FISH Finder 0.27 – A High-Throughput Tool for Analyzing FISH Images

FISH Finder 0.27

:: DESCRIPTION

Fluorescence in situ hybridization (FISH) is used to study the organization and the positioning of specific DNA sequences within the cell nucleus.FISH Finder is a graphical software tool to automatically analyze FISH images that vary significantly.

::DEVELOPER

The Imaging Sciences Lab @ FSU

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows/ MacOsX
MatLab

:: DOWNLOAD

FISH Finder

:: MORE INFORMATION

Citation:

Bioinformatics. 2011 Apr 1;27(7):933-8. doi: 10.1093/bioinformatics/btr053. Epub 2011 Feb 9.
FISH Finder: a high-throughput tool for analyzing FISH images.
Shirley JW1, Ty S, Takebayashi S, Liu X, Gilbert DM.

HiTSelect 20140708 – High-throughput Genome Wide Screen Deconvolution Software

HiTSelect 20140708

:: DESCRIPTION

HiTSelect is a software for the deconvolution and analysis of high-throughput, pooled, genetic screens. It is designed for screens which use next-generation sequencing as readout. HiTSelect provides modules for identifying screen hits via rigorous statistics, visualizing screen readout and performing downstream functional and network analysis.

::DEVELOPER

Jun S. Song’s Research Group

:: SCREENSHOTS

:: REQUIREMENTS

Windows /Linux/ MacOsX

:: DOWNLOAD

HiTSelect

:: MORE INFORMATION

Citation

HiTSelect: a comprehensive tool for high-complexity-pooled screen analysis.
Diaz AA, Qin H, Ramalho-Santos M, Song JS.
Nucleic Acids Res. 2014 Nov 26. pii: gku1197.

CRISP 0.2 – Detection of SNVs and Short Insertion/deletion variants from Pooled high throughput DNA sequencing data

CRISP 0.2

:: DESCRIPTION

CRISP (Comprehensive Read analysis for Identification of Single Nucleotide Polymorphisms from Pooled sequencing) is a software program to detect SNPs and short indels from pooled sequencing data generated using next-generation sequencing instruments. CRISP is designed to detect both rare and common variants by utilizing sequence reads from next-generation sequencing of multiple DNA pools.

::DEVELOPER

Bansal Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

CRISP

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Jun 15;26(12):i318-24. doi: 10.1093/bioinformatics/btq214.
A statistical method for the detection of variants from next-generation resequencing of DNA pools.
Bansal V.

Nozzle 1.1-1 – Generation of Reports in High-throughput data analysis pipelines

Nozzle 1.1-1

:: DESCRIPTION

Nozzle is an R package for generation of reports in high-throughput data analysis pipelines.

::DEVELOPER

Peter Park’s lab at CBMI, Harvard Medical School

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows / MacOsX
R

:: DOWNLOAD

Nozzle

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Apr 15;29(8):1089-91. doi: 10.1093/bioinformatics/btt085. Epub 2013 Feb 17.
Nozzle: a report generation toolkit for data analysis pipelines.
Gehlenborg N1, Noble MS, Getz G, Chin L, Park PJ.

htsint 0.5.2 – High Throughput data Integration tool

htsint 0.5.2

:: DESCRIPTION

htsint (High-Throughput Sequencing INTegrate) is a Python package used to create gene sets for the study of high-throughput sequencing data.

::DEVELOPER

Adam J Richards

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
Python

:: DOWNLOAD

htsint

:: MORE INFORMATION

Citation

htsint: a Python library for sequencing pipelines that combines data through gene set generation.
Richards AJ, Herrel A, Bonneaud C.
BMC Bioinformatics. 2015 Sep 24;16(1):307.

Ontologizer 2.1 – Analysis and Visualization of High-Throughput Biological Data Using Gene Ontology

Ontologizer 2.1

:: DESCRIPTION

Ontologizer is a Java webstart application for GO term enrichment analysis that provides browsing and graph visualization capabilities. The Ontologizer allows users to analyze data with the standard Fisher exact test and also the parent-child method and topology methods.

::DEVELOPER

The Computational Biology @ Charité Berlin

:: SCREENSHOTS

:: REQUIREMENTS

Linux / MacOsX / Windows
Java

:: DOWNLOAD

Ontologizer

:: MORE INFORMATION

Citation

Bioinformatics. 2008 Jul 15;24(14):1650-1. Epub 2008 May 29.
Ontologizer 2.0–a multifunctional tool for GO term enrichment analysis and data exploration.
Bauer S, Grossmann S, Vingron M, Robinson PN.

AMBIENT 1.3 – Find Active Modules in Metabolic Networks using High-throughput data

AMBIENT 1.3

:: DESCRIPTION

AMBIENT (Active Modules for Bipartite Networks) is a Python module that uses simulated annealing to find areas of a metabolic network (modules) that have some consistent characteristic. AMBIENT does not require predefined pathways and gives highly specific predictions of affected areas of metabolism.

:DEVELOPER

The research in the Theoretical Systems Biology Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows/ MacOsX
Python

:: DOWNLOAD

AMBIENT

:: MORE INFORMATION

Citation:

AMBIENT: Active Modules for Bipartite Networks–using high-throughput transcriptomic data to dissect metabolic response.
Bryant WA, Sternberg MJ, Pinney JW.
BMC Syst Biol. 2013 Mar 25;7:26. doi: 10.1186/1752-0509-7-26.

XMRF 1.0 – Fit Markov Networks to High-Throughput Genomics Data

XMRF 1.0

:: DESCRIPTION

XMRF is an R package implemented to enable biomedical researchers to discover complex interaction between genes from multi-dimensional genomics data.

:: DEVELOPER

Liu Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
R

:: DOWNLOAD

XMRF

:: MORE INFORMATION

Citation

Wan YW, Allen GI, Baker Y, Yang E, Ravikumar P, Anderson M, Liu Z.
XMRF: an R package to fit Markov Networks to high-throughput genetics data.
BMC Syst Biol. 2016 Aug 26;10 Suppl 3(Suppl 3):69. doi: 10.1186/s12918-016-0313-0. PMID: 27586041; PMCID: PMC5009817.

MassyTools 1.0.0 – High-Throughput Targeted Data Processing Tool

MassyTools 1.0.0

:: DESCRIPTION

MassyTools is a data processing tool for targeted high-throughput MALDI-MS data extraction.

::DEVELOPER

Bas Jansen

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/Linux
Perl

:: DOWNLOAD

MassyTools

:: MORE INFORMATION

Citation

MassyTools: A High-Throughput Targeted Data Processing Tool for Relative Quantitation and Quality Control Developed for Glycomic and Glycoproteomic MALDI-MS.
Jansen BC, Reiding KR, Bondt A, Hipgrave Ederveen AL, Palmblad M, Falck D, Wuhrer M.
J Proteome Res. 2015 Nov 13.

DNAshape / DNAshapeR 1.0 – High-throughput DNA Shape Prediction

DNAshape / DNAshapeR 1.0

:: DESCRIPTION

DNAshape is a web server for predicting DNA structural features in a high-throughput (HT) manner for massive sequence data.

DNAshapeR predicts DNA shape features in an ultra-fast, high-throughput manner from genomic sequencing data.

::DEVELOPER

the Rohs Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows/Linux
R

:: DOWNLOAD

DNAshapeR

:: MORE INFORMATION

Citation

DNAshapeR: an R/Bioconductor package for DNA shape prediction and feature encoding.
Chiu TP, Comoglio F, Zhou T, Yang L, Paro R, Rohs R.
Bioinformatics. 2015 Dec 14. pii: btv735

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W56-62. doi: 10.1093/nar/gkt437
DNAshape: a method for the high-throughput prediction of DNA structural features on a genomic scale.
Zhou T1, Yang L, Lu Y, Dror I, Dantas Machado AC, Ghane T, Di Felice R, Rohs R.