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http://www.geenivaramu.ee/en/tools/gwama

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software tool for meta analysis of whole genome association data.

Proper citation: GWAMA (RRID:SCR_006624) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/casper.html

Software to infer alternative splicing from paired-end RNA-seq data. The model is based on counting paths across exons, rather than pairwise exon connections, and estimates the fragment size and start distributions non-parametrically, which improves estimation precision.

Proper citation: casper (RRID:SCR_006613) Copy   

•   Source: SciCrunch Registry

http://rulai.cshl.edu/splicetrap/

A statistic tool for quantifying exon inclusion ratios in paired-end RNA-seq data, with broad applications for the study of alternative splicing. SpliceTrap approaches to exon inclusion level estimation as a Bayesian inference problem. For every exon it quantifies the extent to which it is included, skipped or subjected to size variations due to alternative 3?/5? splice sites or Intron Retention. In addition, SpliceTrap can quantify alternative splicing within a single cellular condition, with no need of a background set of reads.

Proper citation: SpliceTrap (RRID:SCR_006728) Copy   

•   Source: SciCrunch Registry

https://github.com/arq5x/bedtools2

A powerful toolset for genome arithmetic allowing one to address common genomics tasks such as finding feature overlaps and computing coverage. Bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.

Proper citation: BEDTools (RRID:SCR_006646) Copy   

•   Source: SciCrunch Registry

http://dictybase.org/

Model organism database for the social amoeba Dictyostelium discoideum that provides the biomedical research community with integrated, high quality data and tools for Dictyostelium discoideum and related species. dictyBase houses the complete genome sequence, ESTs, and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome to provide a ''''reference genome'''' in the Amoebozoa clade. They highlight several new features in the present update: (i) new annotations; (ii) improved interface with web 2.0 functionality; (iii) the initial steps towards a genome portal for the Amoebozoa; (iv) ortholog display; and (v) the complete integration of the Dicty Stock Center with dictyBase. The Dicty Stock Center currently holds over 1500 strains targeting over 930 different genes. There are over 100 different distinct amoebozoan species. In addition, the collection contains nearly 600 plasmids and other materials such as antibodies and cDNA libraries. The strain collection includes: * strain catalog * natural isolates * MNNG chemical mutants * tester strains for parasexual genetics * auxotroph strains * null mutants * GFP-labeled strains for cell biology * plasmid catalog The Dicty Stock Center can accept Dictyostelium strains, plasmids, and other materials relevant for research using Dictyostelium such as antibodies and cDNA or genomic libraries.

Proper citation: Dictyostelium discoideum genome database (RRID:SCR_006643) Copy   

•   Source: SciCrunch Registry

http://rdp.cme.msu.edu

A database which provides ribosome related data services to the scientific community, including online data analysis, rRNA derived phylogenetic trees, and aligned and annotated rRNA sequences. It specifically contains information on quality-controlled, aligned and annotated bacterial and archaean 16S rRNA sequences, fungal 28S rRNA sequences, and a suite of analysis tools for the scientific community. Most of the RDP tools are now available as open source packages for users to incorporate in their local workflow.

Proper citation: Ribosomal Database Project (RRID:SCR_006633) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/ontology-lookup/

Interactive and programmatic interfaces to query, browse and navigate an increasing number of biomedical ontologies and controlled vocabularies. It provides a web service interface to query multiple ontologies from a single location with a unified output format. It can integrate any ontology available in the Open Biomedical Ontology (OBO) format. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A weekly MySQL database export file can be downloaded from the EBI public FTP directory.

Proper citation: Ontology Lookup Service (RRID:SCR_006596) Copy   

•   Source: SciCrunch Registry

http://www.alexaplatform.org/alexa_seq/index.htm

A method for using massively parallel paired-end transcriptome sequencing for ''alternative expression analysis''.

Proper citation: ALEXA-Seq (RRID:SCR_006700) Copy   

•   Source: SciCrunch Registry

http://rice.plantbiology.msu.edu/

Database and resource that provides sequence and annotation data for the rice genome. This website provides genome sequence from the Nipponbare subspecies of rice and annotation of the 12 rice chromosomes. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 75 tracks of annotation. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads. Rice is a model species for the monocotyledonous plants and the cereals which are the greatest source of food for the world''s population. While rice genome sequence is available through multiple sequencing projects, high quality, uniform annotation is required in order for genome sequence data to be fully utilized by researchers. The existence of a common gene set and uniform annotation allows researchers within the rice community to work from a common resource so that their results can be more easily interpreted by other scientists. The objective of this project has always been to provide high quality annotation for the rice genome. They generated, refined and updated gene models for the estimated 40,000-60,000 total rice genes, provided standardized annotation for each model, linked each model to functional annotation including expression data, gene ontologies, and tagged lines. They have provided a resource to extend the annotation of the rice genome to other plant species by providing comparative alignments to other plant species. Analysis/Tools are available including: BLAST, Locus Name Search, Functional Term Search, Protein Domain Search, Anatomy Expression Viewer, Highly Expressed Genes

Proper citation: Rice Genome Annotation (RRID:SCR_006663) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/splicegrapher/

Software that predicts alternative splicing patterns and produces splice graphs that capture in a single structure the ways a gene''s exons may be assembled. It enhances gene models using evidence from next-generation sequencing and EST alignments.

Proper citation: SpliceGrapher (RRID:SCR_006657) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/ChIPXpress.html

A R package designed to improve ChIP-seq and ChIP-chip target gene ranking using publicly available gene expression data. It takes as input predicted transcription factor (TF) bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target.

Proper citation: ChIPXpress (RRID:SCR_006653) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/softsearch/

A sensitive structural variant (SV) detection software tool for Illumina paired-end next-generation sequencing data. It simultaneously utilizes soft-clipping and read-pair strategies for detecting SVs to increase sensitivity. Soft clips are proxies for split-reads that indicate part of the read maps to the reference genome, but the other part is not localized at the same place (e.g. breakpoint spanning reads). Discordant read-pairs refer to a read and its mate, where the insert size is greater (or less than) the expected distribution of the dataset ? or ? where the mapping orientation of the reads is unexpected (e.g. both on the same strand). SoftSearch looks for areas with soft-clipping in the genome that have discordant read pairs supporting the anomaly. Once areas with both these conditions are identified, the read and mate information is extracted directly from the BAM file containing the discordant reads, obviating the need for time-consuming and error-prone complex alignment strategies. Only a small number of soft-masked bases discordant read-pairs are necessary to identify an SV, which on their own would not be sufficient to make an SV call, thus highlighting SoftSearch?s improved sensitivity. SoftSearch is well suited to be ?plugged in? to most sequence analysis workflows, since it requires standard file inputs, such as a BAM file using almost any aligner and a reference genome FASTA file. Because SoftSearch requires soft-masked bases, the only requirement is that the aligner must have this functionality, which is usually turned on by default by many standard aligners (e.g. BWA, Novoalign, etc).

Proper citation: SoftSearch (RRID:SCR_006683) Copy   

•   Source: SciCrunch Registry

http://128.32.118.212/thorfinn/realSFS/

Software program used to estimate allele frequency and SNP calling., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: realSFS (RRID:SCR_002493) Copy   

•   Source: SciCrunch Registry

http://www.unc.edu/~yunmli/shotgun.html

Software for short read simulating in order to facilitate sequencing-based study designs.

Proper citation: ShotGun (RRID:SCR_002529) Copy   

•   Source: SciCrunch Registry

http://ccmbweb.ccv.brown.edu/gibbs/gibbs.html

Software to identify motifs, conserved regions, in DNA or protein sequences.

Proper citation: Gibbs Motif Sampler (RRID:SCR_002550) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/MBASED.html

Software package containing functions for allele-specific gene expression (ASE) analysis using meta-analysis based allele-specific expression detection.

Proper citation: MBASED (RRID:SCR_002584) Copy   

•   Source: SciCrunch Registry

http://pymzml.github.io/

Python module to parse mzML data in Python based on cElementTree. It is an extension to Python that offers (i) an easy access to mass spectrometry (MS) data that allows the rapid development of tools, (ii) a very fast parser for mzML data and (iii) a set of functions to compare or handle spectra., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: pymzML (RRID:SCR_002500) Copy   

•   Source: SciCrunch Registry

http://www.biostars.org/

A question answer forum for scientists, focusing on methods in bioinformatics, computational genomics and biological data analysis. They welcome detailed and specific posts, written clearly and simply.

Proper citation: BioStar (RRID:SCR_002580) Copy   

•   Source: SciCrunch Registry

http://colibread.inria.fr/discosnp/

Software designed for discovering Single Nucleotide Polymorphism (SNP) from raw sets of reads obtained with Next Generation Sequencers (NGS).

Proper citation: discoSnp (RRID:SCR_002612) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/peptide-shaker/

Software providing a search engine independent platform for visualization of peptide and protein identification results from multiple search engines, currently supporting X!Tandem, MS-GF+, MS Amanda, OMSSA, MyriMatch, Comet, Tide, Mascot and mzIdentML. By combining the results from multiple search engines, while re-calculating PTM localization scores and redoing the protein inference, PeptideShaker attempts to give you the best possible understanding of your proteomics data.

Proper citation: PeptideShaker (RRID:SCR_002520) Copy   

•   Source: SciCrunch Registry