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http://lrpath.ncibi.org/

Web tool to perform gene set enrichment testing. Used to test for predefined biologically relevant gene sets that contain more significant genes from experimental dataset than expected by chance. Logistic regression approach for identifying enriched biological groups in gene expression data.

Proper citation: LRPath (RRID:SCR_018572) Copy   

•   Source: SciCrunch Registry

https://github.com/marbl/Mash

Software tool for genome and metagenome distance estimation using MinHash. Reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated.

Proper citation: Mash (RRID:SCR_019135) Copy   

•   Source: SciCrunch Registry

https://github.com/raphael-group/chisel

Software tool to infer allele and haplotype specific copy numbers in individual cells from low coverage single cell DNA sequencing data. Integrates weak allelic signals across individual cells, powering strength of single cell sequencing technologies to overcome weakness. Includes global clustering of RDRs and BAFs, and rigorous model selection procedure for inferring genome ploidy that improves both inference of allele specific and total copy numbers.

Proper citation: CHISEL (RRID:SCR_023220) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/mammals/haploreg/haploreg.php

HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.

Proper citation: HaploReg (RRID:SCR_006796) Copy   

•   Source: SciCrunch Registry

http://pepr.cnmcresearch.org/

An experiment in web-database access to large multi-dimensional data sets using a standardized experimental platform to determine if the larger scientific community can be given simple, intuitive, and user-friendly web-based access to large microarray data sets. All data in PEPR is also available via NCBI GEO. The structure and goals of PEPR differ from other mRNA expression profiling databases in a number of important ways. * The experimental platform in PEPR is standardized, and is an Affymetrix - only database. All microarrays available in the PEPR web database should ascribe to quality control and standard operating procedures. A recent publication has described the QC/SOP criteria utilized in PEPR profiles ( The Tumor Analysis Best Practices Working Group 2004 ). * PEPR permits gene-based queries of large Affymetrix array data sets without any specialized software. For example, a number of large time series projects are available within PEPR, containing 40-60 microarrays, yet these can be simply queried via a dynamic web interface with no prior knowledge of microarray data analysis. * Projects in PEPR originate from scientists world-wide, but all data has been generated by the Research Center for Genetic Medicine, Children''''s National Medical Center, Washington DC. Future developments of PEPR will allow remote entry of Affymetrix data ascribing to the same QC/SOP protocols. They have previously described an initial implementation of PEPR, and a dynamic web-queried time series graphical interface ( Chen et al. 2004 ). A publication showing the utility of PEPR for pharmacodynamic data has recently been published ( Almon et al. 2003 ).

Proper citation: Public Expression Profiling Resource (RRID:SCR_007274) Copy   

•   Source: SciCrunch Registry

http://rulai.cshl.edu/cgi-bin/tools/ESE3/esefinder.cgi?process=home

A web-based resource that facilitates rapid analysis of exon sequences to identify putative exonic splicing enhancers (ESEs) responsive to the human SR proteins SF2/ASF, SC35, SRp40 and SRp55, and to predict whether exonic mutations disrupt such elements.

Proper citation: ESEfinder 3.0 (RRID:SCR_007088) Copy   

•   Source: SciCrunch Registry

https://pepatac.databio.org/en/latest/

Software standardized pipeline for ATAC-seq data analysis with serial alignments. Leverages unique features of ATAC-seq data to optimize for speed and accuracy, and provides several unique analytical approaches. Downstream analysis is simplified by standard definition format, modularity of components, and metadata APIs in R and Python. Restartable, fault-tolerant, and can be run on local hardware, using any cluster resource manager, or in provided Linux containers. We also emphasize the advantage of aligning to the mitochondrial genome serially, which improves alignment and quality control metrics. Includes quality control plots, summary statistics, and variety of data formats.

Proper citation: PEPATAC (RRID:SCR_024758) Copy   

•   Source: SciCrunch Registry

https://jackbibby1.github.io/SCPA/

Software R package for pathway analysis in scRNA-seq data. It’s a different approach to pathway analysis that defines pathway activity as a change in multivariate distribution of a given pathway across conditions, rather than enrichment or over representation of genes.

Proper citation: Single Cell Pathway Analysis (RRID:SCR_024909) Copy   

•   Source: SciCrunch Registry

http://thecellmap.org

Web accessible database for visualizing and mining global yeast genetic interaction network. Allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize sub networks, using data driven network layouts in intuitive and interactive manner. Used for storing and visualizing genetic interactions in S. cerevisiae.

Proper citation: TheCellMap (RRID:SCR_018728) Copy   

•   Source: SciCrunch Registry

https://dfam.org/home

Open collection of Transposable Element DNA sequence alignments, hidden Markov Models, consensus sequences, and genome annotations.Dfam 3.2 provides early access to uncurated, de novo generated families.

Proper citation: Dfam (RRID:SCR_021168) Copy   

•   Source: SciCrunch Registry

http://clovr.org/

A desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing.

Proper citation: CloVR (RRID:SCR_005290) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/

Community model organism database for laboratory mouse and authoritative source for phenotype and functional annotations of mouse genes. MGD includes complete catalog of mouse genes and genome features with integrated access to genetic, genomic and phenotypic information, all serving to further the use of the mouse as a model system for studying human biology and disease. MGD is a major component of the Mouse Genome Informatics.Contains standardized descriptions of mouse phenotypes, associations between mouse models and human genetic diseases, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information. Data are obtained and integrated via manual curation of the biomedical literature, direct contributions from individual investigators and downloads from major informatics resource centers. MGD collaborates with the bioinformatics community on the development and use of biomedical ontologies such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology.

Proper citation: Mouse Genome Database (RRID:SCR_012953) Copy   

•   Source: SciCrunch Registry

https://phenodb.org/

Database for phenotype genotype associations for humans. Used by clinical researchers to store standardized phenotypic information, diagnosis, and pedigree data and then run analyses on VCF files from individuals, families or cohorts with suspected Mendelian disease.

Proper citation: PhenoDB (RRID:SCR_016551) Copy   

•   Source: SciCrunch Registry

http://www.regulomedb.org/

Database that annotates SNPs with known and predicted regulatory elements in intergenic regions of H. sapiens genome. Known and predicted regulatory DNA elements include regions of DNAase hypersensitivity, binding sites of transcription factors, and promoter regions that have been biochemically characterized to regulation transcription. Source of these data include public datasets from GEO, ENCODE project, and published literature.

Proper citation: RegulomeDB (RRID:SCR_017905) Copy   

•   Source: SciCrunch Registry

http://hb.flatironinstitute.org/

Formerly known as GIANT (Genome-scale Integrated Analysis of gene Networks in Tissues), HumanBase applies machine learning algorithms to learn biological associations from massive genomic data collections. These integrative analyses reach beyond existing "biological knowledge" represented in the literature to identify novel, data-driven associations.

Proper citation: HumanBase (RRID:SCR_016145) Copy   

•   Source: SciCrunch Registry

http://www.oreganno.org/oregano/

Open source, open access database and literature curation system for community based annotation of experimentally identified DNA regulatory regions, transcription factor binding sites and regulatory variants. Automatically cross referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, eVOC: Cell type ontology, and Taxonomy database. Community driven resource for curated regulatory annotation.

Proper citation: Open Regulatory Annotation Database (RRID:SCR_007835) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/help/uniref

Databases which provide clustered sets of sequences from UniProt Knowledgebase and selected UniParc records, in order to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences from view. The UniRef100 database combines identical sequences and sub-fragments with 11 or more residues (from any organism) into a single UniRef entry. The sequence of a representative protein, the accession numbers of all the merged entries, and links to the corresponding UniProtKB and UniParc records are all displayed in the entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences with 11 or more residues such that each cluster is composed of sequences that have at least 90% (UniRef90) or 50% (UniRef50) sequence identity to the longest sequence (UniRef seed sequence). All the sequences in each cluster are ranked to facilitate the selection of a representative sequence for the cluster.

Proper citation: UniRef (RRID:SCR_010646) Copy   

•   Source: SciCrunch Registry

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

Software package for Hi-C/HiChIP interaction calling and differential analysis using efficient implementation of HiC-DC statistical framework. Enables principled statistical analysis of Hi-C and HiChIP data sets. Enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

Proper citation: HiCDCPlus (RRID:SCR_025317) Copy   

•   Source: SciCrunch Registry

https://trna.ucsc.edu/tRAX/

Software package built for in-depth analyses of tRNA-derived small RNAs (tDRs), mature tRNAs, and inference of RNA modifications from high-throughput small RNA sequencing data. Used for integrating analysis of tRNAs, tRNA-derived small RNAs, and tRNA modifications.

Proper citation: tRNA Analysis of eXpression (RRID:SCR_025486) Copy   

•   Source: SciCrunch Registry

https://github.com/willtownes/glmpca

Software R package for dimension reduction of non-normally distributed data. Generalized PCA for non-normally distributed data.

Proper citation: glmpca (RRID:SCR_025517) Copy   

•   Source: SciCrunch Registry