Tag: HTS

HTSCluster 2.0.8 – Clustering High Throughput Sequencing (HTS) data

HTSCluster 2.0.8

:: DESCRIPTION

HTSCluster implements a Poisson mixture model to cluster observations (e.g., genes) in high throughput sequencing data. Parameter estimation is performed using either the EM or CEM algorithm, and the slope heuristics are used for model selection (i.e., to choose the number of clusters).

::DEVELOPER

Andrea Rau <andrea.rau at jouy.inra.fr>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R

:: DOWNLOAD

 HTSCluster

:: MORE INFORMATION

Citation:

Co-expression analysis of high-throughput transcriptome sequencing data with Poisson mixture models.
Rau A, Maugis-Rabusseau C, Martin-Magniette ML, Celeux G.
Bioinformatics. 2015 Jan 5. pii: btu845.

HTSeq 0.13.5 – Process and Analyze data from High-throughput Sequencing (HTS) Assays

HTSeq 0.13.5

:: DESCRIPTION

HTSeq is a Python package that provides infrastructure to process data from high-throughput sequencing assays.

::DEVELOPER

Huber Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 HTSeq

:: MORE INFORMATION

Citation

HTSeq–a Python framework to work with high-throughput sequencing data.
Anders S, Pyl PT, Huber W.
Bioinformatics. 2015 Jan 15;31(2):166-9. doi: 10.1093/bioinformatics/btu638.

QuantumClone 1.0.0.6 – Clustering Mutations using High Throughput Sequencing (HTS) Data

QuantumClone 1.0.0.6

:: DESCRIPTION

QuantumClone is a clonal reconstruction method for whole genome or whole exome sequencing data.

::DEVELOPER

Boeva lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX/ Windows
  • R

:: DOWNLOAD

QuantumClone 

:: MORE INFORMATION

Citation

Deveau P, et al.
QuantumClone: clonal assessment of functional mutations in cancer based on a genotype-aware method for clonal reconstruction.
Bioinformatics. 2018 Jun 1;34(11):1808-1816. doi: 10.1093/bioinformatics/bty016. PMID: 29342233; PMCID: PMC5972665.

NGV 0.1 – Browser for Efficient Display of Large HTS Data Sets

NGV 0.1

:: DESCRIPTION

NGV (Next Generation Viewer) is a Preprocessor and Browser for efficient display of large HTS Data Sets. In a preprocessing step, NGV takes a genomic sequence and a file containing mapped reads as input and creates several indices. This preprocessing step is easily extendable by a plug-in mechanism. Preprocessed data sets can then be loaded and visualized efficiently: NGV provides several information visualizations (coverage histogram, coverage overviews, detail view). It makes use of interval tree-based indices to efficiently visualize large HTS data sets and enable users to search for regions with a defined minimum coverage as well as for mismatches between consensus and reference sequence.

::DEVELOPER

 the Center of Integrative Bioinformatics Vienna (CIBIV) headed by Arndt von Haeseler.

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

  NGV

:: MORE INFORMATION