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https://ccb.jhu.edu/software/stringtie/

Software application for assembling of RNA-Seq alignments into potential transcripts. It enables improved reconstruction of a transcriptome from RNA-seq reads. This transcript assembling and quantification program is implemented in C++ .

Proper citation: StringTie (RRID:SCR_016323) Copy   

•   Source: SciCrunch Registry

https://clue.io

Dataset of cellular signatures that catalogs transcriptional responses of human cells to chemical and genetic perturbation. CMap contains perturbagens, expression signatures, and small molecules from cell lines.

Proper citation: CMap (RRID:SCR_016204) Copy   

•   Source: SciCrunch Registry

https://integrativeomics.shinyapps.io/pseudofun_app/

Software as database and query tool for homologous pseudogene and coding gene families. Collection of human pseudogenes and gene associations. Supports search, graphical visualization and functional analysis of pseudogenes and coding genes based on PGG families.

Proper citation: PseudoFuN (RRID:SCR_017095) Copy   

•   Source: SciCrunch Registry

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

http://hms-dbmi.github.io/scde/index.html

Software package that implements a set of statistical methods for analyzing single-cell RNA-seq data, including differential expression analysis (Kharchenko et al.) and pathway and geneset overdispersion analysis (Fan et al.)

Proper citation: SCDE (RRID:SCR_015952) 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://beetlebase.org/

A centralized sequence database and community resource for Tribolium genetics, genomics and developmental biology containing genomic sequence scaffolds mapped to 10 linkage groups, genetic linkage maps, the official gene set, Reference Sequences from NCBI (RefSeq), predicted gene models, ESTs and whole-genome tiling array data representing several developmental stages. The current version of Beetlebase is built on the Tribolium castaneum 3.0 Assembly (Tcas 3.0) released by the Human Genome Sequencing Center at the Baylor College of Medicine. The database is constructed using the upgraded Generic Model Organism Database (GMOD) modules. The genomic data is stored in a PostgreSQL relational database using the Chado schema and visualized as tracks in GBrowse. The genetic map is visualized using the comparative genetic map viewer CMAP. To enhance search capabilities, the BLAST search tool has been integrated with the GMOD tools. Tribolium castaneum is a very sophisticated genetic model organism among higher eukaryotes. As the member of a primitive order of holometabolous insects, Coleoptera, Tribolium is in a key phylogenetic position to understand the genetic innovations that accompanied the evolution of higher forms with more complex development. Coleoptera is also the largest and most species diverse of all eukaryotic orders and Tribolium offers the only genetic model for the profusion of medically and economically important species therein. The genome sequences may be downloaded.

Proper citation: BeetleBase (RRID:SCR_001955) Copy   

•   Source: SciCrunch Registry

http://www.tipharma.com/pharmaceutical-research-projects/predictive-drug-disposition-and-toxicology-research/adr-safety-biomarkers.html

Consortium to develop novel in vitro predictive screening tools and in vivo translational models and biomarkers to improve adverse drug reaction (ADR) hazard identification. This project studies the metabolic effects of eight drugs (among which are paracetamol and diclofenac ) with known side effects in the liver. By looking into the mechanics on a level ranging from the molecule to the patient, the researchers in this project aim to find biomarkers and develop tools for the early prediction of side effects of drugs. One of the breakthroughs in the project is the discovery that a person''''s genetic profile appears to be one of the mechanics that have an influence on the resistance to adverse drug reactions. The ability to identify adverse effects in an early stage will prevent much discomfort in patients and economic loss. Several PhD theses have been written from this project.

Proper citation: Towards novel translational safety biomarkers for adverse drug toxicity (RRID:SCR_004006) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.aecom.yu.edu/index.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Primary informatics resource for joint research efforts of the Albert Einstein College of Medicine and Montefiore Medical Center to facilitate the study and understanding of biological processes, clinical disorders, pathologic abnormalities, and the relationships among them, using a wide variety of informatics techniques, applications, and user training. Their services include: * Collaboration on research design to enable effective data management throughout all phases of a project * Provision of management capability for large volumes of data generated by microarrays and related technologies * Provision and supports a software toolchest for data capture, retrieval, and analysis * Design and implementation of custom interfaces to incorporate existing or separately designed databases into the central data management architecture * Support for data management for the Biorepository, to enhance specimen storage, identification, and linkage with clinical data * Ensuring conformity of data elements and structures to national standards via participation in standards organizations, facilitating intramural and extramural collaboration * Providing individualized support to end-users with bioinformatics training needs * Serving as a bioinformatics liaison to other research institutes and organizations * Providing data management support for clinical research * Providing a common, secure repository for clinical, experimental, and biosample storage data

Proper citation: Einstein-Montefiore ICTR Research Informatics Core (RRID:SCR_003451) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/databases/exomiser/query/exomiser2

A Java program that functionally annotates variants from whole-exome sequencing data starting from a VCF (Variant Call Format) file (version 4). The functional annotation code is based on Annovar and uses UCSCKnownGene transcript definitions and hg19 genomic coordinates. Variants are prioritized according to user-defined criteria on variant frequency, pathogenicity, quality, inheritance pattern, phenotype data from human and model organisms, and proximity in the interactome to phenotypically similar genes.

Proper citation: Exomiser (RRID:SCR_002192) Copy   

•   Source: SciCrunch Registry

https://www.proteinspire.org/MOPED/

An expanding multi-omics resource that enables rapid browsing of gene and protein expression information from publicly available studies on humans and model organisms. MOPED also serves the greater research community by enabling users to visualize their own expression data, compare it with existing studies, and share it with others via private accounts. MOPED uniquely provides gene and protein level expression data, meta-analysis capabilities and quantitative data from standardized analysis utilizing SPIRE (Systematic Protein Investigative Research Environment). Data can be queried for specific genes and proteins; browsed based on organism, tissue, localization and condition; and sorted by false discovery rate and expression. MOPED links to various gene, protein, and pathway databases, including GeneCards, Entrez, UniProt, KEGG and Reactome. The current version of MOPED (MOPED 2.5) The current version of MOPED (MOPED 2.5, 2014) contains approximately 5 million total records including ~260 experiments and ~390 conditions.

Proper citation: MOPED - Model Organism Protein Expression Database (RRID:SCR_006065) Copy   

•   Source: SciCrunch Registry

http://genome.jgi.doe.gov/programs/fungi/index.jsf

Fungal genomics database and interactive analytical tools that integrates all fungal genomes for diverse fungi that are important for energy and environment, the focus of the JGI Fungal program. It integrates genomics data from the DOE JGI and its users and promotes user community participation in data submission, annotation and analysis. Over 100 newly sequenced and annotated fungal genomes from JGI and elsewhere are available to the public through MycoCosm, and new annotated genomes are being added to this resource upon completion of annotation. MycoCosm offers web-based genome analysis tools for fungal biologists to ''navigate'' through sequenced genomes and explore them in the context of ''genome-centric'' and ''comparative views''.

Proper citation: MycoCosm (RRID:SCR_005312) Copy   

•   Source: SciCrunch Registry

http://www.emouseatlas.org/emage

A database of in situ gene expression data in the developing mouse embryo and an accompanying suite of tools to search and analyze the data. mRNA in situ hybridization, protein immunohistochemistry and transgenic reporter data is included. The data held is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. The conceptual framework which houses the descriptions of the gene expression patterns in EMAGE is the EMAP Mouse Embryo Anatomy Atlas. This consists of a set of 3D virtual embryos at different stages of development, as well as an accompanying ontology of anatomical terms found at each stage. The raw data images can be conventional 2D photographs (of sections or wholemount specimens) or 3D images of wholemount specimens derived from Optical Projection Tomography (OPT) or confocal microscopy. Users may submit data using a Data submission tool or without.

Proper citation: EMAGE Gene Expression Database (RRID:SCR_005391) Copy   

•   Source: SciCrunch Registry

http://genecodis.cnb.csic.es/

Web-based tool for the ontological analysis of large lists of genes. It can be used to determine biological annotations or combinations of annotations that are significantly associated to a list of genes under study with respect to a reference list. As well as single annotations, this tool allows users to simultaneously evaluate annotations from different sources, for example Biological Process and Cellular Component categories of Gene Ontology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GeneCodis (RRID:SCR_006943) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/clinvar/

Archive of aggregated information about sequence variation and its relationship to human health. Provides reports of relationships among human variations and phenotypes along with supporting evidence. Submissions from clinical testing labs, research labs, locus-specific databases, expert panels and professional societies are welcome. Collects reports of variants found in patient samples, assertions made regarding their clinical significance, information about submitter, and other supporting data. Alleles described in submissions are mapped to reference sequences, and reported according to HGVS standard.

Proper citation: ClinVar (RRID:SCR_006169) Copy   

•   Source: SciCrunch Registry

http://www.oeb.harvard.edu/faculty/hartl/old_site/lab/publications/GeneMerge.html

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Web-based and standalone application that returns a wide range of functional genomic data for a given set of study genes and provides rank scores for over-representation of particular functions or categories in the data. It uses the hypergeometric test statistic which returns statistically correct results for samples of all sizes and is the #2 fastest GO tool available (Khatri and Draghici, 2005). GeneMerge can be used with any discrete, locus-based annotation data, including, literature references, genetic interactions, mutant phenotypes as well as traditional Gene Ontology queries. GeneMerge is particularly useful for the analysis of microarray data and other large biological datasets. The big advantage of GeneMerge over other similar programs is that you are not limited to analyzing your data from the perspective of a pre-packaged set of gene-association data. You can download or create gene-association files to analyze your data from an unlimited number of perspectives. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMerge (RRID:SCR_005744) Copy   

•   Source: SciCrunch Registry