DiNAMO 1.0 – Discriminative DNA IUPAC motif discovery tool

DiNAMO 1.0

:: DESCRIPTION

The DiNAMO software implements an exhaustive algorithm to detect over-represented IUPAC motifs in a set of DNA sequences. It has two modes: scanning mode, where all windows are parsed, or fixed-position mode, where only motifs occurring at a specific position in the sequences are taken into account.

::DEVELOPER

Bonsai Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX

:: DOWNLOAD

DiNAMO

:: MORE INFORMATION

Citation:

Saad C, Noé L, Richard H, Leclerc J, Buisine MP, Touzet H, Figeac M.
DiNAMO: highly sensitive DNA motif discovery in high-throughput sequencing data.
BMC Bioinformatics. 2018 Jun 11;19(1):223. doi: 10.1186/s12859-018-2215-1. PMID: 29890948; PMCID: PMC5996464.

COMET – Cluster Of Motifs E-value Tool

COMET

:: DESCRIPTION

COMET (Cluster Of Motifs E-value Tool) finds statistically significant clusters of motifs in a DNA sequence. The motifs are represented using 4 x L matrices, which record the frequencies of the nucleotides A, C, G, and T at each position in the motif.

::DEVELOPER

Zlab

:: SCREENSHOTS

Command Line

Web version:

:: REQUIREMENTS

  • Linux / SUN Solaris 8 / SGI/IRIX/ Mac OS X / Alpha (Compaq Tru64 UNIX V5.0A)

:: DOWNLOAD

COMET

:: MORE INFORMATION

Citation:

Frith MC, Spouge JL, Hansen U, Weng Z
Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences.
Nucleic Acids Res 2002 Jul 15;30(14):3214-24

 

MEDEA – Motif Enrichment of Differential Elements of Accessibility

MEDEA

:: DESCRIPTION

MEDEA identifies lineage-specifying transcription factors (TFs) from chromatin accessibility assays.

::DEVELOPER

The Bulyk Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

MEDEA

:: MORE INFORMATION

Citation

Mariani L, Weinand K, Gisselbrecht SS, Bulyk ML.
MEDEA: analysis of transcription factor binding motifs in accessible chromatin.
Genome Res. 2020 May;30(5):736-748. doi: 10.1101/gr.260877.120. Epub 2020 May 18. PMID: 32424069; PMCID: PMC7263192.

AhoPro – Seach for Overrepresentation of Given motifs in DNA sequences, P-value calculation

AhoPro

:: DESCRIPTION

The project AhoPro was created to seach for overrepresentation of given motifs in DNA sequences and to search for motif cooccurrence. This could discover the synergy of transcription factors (TF), which usually takes place in regulatory modules of genes.

::DEVELOPER

Boeva lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • WIndows

:: DOWNLOAD

 AhoPro

:: MORE INFORMATION

Citation:

Algorithms Mol Biol. 2007 Oct 10;2:13.
Exact p-value calculation for heterotypic clusters of regulatory motifs and its application in computational annotation of cis-regulatory modules.
Boeva V, Clément J, Régnier M, Roytberg MA, Makeev VJ.

CAGEd-oPOSSUM 1.0 – Motif Enrichment analysis from CAGE-derived TSSs

CAGEd-oPOSSUM 1.0

:: DESCRIPTION

CAGEd-oPOSSUM is a web-based tool used to detect the over-representation of transcription factor binding sites (TFBS) in regions containing transcription start sites (TSS) derived from Cap Analysis of Gene Expression (CAGE) peaks. It applies the methods of over-representation analysis from our oPOSSUM tool to CAGE derived TSSs.

::DEVELOPER

Wasserman Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

CAGEd-oPOSSUM

:: MORE INFORMATION

Citation:

Arenillas DJ, Forrest AR, Kawaji H, Lassmann T; FANTOM Consortium, Wasserman WW, Mathelier A.
CAGEd-oPOSSUM: motif enrichment analysis from CAGE-derived TSSs.
Bioinformatics. 2016 Sep 15;32(18):2858-60. doi: 10.1093/bioinformatics/btw337. Epub 2016 Jun 9. PMID: 27334471; PMCID: PMC5018375.

ACME v1 – Efficient Parallel Motif Extraction from Very Long Sequences

ACME v1

:: DESCRIPTION

ACME (Advanced parallel motif extractor) is an advanced parallel motif extractor. ACME arranges the search space in contiguous blocks that take advantage of the cache hierarchy in modern architectures, and achieves almost an order of magnitude performance gain in serial execution.

::DEVELOPER

InfoCloud Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / MacOsX / Linux
  • C++ Compiler

:: DOWNLOAD

 ACME

:: MORE INFORMATION

Citation:

Majed Sahli, Essam Mansour, Panos Kalnis:
ACME: Efficient Parallel Motif Extraction from Very Long Sequences.
Technical Report

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).

Haystack 0.5.5 – Epigenetic Variability and Transcription Factor Motifs Analysis Pipeline

Haystack 0.5.5

:: DESCRIPTION

Haystack is a suite of computational tools implemented in a Python 2.7 package called haystack_bio to study epigenetic variability, cross-cell-type plasticity of chromatin states and transcription factors (TFs) motifs providing mechanistic insights into chromatin structure, cellular identity and gene regulation.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Python

:: DOWNLOAD

Haystack

:: MORE INFORMATION

Citation

Bioinformatics, 34 (11), 1930-1933 2018 Jun 1
Haystack: Systematic Analysis of the Variation of Epigenetic States and Cell-Type Specific Regulatory Elements
Luca Pinello, Rick Farouni, Guo-Cheng Yuan

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.

HMS 0.1 – Hybrid Motif Sampler

HMS 0.1

:: DESCRIPTION

HMS (hybrid motif sampler) implements a novel computational algorithm specifically designed for transcription factor binding sites (TFBS) motif discovery using ChIP-Seq data. HMS combines stochastic sampling with determinstic greedy search to achieve rapid and accurate motif pattern identification. In addition, it can identify non-ignorable inter-position dependency inside TFBS motifs.

::DEVELOPER

Ming Hu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 HMS

:: MORE INFORMATION

Citation

Hu M, Yu J, Taylor JM, Chinnaiyan AM, Qin ZS.
On the detection and refinement of transcription factor binding sites using ChIP-Seq data.
Nucleic Acids Res. 2010 Apr;38(7):2154-67. Epub 2010 Jan 6.