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http://cran.r-project.org/web/packages/fcros/

A fold change ranks ordering statistics based software for detecting differentially expressed genes.

Proper citation: FCROS (RRID:SCR_006195) Copy   

•   Source: SciCrunch Registry
  

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

Software package that implements the remove unwanted variation (RUV) methods for the normalization of RNA-Seq read counts between samples.

Proper citation: RUVSeq (RRID:SCR_006263) Copy   

•   Source: SciCrunch Registry
  

http://galaxyproject.org/

Open, web-based platform providing bioinformatics tools and services for data intensive genomic research. Platform may be used as a service or installed locally to perform, reproduce, and share complete analyses. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Community has created Galaxy instances in many different forms and for many different applications including Galaxy servers, cloud services that support Galaxy instances, and virtual machines and containers that can be easily deployed for your own server.The Galaxy team is a part of BX at Penn State, and the Biology and Mathematics and Computer Science departments at Emory University.Training Infrastructure as a Service (TIaaS) is a service offered by some UseGalaxy servers to specifically support training use cases.

Proper citation: Galaxy (RRID:SCR_006281) Copy   

•   Source: SciCrunch Registry
  

http://gensc.org/

An open-membership International community to promote mechanisms that standardize the description of genomes and the exchange and integration of genomic data. Community-driven standards have the best chance of success if developed within the auspices of international working groups. Participants in the GSC include biologists, computer scientists, those building genomic databases and conducting large-scale comparative genomic analyses, and those with experience of building community-based standards. The mission of the GSC is to work with the wider community towards: * the implementation of new genomic standards * methods of capturing and exchanging metadata * harmonization of metadata collection and analysis efforts across the wider genomics community

Proper citation: Genomic Standards Consortium (RRID:SCR_006273) Copy   

•   Source: SciCrunch Registry
  

http://www.megasoftware.net/mega-md/mega-md.php

Software to forecast the deleteriousness of non-synonymous single nucleotide variants (nsSNVs) using multiple methods and explore them in the context of the variability permitted in the long-term evolution of the affected positions. A web version (MEGA-MDW) is also available.

Proper citation: MEGA-MD (RRID:SCR_006403) Copy   

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http://www.uni-koeln.de/med-fak/cgars/

Software package to dissect random from non-random patterns in copy number data and thereby to assess significantly enriched somatic copy number aberrations (SCNA) across a set of tumor specimens or cell lines.

Proper citation: CGARS (RRID:SCR_006404) Copy   

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http://www2.warwick.ac.uk/fac/sci/systemsbiology/staff/ott/tools_and_software/wigwams

A computational tool for analyzing multiple gene expression time series data sets for the same organism. The goal is to determine if there is evidence for gene regulatory mechanisms that are shared by multiple different expression responses.

Proper citation: Wigwams (RRID:SCR_006400) Copy   

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http://www.unc.edu/~yunmli/betaseq/

Software to control Type-I error inflation in partially sequenced data for rare variant association testing. It is typically used to combine sequence and genotype data for the two stage design, in which individuals sequenced in stage one for variant detection are solely or predominantly cases then in stage two the discovered variants are genotyped in the remaining individuals. BETASEQ can work with any existing rare variant association methods that use genotypes or imputed genotypes as input.

Proper citation: BETASEQ (RRID:SCR_006401) Copy   

•   Source: SciCrunch Registry
  

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry
  

http://r3cseq.genereg.net/Site/index.html

An R/Bioconductor package to identify chromosomal interaction regions generated by chromosome conformation capture (3C) coupled to next-generation sequencing (NGS), a technique termed 3C-seq. It performs data analysis for a number of different experimental designs, as it can analyze 3C-seq data with or without a control experiment and it can be used to facilitate data analysis for experiments with multiple replicates. The r3Cseq package provides functions to perform data normalization, statistical analysis for cis/trans interactions and visualization in order to help scientists identify genomic regions that physically interact with the given viewpoints of interest. This tool greatly facilitates hypothesis generation and the interpretation of experimental results.

Proper citation: r3Cseq (RRID:SCR_003198) Copy   

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http://creskolab.uoregon.edu/stacks/

A software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. It was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.

Proper citation: Stacks (RRID:SCR_003184) Copy   

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http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/

Software tool for finding the minimum free energy hybridization of a long and a short RNA. The hybridization is performed in a kind of domain mode, i.e., the short sequence is hybridized to the best fitting part of the long one. The tool is primarily meant as a means for microRNA target prediction.

Proper citation: RNAhybrid (RRID:SCR_003252) Copy   

•   Source: SciCrunch Registry
  

http://cal.tongji.edu.cn/PlantLoc/index.jsp

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4,2023. An accurate web server for predicting plant protein subcellular localization by substantiality motif.

Proper citation: PlantLoc (RRID:SCR_003138) Copy   

•   Source: SciCrunch Registry
  

https://github.com/mozack/abra

Software that is a realigner for next generation sequencing data. It uses localized assembly and global realignment to align reads more accurately, thus improving downstream analysis (detection of indels and complex variants in particular).

Proper citation: Assembly Based ReAligner (RRID:SCR_003277) Copy   

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http://iimcb.genesilico.pl/MetaLocGramN/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.A tool for subcellular localization prediction of Gram-negative proteins. You can also use MetaGramLocN via SOAP. SOAP enables you to invoke our method from scripts written in your programming language of choice.

Proper citation: MetaLocGramN (RRID:SCR_003154) Copy   

•   Source: SciCrunch Registry
  

http://genecruiser.broadinstitute.org/genecruiser3/

A web service and web application for the annotation of microarray data providing integrated access to genomic information freely available from public data sources.

Proper citation: GeneCruiser (RRID:SCR_003153) Copy   

•   Source: SciCrunch Registry
  

http://www.psidev.info/

Initiative to define community standards for data representation in proteomics to facilitate data comparison, exchange and verification. The main organizational unit is the work group, with a Gel Electrophoresis (GEL) work group, a Mass Spectrometry (MS) work group, a Molecular Interactions (MI) work group, a Protein Modifications (MOD) work group, a Proteomics Informatics (PI) work group, and a Sample Processing (SP) work group. The Gel Electrophoresis (GEL) work group aims to develop reporting requirements that supplement the Minimum Information About a Proteomics Experiment (MIAPE) parent document, describing the minimum information that should be reported about gel-based experimental techniques used in proteomics. The group will also develop data formats for capturing MIAPE-compliant data about gel electrophoresis and informatics performed on gel images. The Mass Spectrometry Standards Working Group defines community data formats and controlled vocabulary terms facilitating data exchange and archiving in the field of proteomics mass spectrometry. A past achievement is the mzData standard, which captures mass spectrometry output data. mzData's aim is to unite the large number of current formats (pkl's, dta's, mgf's, .....) into a single format. mzData has been released but is now deprecated in favor of mzML. The Molecular Interactions workgroup is concentrating on improving the annotation and representation of molecular interaction data wherever it is published, be this in journal articles, authors web-sites or public domain databases; and improving the accessibility of molecular interaction data to the user community. By using a common standard data can be downloaded from multiple sources and easily combined using a single parser. The protein modification workgroup focuses on developing a consensus nomenclature and provide an ontology reconciling in a hierarchical representation the complementary descriptions of residue modifications. The protein modification ontology (PSI-MOD) is available in OBO format or in OBO.xml. A spreadsheet containing the mapping of the descriptive labels used in various databases and search engines, the consensus list of proposed short name for protein modifications established by collaborative effort of mass spectrometry community, and the proposed rules and recommendations for this nomenclature are available. These short names are included in the ontology as synonyms of the corresponding terms. The Proteomics Informatics Standards Group (PSI-PI) goals are to provide a set of minimal reporting requirements which augment the MIAPE reporting guidelines with respect to analysis of data derived from proteomics experiments; to provide vendor-neutral and standard formats for representing results of analyzing and processing experimental data; to foster adoption of the format by highlighting efforts made by vendors and individuals that utilize the format in their products. The remit of the Sample Processing Working Group is to produce reporting guidelines, data exchange formats and controlled vocabulary covering all separation techniques not considered to be "classical" one- or two-dimensional gel electrophoresis (cf. the Gel WG home page), along with other kinds of sample handling and processing (for example, "tagging" proteins or peptides, splitting, combining and storing samples). Where possible we seek to develop our products in collaboration with all proteomics stakeholders and, where relevant, developers from other standards communities, most notably metabolomics. * Minimum reporting requirements: The evolving Minimum Information About a Proteomics Experiment (MIAPE) documents offer guidelines on how to adequately report a proteomics experiment. It is expected that these documents will be published, and that the requirements within will be enforced by journals, compliant repositories and funders (cf. MIAME). * XML formats for data exchange: Derived from the FuGE general object model, the formats developed by this workgroup are designed to function both as standalone files and as part of a "parent" FuGE-ML document. These formats will facilitate data exchange between researchers, and submission to repositories or journals. * Controlled vocabularies (CVs) and ontology: Lists of clearly defined terms are crucial for the construction of unambiguously worded data files. In addition to providing supporting CVs for the individual data capture formats as part of the integrated PSI CV, the Sample Processing WG will contribute terms to the Functional Genomics Ontology (FuGO).

Proper citation: HUPO Proteomics Standards Initiative (RRID:SCR_003158) Copy   

•   Source: SciCrunch Registry
  

http://splicq.sourceforge.net/

A Java software package which allows for the identification of splicing events and differentially expressed isoforms in next generation sequencing data.

Proper citation: SpliCQ (RRID:SCR_003266) Copy   

•   Source: SciCrunch Registry
  

http://www.geospiza.com/

Developer of enterprise-class software systems for workflow management of genetic analysis. Geospiza has established itself as the life science industry's top software developer for meeting the combined laboratory, data management and analytical needs of biotechnology and pharmaceutical companies, universities, researchers, contract core and diagnostic laboratories involved in genetic testing and manufacturing bio-therapeutics. Geospiza's products are designed and built by biologists, enabling researchers to focus on the science, not the software. *GeneSifter Analysis Edition: Access easy-to-use statistical, visualization and annotation tools for Microarray and Next Generation Sequencing data. *GeneSifter Lab Edition: Manage cross-platform core lab operations from a single interface out-of-the-box.

Proper citation: Geospiza (RRID:SCR_003264) Copy   

•   Source: SciCrunch Registry
  

http://sourceforge.net/projects/orfer/

An extended software package for high throughput PCR primer design for biological sequences. It reads the NCBI GenBank XML sequence format and extracts open reading frames for proteins. Sequences can be requested by GI or accession number.

Proper citation: ORFprimer (RRID:SCR_003269) Copy   

•   Source: SciCrunch Registry