GROK 1.1.1 – Genomic Region Operation Toolkit

GROK 1.1.1

:: DESCRIPTION

GROK is “Swiss Army knife” library for processing genomic interval data. GROK operates on genomic regions, annotated chromosomal intervals that represent sequencing short reads, gene locations, ChIP-seq peaks or other genomic features. Applications of GROK include file format conversions, set operations, overlap queries, and filtering and transformation operations. Supported file formats include BAM/SAM, BED, BedGraph, CSV, FASTQ, GFF/GTF, VCF and Wiggle.

::DEVELOPER

Systems Biology Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX
  • R

:: DOWNLOAD

 GROK

:: MORE INFORMATION

Citation

IEEE/ACM Trans Comput Biol Bioinform. 2013 Jan-Feb;10(1):200-6. doi: 10.1109/TCBB.2012.170.
Genomic region operation kit for flexible processing of deep sequencing data.
Ovaska K1, Lyly L, Sahu B, J?nne OA, Hautaniemi S.

coMET – Visualisation of EWAS Results in Genomic Region

coMET

:: DESCRIPTION

The coMET package is a web-based plotting tool and R-based package to visualize EWAS (epigenome-wide association scan) results in a genomic region of interest.

::DEVELOPER

coMET team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Mac /  Linux
  • R

:: DOWNLOAD

 coMET

:: MORE INFORMATION

Citation:

coMET: visualisation of regional epigenome-wide association scan results and DNA co-methylation patterns.
Martin TC, Yet I, Tsai PC, Bell JT.
BMC Bioinformatics. 2015 Apr 28;16(1):131

hot_scan – Detect Genomic Regions unusually rich in Translocation Breakpoints

hot_scan

:: DESCRIPTION

hot_scan is a free software to detect genomic regions unusually rich (hotspot) in a given pattern via scan statistics

::DEVELOPER

hot_scan team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R package
  • Perl

:: DOWNLOAD

 hot_scan

:: MORE INFORMATION

Citation

Bioinformatics. 2014 May 23. pii: btu351. [Epub ahead of print]
Identification of cromosomal translocation hotspots via scan statistics.
Silva IT1, Rosales RA2, Holanda AJ2, Nussenzweig MC3, Jankovic M3.

MotifScan 1.3.0 – Scan input Genomic Regions with known DNA motifs

MotifScan 1.3.0

:: DESCRIPTION

Given a set of input genomic regions, MotifScan scans the sequences to detect the occurrences of known motifs. It can also applies a statistical test on each motif to check whether the motif is significantly over- or under-represented (enriched or depleted) in the input genomic regions compared to another set of control regions.

::DEVELOPER

ShaoLab at CAS-MPG Partner Institute for Computational Biology, SIBS, CAS.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

 MotifScan

:: MORE INFORMATION

Citation

Sun, H., Wang, J., Gong, Z. et al.
Quantitative integration of epigenomic variation and transcription factor binding using MAmotif toolkit identifies an important role of IRF2 as transcription activator at gene promoters.
Cell Discov 4, 38 (2018).

CREAM 1.1.1 – Clustering of Genomic Regions Analysis Method

CREAM 1.1.1

:: DESCRIPTION

CREAM (Clustering of Genomic Regions Analysis Method) provides a new method for identification of clusters of genomic regions within chromosomes. Primarily, it is used for calling clusters of cis-regulatory elements (COREs). ‘CREAM’ uses genome-wide maps of genomic regions in the tissue or cell type of interest, such as those generated from chromatin-based assays including DNaseI, ATAC or ChIP-Seq. ‘CREAM’ considers proximity of the elements within chromosomes of a given sample to identify COREs in the following steps: 1) It identifies window size or the maximum allowed distance between the elements within each CORE, 2) It identifies number of elements which should be clustered as a CORE, 3) It calls COREs, 4) It filters the COREs with lowest order which does not pass the threshold considered in the approach.

::DEVELOPER

Princess Margaret Bioinformatics and Computational Genomics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R

:: DOWNLOAD

 CREAM

:: MORE INFORMATION

 

ADMIRE v1.1.0 – Analysis of DNA Methylation in Genomic Regions

ADMIRE v1.1.0

:: DESCRIPTION

ADMIRE is a semi-automatic analysis pipeline and visualization tool for Infinium HumanMethylation450K and Infinium MethylationEpic assays.

::DEVELOPER

the Loosolab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

ADMIRE

:: MORE INFORMATION

Citation:

Preussner J, Bayer J, Kuenne C and Looso M.
ADMIRE: analysis and visualization of differential methylation in genomic regions using the Infinium HumanMethylation450 Assay.
Epigenetics Chromatin, 8, 51(2015), doi:10.1186/s13072-015-0045-1

BLAST2GENE – Gene Analysis in Genomic Regions

BLAST2GENE

:: DESCRIPTION

BLAST2GENE is a program that allows a detailed analysis of genomic regions containing completely or partially duplicated genes. From a BLAST (or BL2SEQ) comparison of a protein or nucleotide query sequence with any genomic region of interest, BLAST2GENE processes all high scoring pairwise alignments (HSPs) and provides the disposition of all independent copies along the genomic fragment. The results are provided in text and PostScript formats to allow an automatic and visual evaluation of the respective region.

::DEVELOPER

Bork Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 BLAST2GENE

:: MORE INFORMATION

Citation

BLAST2GENE: a comprehensive conversion of BLAST output into independent genes and gene fragments.
Suyama M, Torrents D, Bork P
Bioinformatics. 2004 Aug 12; 20(12): 1968-70. Epub 2004 Mar 22; PubMed: 15037510.

BiSA 0.96 – Genomic Regions Binding Sites Analysis

BiSA 0.96

:: DESCRIPTION

BiSA (Binding sites analyser) is a database driven software and stores all of its data in a relational database management system (RDBMS) such as SQL Server in Windows or PostgreSQL on Linux.

::DEVELOPER

BiSA team

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/ WIndows
  • SQL Server

:: DOWNLOAD

 BiSA

:: MORE INFORMATION

Citation

Binding sites analyser (BiSA): software for genomic binding sites archiving and overlap analysis.
Khushi M, Liddle C, Clarke CL, Graham JD.
PLoS One. 2014 Feb 12;9(2):e87301. doi: 10.1371/journal.pone.0087301.

COUGER 1.8.2 – Identifying Co-factors Associated with Uniquely-bound Genomic Regions

COUGER 1.8.2

:: DESCRIPTION

COUGER is a framework for identifying co-factors associated with uniquely-bound genomic regions

::DEVELOPER

The Gordan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 COUGER

:: MORE INFORMATION

Citation:

COUGER-co-factors associated with uniquely-bound genomic regions.
Munteanu A, Ohler U, Gordân R.
Nucleic Acids Res. 2014 May 26. pii: gku435

Munteanu, A., & Gordan,R. (2013)
Distinguishing between genomic regions bound by paralogous transcription factors.
Research in Computational Molecular Biology 2013 (RECOMB13). 7821:145.

regioneR 1.0.3 – Association Analysis of Genomic Regions based on Permutation Tests

regioneR 1.0.3

:: DESCRIPTION

regioneR offers a statistical framework based on customizable permutation tests to assess the association between genomic region sets and other genomic features.

::DEVELOPER

Bernat Gel <bgel at imppc.org>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX / WIndows
  • R
  • BioCouductor

:: DOWNLOAD

 regioneR

:: MORE INFORMATION

Citation:

regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests.
Gel B, Díez-Villanueva A, Serra E, Buschbeck M, Peinado MA, Malinverni R.
Bioinformatics. 2015 Sep 30. pii: btv562.