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http://genome-www.stanford.edu/TMA/

Software Tools for High-Throughput Analysis and Archiving of Immunohistochemistry Staining Data Obtained with Tissue Microarrays.

Proper citation: Stanford TMA Software (RRID:SCR_005598) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/downloads/oxbench/

A suite of programs aimed at developers of alignment methods rather than end-users to assess the accuracy of multiple sequence alignment methods. It includes a reference database of protein multiple sequence alignments that were generated by consideration of protein three-dimensional structure.

Proper citation: OXBench (RRID:SCR_005591) 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://www.hca-vision.com/product_spot.html

Software package for analysis of microarray images. Microarray spot detection and characterization software package which extracts numerical information from cDNA microarrays., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SPOT (RRID:SCR_005623) Copy   

•   Source: SciCrunch Registry

http://mesquiteproject.org/packages/chromaseq/

A software package in Mesquite that processes chromatograms, makes contigs, base calls, etc., using in part the programs Phred and Phrap.

Proper citation: Chromaseq (RRID:SCR_005587) Copy   

•   Source: SciCrunch Registry

https://github.com/phe-bioinformatics/snp-search/tree/master/test_data

A software tool that manages SNP data and outputs useful information which can be used to test important biological hypotheses.

Proper citation: snp-search (RRID:SCR_005618) Copy   

•   Source: SciCrunch Registry

http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/pfa/iprscan/

Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.

Proper citation: InterProScan (RRID:SCR_005829) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/webservices/whatizit/info.jsf

A text processing system that allows you to do textmining tasks on text. It is great at identifying molecular biology terms and linking them to publicly available databases. Whatizit is also a Medline abstracts retrieval/search engine. Instead of providing the text by Copy&Paste, you can launch a Medline search. The abstracts that match your search criteria are retrieved and processed by a pipeline of your choice. Whatizit is also available as 1) a webservice and as 2) a streamed servlet. The webservice allows you to enrich content within your website in a similar way as in the wikipedia. The streamed servlet allows you to process large amounts of text.

Proper citation: Whatizit (RRID:SCR_005824) Copy   

•   Source: SciCrunch Registry

http://www.ibridgenetwork.org/wustl/splinter

Software that detects and quantifies short IN/DELs as well as single nucleotide substitutions in pooled-DNA samples.

Proper citation: SPLINTER (RRID:SCR_005826) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/devel/bioc/html/SeqGSEA.html

Software package that provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene''s differential expression and splicing, respectively.

Proper citation: SeqGSEA (RRID:SCR_005724) 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

https://genorm.cmgg.be/

Software to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.

Proper citation: geNORM (RRID:SCR_006763) Copy   

•   Source: SciCrunch Registry

http://watson.nci.nih.gov/bioc_mirror/packages/2.11/bioc/html/EDASeq.html

Software for numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EDASeq (RRID:SCR_006751) Copy   

•   Source: SciCrunch Registry

http://www.genomesunzipped.org/

A group blog providing expert, independent commentary on the personal genomics industry. The goal of the project is to provide genetic testing consumers with independent and informed analysis of developments in the field of genetics and the genetic testing industry. Members of Genomes Unzipped include active researchers in various fields of genetics, as well as specialists in the legal and public health issues surrounding new genomic technologies. Many of us have also been extensively involved in public communication about genetics. Members of the group have had their DNA tested with a variety of products. We have released all of these genetic data openly to the public, both as raw data and in a custom genome browser. As the project proceeds we plan to obtain more genetic tests ����?? up to and including whole genome sequencing ����?? and to continue to release these data to the world. The group is also performing analyses of our own raw genetic data to illustrate fundamental concepts in genetics, using software written both by group members and other collaborators; and we����??ll be releasing the code for that software in our new code repository. As the project expands, we����??ll be looking to add data from other volunteers to the project, as well as to collaborate with other ����??genome hackers����?? on the development of new tools for exploring genetic data.

Proper citation: Genomes Unzipped (RRID:SCR_006870) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/mubiomics/

A set of scripts (mostly python) for processing reads generated by the Roche 454 or Illumina next-gen sequencing platforms. Included are quality control, read demultiplexing and microbiome characterisation scripts for use with usearch, pplacer and RDP classifier.

Proper citation: mubiomics (RRID:SCR_006785) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.11/bioc/html/ShortRead.html

Software package for input, quality assessment and exploration of high-throughput sequence data. Used for input, quality assurance, and basic manipulation of `short read'' DNA sequences such as those produced by Solexa, 454, and related technologies, including exible import of common short read data formats.

Proper citation: ShortRead (RRID:SCR_006813) Copy   

•   Source: SciCrunch Registry

http://compbio.bccrc.ca/software/mutationseq/

A software suite using feature-based classifiers for somatic mutation prediction from paired tumour/normal next-generation sequencing data. mutationSeq has the advantages of integrating different features (e.g., base qualities, mapping qualities, strand bias, and tailed distance features), and validated somatic mutations to make predictions. Given paired normal/tumour bam files, mutationSeq will output the probability of each candidate site being somatic.

Proper citation: mutationSeq (RRID:SCR_006815) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.12/bioc/html/RIPSeeker.html

A statistical software package for identifying protein-associated transcripts from RIP-seq experiments. Infer and discriminate RIP peaks from RIP-seq alignments using two-state HMM with negative binomial emission probability. While RIPSeeker is specifically tailored for RIP-seq data analysis, it also provides a suite of bioinformatics tools integrated within this self-contained software package comprehensively addressing issues ranging from post-alignments processing to visualization and annotation.

Proper citation: RIPSeeker (RRID:SCR_006810) Copy   

•   Source: SciCrunch Registry