Tools   Select Another Resource Report Type

https://github.com/madeluis/GENIST

Software tool as an algorithm to infer gene regulatory networks from spatial and temporal datasets. Spatial dataset or any data that can provide information about coexpression is used by the first step of the algorithm to perform clustering and separate the genes in the network in smaller coexpressed groups. Temporal dataset is used by the second step of the algorithm to infer regulations among the genes, based on Bayesian networks.

Proper citation: GENIST (RRID:SCR_016942) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/charade/svengine

Software for analysis and simulation of gene sequences and structural variants. This software works with FASTA, FASTQ, BAM, VAR, META, and NEWICK file formats.

Proper citation: SVEngine (RRID:SCR_016235) Copy   

•   Source: SciCrunch Registry

https://github.com/shanglicheng/RandomPooling

Software tool to identify the most reliable differences between any two groups . Used to identify differentially expressed genes between two groups.

Proper citation: RandomPooling (RRID:SCR_016607) Copy   

•   Source: SciCrunch Registry

http://brainarchitecture.org/allen-atlas-brain-toolbox

Software Matlab toolbox for quantitative analysis of digitized brain wide gene expression data from Allen Atlas of adult mouse brain.

Proper citation: Brain Gene Expression Analysis toolbox (RRID:SCR_017438) Copy   

•   Source: SciCrunch Registry

https://www.rdocumentation.org/packages/DGCA/versions/1.0.2

Software R package to perform differential gene correlation analysis. Performs differential correlation analysis on input matrices, with multiple conditions specified by design matrix.

Proper citation: Differential Gene Correlation Analysis (RRID:SCR_020964) Copy   

•   Source: SciCrunch Registry

http://faryabi05.med.upenn.edu:8050/

Portal for scRNA-seq study. Includes dendrogram visualization and clustering of all cells in scRNA-seq study as well as interactive filtered views for cell type, gene and/or donor group.

Proper citation: Mapping the pancreas and its ecosystem at the cellular level in health and type 1 diabetes (RRID:SCR_020952) Copy   

•   Source: SciCrunch Registry

http://www.seattle.eric.research.va.gov/VETR/Home.asp

The Vietnam Era Twin (VET) Registry is a closed cohort composed of approximately 7,000 middle-aged male-male twin pairs both of whom served in the military during the time of the Vietnam conflict (1964-1975). The Registry is a United States Department of Veterans Affairs (VA) resource that was originally constructed from military records; the Registry has been in existence for almost 20 years. It is one of the largest national twin registries in the US and currently has members living in all 50 states. Initially formed to address questions about the long-term health effects of service in Vietnam, the Registry has evolved into a resource for genetic epidemiological studies of mental and physical health conditions. Several waves of mail and telephone surveys have collected a wealth of health-related information on Registry twins, referred to as members. In addition to twins, selected adult offspring of twins and the mothers of those offspring are also VET Registry members. More recent data collection efforts have focused on specific sets of twin pairs and have conducted detailed clinical or laboratory testing. Selected Vietnam Era Registry Research Studies: * Veteran Health Study * VETSA 2: A Longitudinal Study of Cognitive Aging * Alcoholism Course thought Midlife: A Twin Family Study and Offspring of Twins: G, E and GxE Risk for Alcoholism * GE: Offspring of Twins with Substance Use Disorder * Mechanisms Linking Depression to Cardiovascular Risk (Twins Heart Study 2) * Post-traumatic Stress Disorder and Cardiovascular Disease * Biological Markers for Post-traumatic Stress Disorder (T3) * Memory and the Hippocampus in Vietnam-era Twins with PTSD (Time 3)

Proper citation: Vietnam Era Twin Registry (RRID:SCR_008807) Copy   

•   Source: SciCrunch Registry

http://www.cdc.gov/genomics/hugenet/default.htm

Human Genome Epidemiology Network, or HuGENet, is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. Its goals include: establishing an information exchange that promotes global collaboration in developing peer-reviewed information on the relationship between human genomic variation and health and on the quality of genetic tests for screening and prevention; providing training and technical assistance to researchers and practitioners interested in assessing the role of human genomic variation on population health and how such information can be used in practice; developing an updated and accessible knowledge base on the World Wide Web; and promoting the use of this knowledge base by health care providers, researchers, industry, government, and the public for making decisions involving the use of genetic information for disease prevention and health promotion. HuGENet collaborators come from multiple disciplines such as epidemiology, genetics, clinical medicine, policy, public health, education, and biomedical sciences. Currently, there are 4 HuGENet Coordinating Centers for the implementation of HuGENet activities: CDC''s Office of Public Health Genomics, Atlanta, Georgia; HuGENet UK Coordinating Center, Cambridge, UK; University of Ioannina, Greece; University of Ottawa , Ottawa, Canada. HuGENet includes: HuGE e-Journal Club: The HuGE e-Journal Club is an electronic discussion forum where new human genome epidemiologic (HuGE) findings, published in the scientific literature in the CDC''s Office of Public Health Genomics Weekly Update, will be abstracted, summarized, presented, and discussed via a newly created HuGENet listserv. HuGE Reviews: A HuGE Review identifies human genetic variations at one or more loci, and describes what is known about the frequency of these variants in different populations, identifies diseases that these variants are associated with and summarizes the magnitude of risks and associated risk factors, and evaluates associated genetic tests. Reviews point to gaps in existing epidemiologic and clinical knowledge, thus stimulating further research in these areas. HuGE Fact Sheets: HuGE Fact Sheets summarize information about a particular gene, its variants, and associated diseases. HuGE Case Studies: An on-line presentation designed to sharpen your epidemiological skills and enhance your knowledge on genomic variation and human diseases. Its purpose is to train health professionals in the practical application of human genome epidemiology (HuGE), which translates gene discoveries to disease prevention by integrating population-based data on gene-disease relationships and interventions. Students will acquire conceptual and practical tools for critically evaluating the growing scientific literature in specific disease areas. HUGENet Publications: Articles related to the HuGENet movement written by our HuGENet collaborators. HuGE Navigator: An integrated, searchable knowledge base of genetic associations and human genome epidemiology, including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. HuGE Workshops: HuGENet has sponsored meetings and workshops with national and international partners since 2001. Available are detailed summaries, agendas or the ability to download speaker slides. HuGE Book: Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease. (The findings and conclusions in this book are those of the author(s) and do not necessarily represent the views of the funding agency.) HuGENet Collaborators: HuGENet is interested in establishing collaborations with individuals and organizations working on population based research involving genetic information. HuGE Funding: Funding opportunities for specific population-based genetic epidemiology research projects are available. Research initiatives whose aims include assessing the prevalence of human genetic variation, the association between genetic variants and human diseases, the measurement of gene-gene or gene-environment interaction, and the evaluation of genetic tests for screening and prevention are compiled to create a posted listing. Additional information and application details can be found by clicking on the respective links.

Proper citation: Human Genome Epidemiology Network (RRID:SCR_013117) Copy   

•   Source: SciCrunch Registry

http://david.abcc.ncifcrf.gov/content.jsp?file=/ease/ease1.htm&type=1

Windows(c) desktop software application, customizable and standalone, that facilitates the biological interpretation of gene lists derived from the results of microarray, proteomic, and SAGE experiments. Provides statistical methods for discovering enriched biological themes within gene lists, generates gene annotation tables, and enables automated linking to online analysis tools. Offers statistical models to deal with multi-test comparison problem. Platform: Windows compatible

Proper citation: EASE: the Expression Analysis Systematic Explorer (RRID:SCR_013361) Copy   

•   Source: SciCrunch Registry

https://github.com/aertslab/SCENIC

Software R package as single cell regulatory network inference and clustering. Used for simultaneous gene regulatory network reconstruction and cell state identification from single cell RNA-seq data.

Proper citation: SCENIC (RRID:SCR_017247) Copy   

•   Source: SciCrunch Registry

https://www.4dnucleome.org

Research project to understand the principles underlying nuclear organization in space and time, the role nuclear organization plays in gene expression and cellular function, and how changes in nuclear organization affect normal development and diseases. Portal provides free access to datasets, software packages, and protocols to advance biomedical research of nuclear architecture. Aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes.

Proper citation: 4D Nucleome (RRID:SCR_016925) Copy   

•   Source: SciCrunch Registry

https://hub.docker.com/r/mziemann/tallyup/

Docker image that is used to process all of the data present in the Digital Expression Explorer 2 dataset. It can be freely used by anyone to process data on NCBI SRA or process their own RNA-seq fastq files. Used for bulk reprocessing of public RNA-seq data from SRA. The pipeline tallies the reads assigned to each gene or transcript.

Proper citation: Digital Expression Explorer 2 Docker Image (RRID:SCR_016931) Copy   

•   Source: SciCrunch Registry

http://ophid.utoronto.ca/mirDIP/

microRNA data integration portal to find microRNAs that target a gene, or genes targeted by a microRNA, in Homo sapiens. Software to integrate prediction databases to elucidate accurate microRNA:target relationships. Used for human microRNA prediction studies.

Proper citation: mirDIP (RRID:SCR_016770) Copy   

•   Source: SciCrunch Registry

http://cab.spbu.ru/software/rnaquast/

Software tool for evaluating RNA-Seq assembly quality and benchmarking transcriptome assemblers using reference genome and gene database. Capable to estimate gene database coverage by raw reads and de novo quality assessment using third party software.

Proper citation: rnaQUAST (RRID:SCR_016994) Copy   

•   Source: SciCrunch Registry

http://galaxy.cineca.it/fusion/main

Portal provides an easy access to a comprehensive database designed for storing, displaying and annotating gene fusion events detected from NGS data. It can query a database of somatic fusion genes events predicted and annotated starting from paired-end RNA-seq data.

Proper citation: LiGeA (RRID:SCR_015940) Copy   

•   Source: SciCrunch Registry

https://www.thermofisher.com/order/catalog/product/4363993

Software tool by Applied Biosystems to design primers and probes using TaqMan and SYBR Green I dye chemistries for gene quantitation and allelic discrimination (SNP) real-time PCR applications. Developed for use with StepOne, StepOnePlus, 7300, 7500, 7500 Fast, 7900HT, ViiA 7, and QuantStudio real-time PCR systems. Provides customized application specific documents for absolute⁄relative quantitation and allelic discrimination.

Proper citation: Primer Express Software (RRID:SCR_017376) Copy   

•   Source: SciCrunch Registry

https://github.com/lufuhao/AutoEVM

Software tool as Autorun Evidence Modeler. Requires EVidenceModeler (aka EVM) software which combines ab into gene predictions and protein and transcript alignments into weighted consensus gene structures.

Proper citation: AutoEVM (RRID:SCR_017556) Copy   

•   Source: SciCrunch Registry

http://gene64.dna.affrc.go.jp/RPD/main_en.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 22, 2016.

A database on the proteome of rice that contains reference maps based on two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) of proteins from rice tissues and subcellular compartments.

Proper citation: Rice Proteome Database (RRID:SCR_000743) Copy   

•   Source: SciCrunch Registry

http://www-personal.umich.edu/~jianghui/rseq/

A software toolkit for RNA sequence data analysis. It contains programs that cover several aspects of RNA-Seq data analysis such as read quality assessment, reference sequence generation, sequence mapping, and gene and isoform expressions estimations.

Proper citation: rSeq (RRID:SCR_000562) Copy   

•   Source: SciCrunch Registry

http://psychiatry.igm.jhmi.edu/SynaptomeDB/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Ontology-based knowledgebase for synaptic genes. These genes encode components of the synapse including neurotransmitters and their receptors, adhesion / cytoskeletal proteins, scaffold proteins, transporters, and others. It integrates various and complex data sources for synaptic genes and proteins., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SynaptomeDB (RRID:SCR_000157) Copy   

•   Source: SciCrunch Registry