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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.
https://github.com/PathwayAnalysisPlatform/PathwayMatcher
Software tool for multi omics pathway mapping and proteoform network generation. Open source software writen in Java to search for pathways related to a list of proteins in Reactome.
Proper citation: PathwayMatcher (RRID:SCR_016759) Copy
https://pachterlab.github.io/sleuth/about
Software tool for analysis of RNA-Seq experiments for which transcript abundances have been quantified with kallisto. Used for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance.
Proper citation: sleuth (RRID:SCR_016883) Copy
https://github.com/yarden/MISO/blob/fastmiso/docs/source/sashimi.rst
Software tool for quantitative visualization of aligned RNA-Seq reads that enables quantitative comparison of exon usage across samples or experimental conditions.
Proper citation: Sashimiplot (RRID:SCR_016861) Copy
Software tool to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically. It counts cells and also measures the size, shape, intensity and texture of every cell (and every labeled subcellular compartment) in every image. It was designed for high throughput screening but can perform automated image analysis for images from time-lapse movies and low-throughput experiments. CellProfiler has an increasing number of algorithms to identify and measure properties of neuronal cell types.
Proper citation: CellProfiler Image Analysis Software (RRID:SCR_007358) Copy
http://llama.mshri.on.ca/funcassociate/
A web-based tool that accepts as input a list of genes, and returns a list of GO attributes that are over- (or under-) represented among the genes in the input list. Only those over- (or under-) representations that are statistically significant, after correcting for multiple hypotheses testing, are reported. Currently 37 organisms are supported. In addition to the input list of genes, users may specify a) whether this list should be regarded as ordered or unordered; b) the universe of genes to be considered by FuncAssociate; c) whether to report over-, or under-represented attributes, or both; and d) the p-value cutoff. A new version of FuncAssociate supports a wider range of naming schemes for input genes, and uses more frequently updated GO associations. However, some features of the original version, such as sorting by LOD or the option to see the gene-attribute table, are not yet implemented. Platform: Online tool
Proper citation: FuncAssociate: The Gene Set Functionator (RRID:SCR_005768) Copy
http://www.jcvi.org/charprotdb/index.cgi/home
The Characterized Protein Database, CharProtDB, is designed and being developed as a resource of expertly curated, experimentally characterized proteins described in published literature. For each protein record in CharProtDB, storage of several data types is supported. It includes functional annotation (several instances of protein names and gene symbols) taxonomic classification, literature links, specific Gene Ontology (GO) terms and GO evidence codes, EC (Enzyme Commisssion) and TC (Transport Classification) numbers and protein sequence. Additionally, each protein record is associated with cross links to all public accessions in major protein databases as ��synonymous accessions��. Each of the above data types can be linked to as many literature references as possible. Every CharProtDB entry requires minimum data types to be furnished. They are protein name, GO terms and supporting reference(s) associated to GO evidence codes. Annotating using the GO system is of importance for several reasons; the GO system captures defined concepts (the GO terms) with unique ids, which can be attached to specific genes and the three controlled vocabularies of the GO allow for the capture of much more annotation information than is traditionally captured in protein common names, including, for example, not just the function of the protein, but its location as well. GO evidence codes implemented in CharProtDB directly correlate with the GO consortium definitions of experimental codes. CharProtDB tools link characterization data from multiple input streams through synonymous accessions or direct sequence identity. CharProtDB can represent multiple characterizations of the same protein, with proper attribution and links to database sources. Users can use a variety of search terms including protein name, gene symbol, EC number, organism name, accessions or any text to search the database. Following the search, a display page lists all the proteins that match the search term. Click on the protein name to view more detailed annotated information for each protein. Additionally, each protein record can be annotated.
Proper citation: CharProtDB: Characterized Protein Database (RRID:SCR_005872) Copy
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
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
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
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
https://github.com/stephens999/ashr
Software R package for adaptive shrinkage. Implements Empirical Bayes approach for large scale hypothesis testing and false discovery rate estimation.
Proper citation: Adaptive Shrinkage in R (RRID:SCR_023486) Copy
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
https://github.com/rondolab/MR-PRESSO
Software R package for performing Mendelian randomization pleiotropy residual sum and outlier method.Used to identify horizontal pleiotropic outliers in multi instrument summary level MR testing.
Proper citation: MR-PRESSO (RRID:SCR_023697) Copy
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
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
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
https://github.com/pjedge/longshot
Software variant calling tool for diploid genomes using long error prone reads such as Pacific Biosciences (PacBio) SMRT and Oxford Nanopore Technologies (ONT). Enables accurate variant calling in diploid genomes from single-molecule long read sequencing. Takes as input aligned BAM/CRAM file and outputs phased VCF file with variants and haplotype information.
Proper citation: longshot (RRID:SCR_025318) Copy
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
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
https://github.com/bmvdgeijn/WASP/
Software allele-specific pipeline for unbiased read mapping and molecular QTL discovery. Allele-specific software for robust molecular quantitative trait locus discovery.
Proper citation: WASP (RRID:SCR_025497) Copy
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