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http://chipexo.sourceforge.net/

A bioinformatics tool dedicated to analyze ChIP-exo data: 1) Sequencing depth normalization and nucleotide composition bias correction. 2) Signal consolidation and noise reduction. 3) Single base resolution border detection. 4) Border matching.

Proper citation: MACE (RRID:SCR_005520) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/p/treq/home/Home/

A software read mapper for high-throughput DNA sequencing reads, in particular one to several hundred nucleotides in length, and for large edit distance between sequencing read and match in the reference genome. It can cope particularly well with indels for single-best hit recall of 200nt reads simulated from the human reference genome. TreQ performs best at a running time comparable to BWA at large edit distance settings.

Proper citation: TreQ (RRID:SCR_005505) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/netclassr/

An R package for network-based feature (gene) selection for biomarkers discovery via integrating biological information. The package adapts the following 5 algorithms for classifying and predicting gene expression data using prior knowledge: # average gene expression of pathway (aep); # pathway activities classification (PAC); # Hub network classification (hubc); # filter via top ranked genes (FrSVM); # network smoothed t-statistic (stSVM).

Proper citation: netClass (RRID:SCR_005672) Copy   

•   Source: SciCrunch Registry

http://geneontology.svn.sourceforge.net/viewvc/geneontology/go-moose/

go-moose is intended as a replacement for the aging go-perl and go-db-perl Perl libraries. It is written using the object oriented Moose libraries. It can be used for performing a number of analyses on GO data, including the remapping of GO annotations to a selected subset of GO terms. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: go-moose (RRID:SCR_005666) Copy   

•   Source: SciCrunch Registry

http://tmaj.pathology.jhmi.edu/

Open-source software to support information and images related to tissue micro-arrays. It contains support for multiple organ systems, multiple users, image analysis, and is designed to be compliant with HIPPA regulations. Patients, specimens, blocks, slides, cores, images, and scores can all be stored and viewed. Features include advanced security, custom dynamic fields, and an image analysis program.

Proper citation: TMAJ (RRID:SCR_005601) Copy   

•   Source: SciCrunch Registry

http://maq.sourceforge.net/maqview.shtml

A graphical read alignment viewer specifically designed for the Maq alignment file and allows you to see the mismatches, base qualities and mapping qualities. It is highly efficient in speed, memory and disk usage. Maqview is based on OpenGL and is known to work on both Mac OS X and Linux. Porting to Windows is in principle easy.

Proper citation: Maqview (RRID:SCR_005632) Copy   

•   Source: SciCrunch Registry

http://staden.sourceforge.net/

A fully developed set of DNA sequence assembly (Gap4 and Gap5), editing and analysis tools (Spin) for Unix, Linux, MacOSX and MS Windows.

Proper citation: Staden Package (RRID:SCR_005629) Copy   

•   Source: SciCrunch Registry

http://snp-magma.sourceforge.net

Software that utilizes a multiobjective evolutionary algorithm for genetic mapping. It is based on a the ECJ evolutionary software package written by Sean Luke and includes the Strength Pareto Evoluationary Algorithm Version 2 changes for multiobjective analysis. The code runs on any platform with Java Version 2. A genetic mapping project, typically implemented during a search for genes responsible for a disease, requires the acquisition of a set of data from each of a large number of individuals. This data set includes the values of multiple genetic markers. These genetic markers occur at discrete positions along the genome, which is a collection of one or more linear chromosomes. Typing the value of a marker in an individual carries a cost; one seeks to minimize the number of markers typed without excessively jeopardizing the probability of detecting an association between a marker and a disease phenotype. MAGMA is a project which employ''s a multiobjective evolutionary algorithm to solve this problem.

Proper citation: MAGMA (RRID:SCR_005757) Copy   

•   Source: SciCrunch Registry

http://brainnetworks.sourceforge.net

Brain Networks: Code to perform network analysis on brain imaging data.

Proper citation: Brain Networks (RRID:SCR_005841) Copy   

•   Source: SciCrunch Registry

http://estscan.sourceforge.net/

ESTScan is a program that can detect coding regions in DNA sequences, even if they are of low quality. ESTScan will also detect and correct sequencing errors that lead to frameshifts. ESTScan is not a gene prediction program , nor is it an open reading frame detector. In fact, its strength lies in the fact that it does not require an open reading frame to detect a coding region. As a result, the program may miss a few translated amino acids at either the N or the C terminus, but will detect coding regions with high selectivity and sensitivity. ESTScan takes advantages of the bias in hexanucleotide usage found in coding regions relative to non-coding regions. This bias is formalized as an inhomogeneous 3-periodic fifth-order Hidden Markov Model (HMM). Additionally, the HMM of ESTScan has been extended to allows insertions and deletions when these improve the coding region statistics.

Proper citation: ESTScan (RRID:SCR_005742) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/bless-ec/

Software tool for Bloom-filter-based error correction for next-generation sequencing (NGS) reads. The algorithm produces accurate correction results with much less memory.

Proper citation: BLESS (RRID:SCR_005963) Copy   

•   Source: SciCrunch Registry

https://compbio.dfci.harvard.edu/predictivenetworks//

A flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ''known'' interactions together with gene expression data to infer robust gene networks. The regression-based network inference algorithm creates a graph of gene interactions in which cycles may be present (but no self-loops). Based on information-theoretic techniques, a causal gene interaction network is inferred from both prior knowledge (interactions extracted from biomedical literature and structured biological databases) and gene expression data. A prediction model is fitted for each gene, given its parents, enabling assessment of the predictive ability of the network model.

Proper citation: Predictive Networks (RRID:SCR_006110) Copy   

•   Source: SciCrunch Registry

https://github.com/gbook/nidb

Neuroimaging database designed to allow simple importing, searching, and sharing of imaging data. NIDB also provides automated pipelining with importing of results back into NIDB which can be searched along with imaging meta data.

Proper citation: NIDB - Neuroinformatics Database (RRID:SCR_002488) Copy   

•   Source: SciCrunch Registry

http://scralyze.sourceforge.net

A powerful software for model-based analysis of peripheral psychophysiology (e.g. skin conductance, heart rate, pupil size etc.). General linear modelling and dynamic causal modelling of these signals provide for inference on neural states/processes. SCRalyze includes flexible data import and display, statistical inference and results display and export. Easy programming of add-ons for new data formats, signal channels, and models.

Proper citation: SCRalyze (RRID:SCR_002542) Copy   

•   Source: SciCrunch Registry

http://andestools.sourceforge.net/

Software library and a suite of applications, written in Perl and R, for deep sequencing statistical analyses.

Proper citation: ANDES (RRID:SCR_002791) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/glprobs/

Software implementing a simple and effective approach to improve the accuracy of multiple sequence alignment.

Proper citation: GLProbs (RRID:SCR_002739) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/bio-rainbow/

Software developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq.

Proper citation: Rainbow (RRID:SCR_002724) Copy   

•   Source: SciCrunch Registry

http://rdock.sourceforge.net/

A fast and versatile Open Source docking software program that can be used to dock small molecules against proteins and nucleic acids.

Proper citation: rDock (RRID:SCR_002838) Copy   

•   Source: SciCrunch Registry

http://seqpig.sourceforge.net/

A software library for Apache Pig for the distributed analysis of large sequencing datasets on Hadoop clusters.

Proper citation: SeqPig (RRID:SCR_008548) Copy   

•   Source: SciCrunch Registry

http://geckoe.sourceforge.net/

A complete, high-capacity centralized gene expression analysis system, developed in response to the needs of a distributed user community.

Proper citation: Gecko (RRID:SCR_009001) Copy   

•   Source: SciCrunch Registry