arenillas D, Lim J, Swanson MI, Jiang S, McCallum A, Kirov S, Wasserman WW.

ClineHelpR v1.1 – Genomic Cline Outlier Detection and Visualization

ClineHelpR v1.1

:: DESCRIPTION

ClineHelpR is an R-package for visualizing genomic clines and detecting outlier loci using output generated by two popular software packages, bgc and Introgress

::DEVELOPER

Bradley Martin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOsX
  • R

:: DOWNLOAD

ClineHelpR

:: MORE INFORMATION

Citation

Martin BT, Chafin TK, Douglas MR, Douglas ME.
ClineHelpR: an R package for genomic cline outlier detection and visualization.
BMC Bioinformatics. 2021 Oct 16;22(1):501. doi: 10.1186/s12859-021-04423-x. PMID: 34656096; PMCID: PMC8520269.

HiNT v2.2.7 – Hi-C for Copy Number Variation and Translocation Detection

HiNT v2.2.7

:: DESCRIPTION

HiNT is a computational method to detect CNVs and Translocations from Hi-C data.

::DEVELOPER

Peter Park’s lab at CBMI, Harvard Medical School

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • Perl
  • R package
  • Python

:: DOWNLOAD

HiNT

:: MORE INFORMATION

Citation

Wang S, Lee S, Chu C, Jain D, Kerpedjiev P, Nelson GM, Walsh JM, Alver BH, Park PJ.
HiNT: a computational method for detecting copy number variations and translocations from Hi-C data.
Genome Biol. 2020 Mar 23;21(1):73. doi: 10.1186/s13059-020-01986-5. PMID: 32293513; PMCID: PMC7087379.

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.

REPET 3.0 / PASTEClassifier 2.0 – Detection, Annotation and Analysis of Repeats in Genomic Sequences

REPET 3.0 / PASTEClassifier 2.0

:: DESCRIPTION

REPET is a software of detection, annotation and analysis of repeats in genomic sequences, specifically designed for transposable elements

PASTEClassifier  classifies TEs by searching for structural features and similarities.

::DEVELOPER

URGI

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 REPET , PASTEC

:: MORE INFORMATION

Citation

PASTEC: An Automatic Transposable Element Classification Tool.
Hoede C, Arnoux S, Moisset M, Chaumier T, Inizan O, Jamilloux V, Quesneville H.
PLoS One. 2014 May 2;9(5):e91929. doi: 10.1371/journal.pone.0091929.

Flutre T, Duprat E, Feuillet C, Quesneville H.
Considering transposable element diversification in de novo annotation approaches.
PLoS One. 2011 Jan 31;6(1):e16526.

dipSFP 1.0 – SFP Detection based on Dip Statistic

dipSFP 1.0

:: DESCRIPTION

dipSFP: Given a matrix of microarray data, SFPs (Single feature polymorphisms) are detected based on the dip statistic.

::DEVELOPER

Cui Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ WIndows/ MacOsX
  • R

:: DOWNLOAD

 dipSFP

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Aug 15;26(16):1983-9. doi: 10.1093/bioinformatics/btq316. Epub 2010 Jun 23.
Single feature polymorphism detection using recombinant inbred line microarray expression data.
Cui X1, You N, Girke T, Michelmore R, Van Deynze A.