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https://www.bioconductor.org/packages/release/bioc/html/SingleR.html

Software R package for unbiased cell type recognition of scRNA-seq data. Performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer cell of origin of each single cell independently.

Proper citation: SingleR (RRID:SCR_023120) Copy   

•   Source: SciCrunch Registry

https://benjjneb.github.io/dada2/

Open source software R package for modeling and correcting Illumina sequenced amplicon errors. Fast and accurate sample inference from amplicon data with single nucleotide resolution.

Proper citation: DADA2 (RRID:SCR_023519) Copy   

•   Source: SciCrunch Registry

https://github.com/cliu32/athlates

Software package for determining HLA genotypes for individuals from Illumina exome sequencing data. Program applies assembly, allele identification and allelic pair inference to short read sequences, and applies it to data from Illumina platforms.

Proper citation: ATHLATES (RRID:SCR_023689) Copy   

•   Source: SciCrunch Registry

http://www.niaid.nih.gov/about/organization/dait/pages/csgadp.aspx

Collaborative network of investigators with a focus on prevention of autoimmune disease, defined as halting the development of autoimmune disease prior to clinical onset by means other than global immunosuppression, and an emphasis on Type 1 diabetes. Its mission is to engage in scientific discovery that significantly advances knowledge for the prevention and regulation of autoimmune disease. The specific goals enunciated in pursuit of this mission are: * To create improved models of disease pathogenesis and therapy to better understand immune mechanisms that will provide opportunities for prevention strategies * To use these models as validation platforms with which to test new tools applicable to human studies * To encourage core expertise and collaborative projects designed for rapid translation from animal to human studies, emphasizing the development of surrogate markers for disease progression and/or regulation which can be utilized in the context of clinical trials

Proper citation: Cooperative Study Group for Autoimmune Disease Prevention (RRID:SCR_006803) Copy   

•   Source: SciCrunch Registry

http://www.cbs.dtu.dk/services/NetMHCpan/

Web server for quantitative prediction of peptide binding to any MHC molecule of known sequence using artificial neural networks. Characterizes binding specificity of given major histocompatibility complex molecule and predicts peptide length profile and peptide binding affinity. NetMHCpan 3.0 is improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length data sets. NetMHCpan 4.0 is trained on naturally eluted ligands and on peptide binding affinity data. NetMHCpan-4.1 server predicts binding of peptides to any MHC molecule of known sequence using artificial neural networks (ANNs).

Proper citation: NetMHCpan Server (RRID:SCR_018182) Copy   

•   Source: SciCrunch Registry

https://github.com/mwang87/MassQueryLanguage

Software application for universal searching of Mass Spectrometry data. Open source MS query language for flexible and mass spectrometer manufacturer-independent mining of MS data. Implements common MS terminology to build consensus vocabulary to search for MS patterns in single mass spectrometry run. Enables set of mass spectrometry patterns to be queried directly from raw data.

Proper citation: MassQL (RRID:SCR_025106) Copy   

•   Source: SciCrunch Registry

https://github.com/sxf296/drug_targeting

Software tool to detect phenotypically relevant drug targets through unique transcriptomic enrichment that emphasizes biological directionality of drug-derived gene sets. Exploratory tool to screen for possible drug targeting molecules.

Proper citation: drug perturbation Gene Set Enrichment Analysis (RRID:SCR_025351) Copy   

•   Source: SciCrunch Registry

https://github.com/immunogenomics/masc

Software tool for testing whether specified covariate influences membership of single cells in any of multiple cellular subsets while accounting for technical confounds and biological variation.

Proper citation: Mixed effects association testing for single cells (RRID:SCR_025632) Copy   

•   Source: SciCrunch Registry

http://www.immuneprofiling.org/

Consortium established to capitalize on recent advances in immune profiling methods in order to create a novel public resource that characterizes diverse states of the human immune system following infection; prior to and following vaccination against an infectious disease; or prior to and following treatment with an immune adjuvant that targets a known innate immune receptor(s). Through this program, well-characterized human cohorts are studied using a variety of modern analytic tools, including multiplex transcriptional, cytokine, and proteomic assays; multiparameter phenotyping of leukocyte subsets; assessment of leukocyte functional status; and multiple computational methods. Centralized research resources and a comprehensive, centralized database will be constructed for use by the greater scientific community. The information gained from the program will provide a comprehensive understanding of the human immune system and its regulation, and will reveal novel associations between components of the immune system and other biological systems, identify novel immune mediators and pathways, establish predictors of vaccine safety in different populations, and enable the rapid evaluation of different vaccine formulations and administration regimens in human populations.

Proper citation: Human Immunology Project Consortium (RRID:SCR_001491) Copy   

•   Source: SciCrunch Registry

https://david.ncifcrf.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

Proper citation: DAVID (RRID:SCR_001881) Copy   

•   Source: SciCrunch Registry

http://hiv-web.lanl.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4, 2023. HIV Sequence Database is a database of annotated HIV sequences, plus a variety of tools and information for researchers studying HIV and SIV. The main aim of this website is to provide easy access to our sequence database, alignments, and the tools and interfaces we have produced. The HIV Sequence Database focuses on five primary goals: * Collecting HIV and SIV sequence data (all sequences since 1987) * Curating and annotating this data, and making it available to the scientific community * Computer analysis of HIV and related sequences * Production of software for the analysis of (sequence) data * The data and analyses on this site and published in a yearly printed publication, the HIV sequence Compendium, which is available free of charge.

Proper citation: HIV Sequence Database (RRID:SCR_002906) Copy   

•   Source: SciCrunch Registry

http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/

Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy   

•   Source: SciCrunch Registry

http://hcv.lanl.gov/content/sequence/HCV/ToolsOutline.html

The HCV sequence database collects and annotates sequence data and provides them to the public via a website that contains a user-friendly search interface and a large number of sequence analysis tools, based on the model of the highly regarded Los Alamos HIV database. The hepatitis C virus (HCV) is a significant threat to public health worldwide. The virus is highly variable and evolves rapidly, making it an elusive target for the immune system and for vaccine and drug design. At present, some 30 000 HCV sequences have been published. This central website provides annotated sequences and analysis tools that will be helpful to HCV scientists worldwide. Things you can do: * Find sequences in the database * Download sequences from the database * Retrieve data about the sequences * Analyze sequences * Work with the sequences using our tools * Download ready-made alignments The HCV sequence database was officially launched in September 2003. Since then, its usage has steadily increased and is now at an average of approximately 280 visits per day from distinct IP addresses.

Proper citation: HCV Sequence Database (RRID:SCR_006019) Copy   

•   Source: SciCrunch Registry

http://www.ontobee.org/

Web-based linked data server and browser specifically designed for ontology terms, it supports ontology visualization, query, and development. Ontobee provides a web interface for displaying the details and hierarchy of a specific ontology term. Meanwhile, Ontobee provides a RDF source code for the particular web page, which supports remote query of the ontology term and the Semantic Web. Ontobee provides an efficient and publicly available method to promote ontology sharing, interoperability, and data integration.

Proper citation: Ontobee (RRID:SCR_006321) Copy   

•   Source: SciCrunch Registry

http://www.usidnet.org/

Research consortium to advance scientific research in the primary immune deficiency diseases (PIDD) and: * Assemble and maintain a registry of patients with primary immunodeficiency diseases to provide a minimum estimate of the prevalence of each disorder in the United States. Provide a comprehensive clinical picture of each disorder and act as a resource for clinical and laboratory research. * Establish a multifaceted mentoring program to introduce new investigators into the field and stimulate interest and research in primary immune deficiency diseases. * Establish an advisory/review committee to maintain a cell/DNA Repository of biologic material from well-characterized PIDD patients for the advancement of scientific research USIDNET operates a large database of patient information for your use. The purpose and scope of this project is to assemble and maintain a registry of residents with primary immunodeficiency diseases. The project was started with the Registry of U.S. Residents with Chronic Granulomatous Disease. Since then, the registry has been expanded and now collects data on all primary immunodeficiency disorders. The following are just a few of the diseases housed in the registry: Chronic Granulomatous Disease, Common Variable Immunodeficiency Disease, DiGeorge Anomaly, Hyper IgM Syndrome, Leukocyte Adhesion Defect, Severe Combined Immunodeficiency Disease, Wiskott-Aldrich Syndrome, X-Linked Agammaglobulinemia Physicians who would like to register their patients or access the registry are encouraged to contact Onika Davis or Lamar Hamilton, USIDNET team, at odavis (at) primaryimmune.org, or lhamilton (at) primaryimmune.org

Proper citation: USIDNET: US Immunodeficiency Network (RRID:SCR_004672) Copy   

•   Source: SciCrunch Registry

http://eupathdb.org/eupathdb/

EuPathDB integrates numerous database resources and multiple data types. The phylum Apicomplexa comprises veterinary and medically important parasitic protozoa including human pathogenic species of genera Cryptosporidium, Plasmodium and Toxoplasma. ApiDB serves not only as database but unifies access to three major existing individual organism databases, PlasmoDB.org, ToxoDB.org and CryptoDB.org, and integrates these databases with data available from additional sources. Through ApiDB site, users may pose queries and search all available apicomplexan data and tools, or they may visit individual component organism databases. EuPathDB Bioinformatics Resource Center for Biodefense and Emerging/Re-emerging Infectious Diseases is a portal for accessing genomic-scale datasets associated with eukaryotic pathogens.

Proper citation: Eukaryotic Pathogen Database Resources (RRID:SCR_004512) Copy   

•   Source: SciCrunch Registry

http://www.hiv.lanl.gov/content/index

Contains comprehensive data on HIV genetic sequences and immunological epitopes. This collection of databases contains tools to visualize and analyze HIV-related data.

Proper citation: HIV Databases (RRID:SCR_000614) Copy   

•   Source: SciCrunch Registry

https://masst.gnps2.org/microbemasst/

Web taxonomically informed mass spectrometry search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging database of over 60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns.

Proper citation: microbeMASST (RRID:SCR_024713) Copy   

•   Source: SciCrunch Registry

http://www.sb.cs.cmu.edu/drem

The Dynamic Regulatory Events Miner (DREM) allows one to model, analyze, and visualize transcriptional gene regulation dynamics. The method of DREM takes as input time series gene expression data and static transcription factor-gene interaction data (e.g. ChIP-chip data), and produces as output a dynamic regulatory map. The dynamic regulatory map highlights major bifurcation events in the time series expression data and transcription factors potentially responsible for them. DREM 2.0 was released and supports a number of new features including: * new static binding data for mouse, human, D. melanogaster, A. thaliana * a new and more flexible implementation of the IOHMM supports dynamic binding data for each time point or as a mix of static/dynamic TF input * expression levels of TFs can be used to improve the models learned by DREM * the motif finder DECOD can be used in conjuction with DREM and help find DNA motifs for unannotated splits * new features for the visualization of expressed TFs, dragging boxes in the model view, and switching between representations

Proper citation: Dynamic Regulatory Events Miner (RRID:SCR_003080) Copy   

•   Source: SciCrunch Registry

http://www.cs.cmu.edu/~jernst/stem/

The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy   

•   Source: SciCrunch Registry