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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
A software tool for comparative visualization of genomes. It is based in the GBrowse frameworks and integrates with the annotation features.
Proper citation: SynView (RRID:SCR_001106) Copy
http://sourceforge.net/projects/sparseassembler/
Software for memory-efficient genome assembly. It utilizes sparse k-mer.
Proper citation: SparseAssembler (RRID:SCR_001100) Copy
A high-performance visualization tool for interactive exploration of large, integrated genomic datasets written primarily in JavaScript. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.
Proper citation: JBrowse (RRID:SCR_001004) Copy
http://patchwork.r-forge.r-project.org/
Software tool for analyzing and visualizing allele-specific copy numbers and loss-of-heterozygosity in cancer genomes. The data input is in the format of whole-genome sequencing data which enables characterization of genomic alterations ranging in size from point mutations to entire chromosomes. High quality results are obtained even if samples have low coverage, ~4x, low tumor cell content or are aneuploid. Patchwork takes BAM files as input whereas PatchworkCG takes input from CompleteGenomics files. TAPS performs the same analysis as Patchwork but for microarray data.
Proper citation: Patchwork (RRID:SCR_000072) Copy
Web based integrative platform for transcriptional regulation studies.
Proper citation: Cistrome (RRID:SCR_000242) Copy
https://github.com/feschottelab/REPCLASS
Tool for the classification of known transposable elements in eukaryotic genomes. It can be combined with ab initio repeat finding in order to recover contrasting transposable element landscapes between species.
Proper citation: REPCLASS (RRID:SCR_014654) Copy
https://gemini.readthedocs.io/en/latest/
Framework for exploring genetic variation in the context of the genome annotations available for the human genome. Users can load a VCF file into a database and each variant is automatically annotated by comparing it to several genome annotations from source such as ENCODE tracks, UCSC tracks, OMIM, dbSNP, KEGG, and HPRD.
Proper citation: GEMINI (RRID:SCR_014819) Copy
http://regulatorygenomicsgroup.org/chicago
Statistical pipeline for detecting significant chromosomal interactions in Capture Hi-C data. CHiCAGO uses a convolution background model accounting for both random Brownian collisions between chromatin fragments and technical noise. CHiCAGO then performs a p-value weighting procedure based on the expected true positive rates at different distance ranges, with scores representing soft-thresholded -log weighted p-values., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: CHiCAGO (RRID:SCR_014941) Copy
The Society aims to foster discovery and characterization of genomic variations including population distribution and phenotypic associations. We promote collection, documentation and free distribution of genomic variation information and associated clinical variations and endeavor to foster the development of the necessary methodology and informatics. Mission Statement To enhance human health through identification and characterization of changes in the genome that lead to susceptibility to illness. To this end, to collate the genomic information necessary for molecular diagnosis, research on basic mechanisms and design of treatments of human ailments. Society Journal Human Mutation is the Society journal. Members will receive a reduced subscription to the journal if they choose to subscribe. Meetings The Society holds two scientific meetings per year. One as a satellite to either the HUGO (Human Genome Organization) annual meeting or the ESHG (European Society of Human Genetics) annual meeting and one meeting is a satellite to the ASHG (American Society of Human Genetics annual meeting. The meetings are a forum for scientists to exchange ideas and form collaborations. Prominent speakers in the field are invited as well as a call for abstracts at large. The meetings are designed to update and increase knowledge of human genome variation and generally attract a stimulating and interesting collection of abstracts in all fields of human genome variation making it an ideal forum to share information and results. Past themes include: copy number variation, pathogenic or not?, pharmacogenomics, new DNA sequencing technologies, and genotype to pheontype relationships. We invite members and non-members alike to attend these meetings. The Society holds the Annual General Meeting of the members after the scientific meeting that is a satellite of the ASHG. Exhibitor''s booths The Society usually takes out an Exhibitor''s booth at the American & European Societies of Human Genetics annual meetings and sometimes the HUGO HGM meeting. GUIDELINES & RECOMMENDATIONS Members of the Society have formulated Guidelines & Recommendations on a number of topics, but especially for nomenclature of gene variations and guidelines on variation databases.
Proper citation: Human Genome Variation Society (RRID:SCR_012989) Copy
http://commonfund.nih.gov/GTEx/
Project to study human gene expression and regulation in multiple tissues, providing valuable insights into mechanisms of gene regulation and its disease related perturbations. Genetic variation between individuals will be examined for correlation with differences in gene expression level to identify regions of the genome that influence whether and how much a gene is expressed. Includes initiatives: Novel Statistical Methods for Human Gene Expression Quantitative Trait Loci (eQTL) Analysis ,Laboratory, Data Analysis, and Coordinating Center (LDACC), caHUB Acquisition of Normal Tissues in Support of GTEx Project.
Proper citation: Genotype-Tissue Expression (RRID:SCR_013042) Copy
http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml
This resource gives information about the U.S. Human Genome Project, which was was a 13-year effort to to discover all the estimated 20,000-25,000 human genes and make them accessible for further biological study. The primary project goals were to: - identify all the approximately 20,000-25,000 genes in human DNA, - determine the sequences of the 3 billion chemical base pairs that make up human DNA, - store this information in databases, - improve tools for data analysis, - transfer related technologies to the private sector, and - address the ethical, legal, and social issues (ELSI) that may arise from the project. To help achieve these goals, researchers also studied the genetic makeup of several nonhuman organisms. These include the common human gut bacterium Escherichia coli, the fruit fly, and the laboratory mouse. These parallel studies helped to develop technology and interpret human gene function. Sponsors: The DOE Human Genome Program and the NIH National Human Genome Research Institute (NHGRI) together sponsored the U.S. Human Genome Project.
Proper citation: Human Genome Project Information (RRID:SCR_013028) Copy
https://bitbucket.org/nsegata/phylophlan/wiki/Home
Software pipeline for reconstructing highly accurate and resolved phylogenetic trees based on whole-genome sequence information. Pipeline is scalable to thousands of genomes and uses the most conserved 400 proteins for extracting the phylogenetic signal. PhyloPhlAn also implements taxonomic curation, estimation, and insertion operations., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: PhyloPhlAn (RRID:SCR_013082) Copy
http://genetics.bwh.harvard.edu/pph2/
Software tool which predicts possible impact of amino acid substitution on structure and function of human protein using straightforward physical and comparative considerations. PolyPhen-2 is new development of PolyPhen tool for annotating coding nonsynonymous SNPs.
Proper citation: PolyPhen: Polymorphism Phenotyping (RRID:SCR_013189) Copy
http://web.bioinformatics.ic.ac.uk/eqtlexplorer/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 1,2023. eQTL Explorer was developed as a computational resource to visualize and explore data from combined genome-wide expression and linkage studies is essential for the development of testable hypotheses. This visualization tool stores expression profiles, linkage data and information from external sources in a relational database and enables simultaneous visualization and intuitive interpretation of the combined data via a Java graphical interface. eQTL Explorer also provides a new and powerful tool to interrogate these very large and complex datasets. eQTLexplorer allows users to mine and understand data from a repository of genetical genomics experiments. It will graphically display eQTL information based on a certain number of selection criteria, including: tissue type, p-value, cis/trans, probeset Affymetrix id and PQTL type. Sponsors: This work was funded by the MRC Clinical Sciences Centre and the Wellcome Trust programme for Cardiovascular Functional Genomics.
Proper citation: eQTL Visualization Tool (RRID:SCR_013413) Copy
http://www.mrc-lmb.cam.ac.uk/genomes/dolop/
DOLOP is an exclusive knowledge base for bacterial lipoproteins by processing information from 510 entries to provide a list of 199 distinct lipoproteins with relevant links to molecular details. Features include functional classification, predictive algorithm for query sequences, primary sequence analysis and lists of predicted lipoproteins from 43 completed bacterial genomes along with interactive information exchange facility. This website along will have additional information on the biosynthetic pathway, supplementary material and other related figures. DOLOP also contains information and links to molecular details for about 278 distinct lipoproteins and predicted lipoproteins from 234 completely sequenced bacterial genomes. Additionally, the website features a tool that applies a predictive algorithm to identify the presence or absence of the lipoprotein signal sequence in a user-given sequence. The experimentally verified lipoproteins have been classified into different functional classes and more importantly functional domain assignments using hidden Markov models from the SUPERFAMILY database that have been provided for the predicted lipoproteins. Other features include: primary sequence analysis, signal sequence analysis, and search facility and information exchange facility to allow researchers to exchange results on newly characterized lipoproteins.
Proper citation: DOLOP: A Database of Bacterial Lipoproteins (RRID:SCR_013487) Copy
http://ctb.pku.edu.cn/main/SheGroup/Software/MED2.htm
A non-supervised gene prediction algorithm for prokaryotic genomes with multivariate entropy distance method.
Proper citation: MED (RRID:SCR_013403) Copy
A universal collaborative platform for bioinformatics application development that allows users to store and share large data sets securely within and across organizations, with free access to public data from major databases. The platform includes open-source and proprietary genomics applications, working together independent of file formats. For developers an SDK, APIs and a marketplace are provided.
Proper citation: Genestack (RRID:SCR_011885) Copy
http://www.genboree.org/java-bin/EpigenomeAtlas/workbench.jsp?isPublic=yes&context=EpigenomeAtlas
Service where users are able to upload and store data, access bioinformatics tools, and perform analyses.
Proper citation: Genboree Workbench (RRID:SCR_011864) Copy
http://bioinfo-out.curie.fr/projects/snp_gap/
Software for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured by single-nucleotide polymorphism (SNP) arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. The method performs well even for poor-quality data, low tumor content, and highly rearranged tumor genomes.
Proper citation: Genome Alteration Print (RRID:SCR_012016) Copy
http://www.bioinformatics.ucla.edu/ASAP2
THIS RESOURCE IS NO LONGER IN SERVICE, documented on 8/12/13. An expanded version of the Alternative Splicing Annotation Project (ASAP) database with a new interface and integration of comparative features using UCSC BLASTZ multiple alignments. It supports 9 vertebrate species, 4 insects, and nematodes, and provides with extensive alternative splicing analysis and their splicing variants. As for human alternative splicing data, newly added EST libraries were classified and included into previous tissue and cancer classification, and lists of tissue and cancer (normal) specific alternatively spliced genes are re-calculated and updated. They have created a novel orthologous exon and intron databases and their splice variants based on multiple alignment among several species. These orthologous exon and intron database can give more comprehensive homologous gene information than protein similarity based method. Furthermore, splice junction and exon identity among species can be valuable resources to elucidate species-specific genes. ASAP II database can be easily integrated with pygr (unpublished, the Python Graph Database Framework for Bioinformatics) and its powerful features such as graph query, multi-genome alignment query and etc. ASAP II can be searched by several different criteria such as gene symbol, gene name and ID (UniGene, GenBank etc.). The web interface provides 7 different kinds of views: (I) user query, UniGene annotation, orthologous genes and genome browsers; (II) genome alignment; (III) exons and orthologous exons; (IV) introns and orthologous introns; (V) alternative splicing; (IV) isoform and protein sequences; (VII) tissue and cancer vs. normal specificity. ASAP II shows genome alignments of isoforms, exons, and introns in UCSC-like genome browser. All alternative splicing relationships with supporting evidence information, types of alternative splicing patterns, and inclusion rate for skipped exons are listed in separate tables. Users can also search human data for tissue- and cancer-specific splice forms at the bottom of the gene summary page. The p-values for tissue-specificity as log-odds (LOD) scores, and highlight the results for LOD >= 3 and at least 3 EST sequences are all also reported.
Proper citation: Alternative Splicing Annotation Project II Database (RRID:SCR_000322) Copy
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