msCentipede 1.0 – Hierarchical Multiscale model for inferring Transcription Factor Binding from Chromatin Accessibility data

msCentipede 1.0

:: DESCRIPTION

msCentipede is an algorithm for accurately inferring transcription factor binding sites using chromatin accessibility data (Dnase-seq, ATAC-seq)

::DEVELOPER

Anil Raj

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOS
  • Python

:: DOWNLOAD

 msCentipede

:: MORE INFORMATION

Citation

msCentipede: Modeling Heterogeneity across Genomic Sites and Replicates Improves Accuracy in the Inference of Transcription Factor Binding.
Raj A, Shim H, Gilad Y, Pritchard JK, Stephens M.
PLoS One. 2015 Sep 25;10(9):e0138030. doi: 10.1371/journal.pone.0138030.

PhylochipAnalyzer 1.0 – Analyse Hierarchical Probe sets

PhylochipAnalyzer 1.0

:: DESCRIPTION

PhylochipAnalyzer is a Windows-program for the analysis of experiments with hierarchical probe-sets. It operates in two modes: first, the hierarchy of probes is defined interactively, second, the intensity data of a hybridized chip is loaded and analyzed according to the hierarchy. The program can export hierarchy trees to Newick-format and analyzed data to Excel. It contains a Delphi-script that makes it configurable with respect to different criteria for positive signals.

::DEVELOPER

Bioinformatics at AWI

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

PhylochipAnalyzer

:: MORE INFORMATION

Citation:

Metfies K, Borsutzki P, Gescher C, Medlin LK, Frickenhaus S
Phylochipanalyser — a program for analysing hierarchical probe sets
Molecular Ecology Resources (2008) 8, 99–102
doi:10.1111/j.1471-8286.2007.01927.x

HAC 1.2.1 – Hierarchical Agglomerative Clustering for a large-scale Network data

HAC 1.2.1

:: DESCRIPTION

HAC is developed for fast clustering of heterogeneous interaction networks.

::DEVELOPER

Joel Bader lab

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux

:: DOWNLOAD

 HAC

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2011 Feb 15;12 Suppl 1:S44. doi: 10.1186/1471-2105-12-S1-S44.
Resolving the structure of interactomes with hierarchical agglomerative clustering.
Park Y, Bader JS.

RVD 27 – Hierarchical Bayesian model to detect Rare Single Nucleotide Variants

RVD 27

:: DESCRIPTION

RVD2 is an ultra-sensitive variant detection model for low-depth targeted next-generation sequencing data

::DEVELOPER

Flaherty Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux
  • Python

:: DOWNLOAD

 RVD2

:: MORE INFORMATION

Citation

RVD2: An ultra-sensitive variant detection model for low-depth heterogeneous next-generation sequencing data.
He Y, Zhang F, Flaherty P.
Bioinformatics. 2015 Apr 29. pii: btv275.

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