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http://www.hapsample.org/

Web application for simulating SNP genotypes for case-control and affected-child trio studies by resampling from Phase I/II HapMap SNP data. The user provides a list of SNPs to be genotyped, along with a disease model file that describes causal SNPs and their effect sizes. The simulation tool is appropriate for candidate regions or whole-genome scans. (entry from Genetic Analysis Software)

Proper citation: HAP-SAMPLE (RRID:SCR_009234) Copy   

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http://pages.stat.wisc.edu/~yandell/qtl/software/qtlbim/

Software library for QTL Bayesian Interval Mapping that provides a Bayesian model selection approach to map multiple interacting QTL. It works on experimentally inbred lines and performs a genome-wide search to locate multiple potential QTL. The package can handle continuous, binary and ordinal traits. (entry from Genetic Analysis Software)

Proper citation: R/QTLBIM (RRID:SCR_009375) Copy   

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http://www.ebi.ac.uk/ega/

Web service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The repository allows you to explore datasets from numerous genotype experiments, supplied by a range of data providers. The EGA''s role is to provide secure access to the data that otherwise could not be distributed to the research community. The EGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the EGA project. As an example, only members of the EGA team are allowed to process data in a secure computing facility. Once processed, all data are encrypted for dissemination and the encryption keys are delivered offline. The EGA also supports data access only for the consortium members prior to publication.

Proper citation: European Genome phenome Archive (RRID:SCR_004944) Copy   

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http://glioblastoma.alleninstitute.org/

Platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels that includes two interactive databases linked together by de-identified tumor specimen numbers to facilitate comparisons across data modalities: * The open public image database, here, providing in situ hybridization data mapping gene expression across the anatomic structures inherent in glioblastoma, as well as associated histological data suitable for neuropathological examination * A companion database (Ivy GAP Clinical and Genomic Database) offering detailed clinical, genomic, and expression array data sets that are designed to elucidate the pathways involved in glioblastoma development and progression. This database requires registration for access. The hope is that researchers all over the world will mine these data and identify trends, correlations, and interesting leads for further studies with significant translational and clinical outcomes. The Ivy Glioblastoma Atlas Project is a collaborative partnership between the Ben and Catherine Ivy Foundation, the Allen Institute for Brain Science and the Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment.

Proper citation: Ivy Glioblastoma Atlas Project (RRID:SCR_005044) Copy   

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http://bejerano.stanford.edu/prism/public/html/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRISM (Stanford database) (RRID:SCR_005375) Copy   

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http://202.97.205.78/CpG_MPs/

Tool for identification and analysis of CpG methylation patterns of genomic regions from high-throughput bisulfite sequencing data. It may identify the unmethylated and methylated regions for a single sample, the conserved and differential methylation regions with different methylation patterns for paired or multiple samples. It includes four main modules as follows: # Normalization of the sequencing reads of cytosines following guanines; # Identification of the unmethylated (methylated) regions using hotspot extension algorithm; # Identification of conservatively and differentially methylated regionsby combining the combinatorial algorithm for determination of potentially functional regions with the algorithm of analysis of variance (ANOVA) for assess the statistical significance of differentially methylated regions; # Extraction of sequence features and visualization of these potentially functional regions.

Proper citation: CpG MPs (RRID:SCR_005441) Copy   

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http://galton.uchicago.edu/~junzhang/LAPSTRUCT.html

Software application to describe population structure using biomarker data ( typically SNPs, CNVs etc.) available in a population sample. The main features different from PCA are: (1) geometrically motivated and graphic model based; (2)robustness of outliers. (entry from Genetic Analysis Software)

Proper citation: LAPSTRUCT (RRID:SCR_007550) Copy   

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http://bnmc.caltech.edu/

The Beckman Institute BNMC brings together researchers from many disciplines at Caltech to address problems in the mechanistic modeling of coupled genomic, intercellular and intracellular processes. It represents an attempt to encourage closer interaction and collaboration between groups in Biology, Control and Dynamical Systems, and the Center for Advanced Computing Research. The focus of BNMC is biochemical phenomena occurring within and between cells, in particular the mechanistic modeling of molecular networks of all kinds (e.g., transcriptional, regulatory, metabolic, signal transduction, mechanical, etc.) with and without spatial variation and intercellular communication. BNMC is formed as a coordinated effort aimed at (1) applying existing capabilities to collaboratively solve biological modeling problems that arise in answering scientific questions in Caltech laboratories, (2) exploring a diversity of novel approaches in order to achieve fundamental advances necessary to address the classes of modeling problems biologists want to solve, and (3) organizing projects to better share human experience as well as common infrastructure to avoid duplication and maximize solution interoperability.

Proper citation: Caltech, The Beckman Institute: The Biological Network Modeling Center (RRID:SCR_008060) Copy   

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http://www.pedigree-draw.com/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 12,2024. Software application for pedigree drawing (entry from Genetic Analysis Software)

Proper citation: Pedigree-Draw (RRID:SCR_008302) Copy   

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https://cran.r-project.org/web/packages/ibdreg/index.html

Software package in S-PLUS and R to test genetic linkage with covariates by regression methods with response IBD sharing for relative pairs. Account for correlations of IBD statistics and covariates for relative pairs within the same pedigree. (entry from Genetic Analysis Software)

Proper citation: IBDREG (RRID:SCR_013127) Copy   

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https://nels.bioinfo.no

Web portal for the administration of Norwegian e-Infrastructure for Life Sciences. Enables Norwegian life scientists and their international collaborators to store, share, archive, and analyse their genomics scale data. NeLS is one of the packages of the ELIXIR.NO project.

Proper citation: NeLS (RRID:SCR_016301) Copy   

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https://kona.nhgri.nih.gov/mnemiopsis/

Portal to obtain genomic information on Mnemiopsis. Data available provide annotations and other key biological information not available elsewhere. Used to advance research projects aimed at understanding phylogenetic diversity and evolution of proteins that play fundamental role in metazoan development. Collection of sequenced, assembled, annotated, and performed preliminary analysis of genome of Mnemiopsis.

Proper citation: Mnemiopsis Genome Project Portal (RRID:SCR_018293) Copy   

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http://www.molecularevolution.org/software/genomics/velvet

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package as de novo genomic assembler for short read sequencing technologies using de Bruijn graphs. Takes in short read sequences, removes errors, then produces high quality unique contigs, retrieves repeated areas between contigs. Can leverage very short reads in combination with read pairs to produce useful assemblies. Operating system Unix/Linux., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Velvet (RRID:SCR_010755) Copy   

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http://homer.ucsd.edu/

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

Proper citation: HOMER (RRID:SCR_010881) Copy   

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http://tagcleaner.sourceforge.net/

A software tool which can automatically detect and efficiently remove tag sequences from genomic and metagenomic datasets.

Proper citation: TagCleaner (RRID:SCR_011846) Copy   

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https://www.q2labsolutions.com/genomics-laboratories

Core provides whole genome to focused set gene expression and genotyping assays along with DNA sequencings services, sequence enrichment technologies and bioinformatics support. Platforms utilized include Affymetrix GeneChip, Agilent Sure Select, Fluidigm Access Arrays, Illumina BeadChip, iScan, Genome Analyzer and Hi-Seq, RainDance Technologies RDT 1000 and, the Pacific Biosciences PacBio RS. Expression Analysis offers solutions for challenging specimens such as whole blood and FFPE tissues, as well as nucleic acid isolation and data analysis services.

Proper citation: Q Squared Solutions Expression Analysis (RRID:SCR_012497) Copy   

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http://PlasmoDB.org

Functional genomic database for malaria parasites. Database for Plasmodium spp. Provides resource for data analysis and visualization in gene-by-gene or genome-wide scale. PlasmoDB 5.5 contains annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution data. Data can be queried by selecting from query grid or drop down menus. Results can be combined with each other on query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.Key community database for malaria researchers, intersecting many types of laboratory and computational data, aggregated by gene.

Proper citation: PlasmoDB (RRID:SCR_013331) Copy   

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http://www.viprbrc.org/brc/home.do?decorator=vipr

Provides searchable public repository of genomic, proteomic and other research data for different strains of pathogenic viruses along with suite of tools for analyzing data. Data can be shared, aggregated, analyzed using ViPR tools, and downloaded for local analysis. ViPR is an NIAID-funded resource that support the research of viral pathogens in the NIAID Category A-C Priority Pathogen lists and those causing (re)emerging infectious diseases. It provides a dedicated gateway to SARS-CoV-2 data that integrates data from external sources (GenBank, UniProt, Immune Epitope Database, Protein Data Bank), direct submissions, analysis pipelines and expert curation, and provides a suite of bioinformatics analysis and visualization tools for virology research.

Proper citation: Virus Pathogen Resource (ViPR) (RRID:SCR_012983) Copy   

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http://www.dkfz.de/en/epidemiologie-krebserkrankungen/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

Proper citation: PIAGE (RRID:SCR_013124) Copy   

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http://bioinformatics.ust.hk/BOOST.html

Software application (entry from Genetic Analysis Software) for a method for detecting gene-gene interactions. It allows examining all pairwise interactions in genome-wide case-control studies.

Proper citation: BOOST (RRID:SCR_013133) Copy   

•   Source: SciCrunch Registry