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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://software.broadinstitute.org/cancer/cga/polysolver
Software tool for HLA typing based on whole exome sequencing data and infers alleles for three major MHC class I genes. Enables accurate inference of germline alleles of class I HLA-A, B and C genes and subsequent detection of mutations in these genes using inferred alleles as reference.
Proper citation: Polysolver (RRID:SCR_022278) Copy
https://cytotrace.stanford.edu/
Software tool that predicts differentiation state of cells from single cell RNA sequencing data. Used for predicting differentiation states from scRNA-seq data.
Proper citation: CytoTRACE (RRID:SCR_022828) Copy
https://github.com/walaj/svaba
Software tool for detecting structural variants in sequencing data using genome wide local assembly. Genome wide detection of structural variants and indels by local assembly. Used for detecting SVs from short read sequencing data using genome wide local assembly with low memory and computing requirements.
Proper citation: SvABA (RRID:SCR_022998) Copy
https://immunedb.readthedocs.io/en/latest/
Software system for storing and analyzing high throughput B and T cell immune receptor sequencing data. Comprised of web interface and of Python analysis tools to process raw reads for gene usage, infer clones, aggregate data, and run downstream analyses, or in conjunction with other AIRR tools using its import and export features.
Proper citation: ImmuneDB (RRID:SCR_017125) Copy
Software tool as data and metadata repository of Extracellular RNA Communication Consortium. Atlas includes small RNA sequencing and qPCR derived exRNA profiles from human and mouse biofluids. All RNAseq datasets are processed using version 4 of exceRpt small RNAseq pipeline. Atlas accepts submissions for RNAseq or qPCR data.
Proper citation: exRNA Atlas (RRID:SCR_017221) Copy
Web service for querying or retrieving gene annotation data.
Proper citation: MyGene.info (RRID:SCR_018660) Copy
https://github.com/plaisier-lab/sygnal
Software pipeline to integrate correlative, causal and mechanistic inference approaches into unified framework that systematically infers causal flow of information from mutations to TFs and miRNAs to perturbed gene expression patterns across patients. Used to decipher transcriptional regulatory networks from multi-omic and clinical patient data. Applicable for integrating genomic and transcriptomic measurements from human cohorts.
Proper citation: SYGNAL (RRID:SCR_023080) Copy
https://github.com/qianli10000/mtradeR
Software R package implements Joint model with Matching and Regularization and simulation pipeline. Used to test association between taxa and disease risk, and adjusted for correlated taxa screened by pre-selection procedure in abundance and prevalence, individually.
Proper citation: mtradeR (RRID:SCR_022977) Copy
https://github.com/Shenhav-and-Korem-labs/SCRuB
Software R package to help researchers address common issue of contamination in microbial studies. Well aware MiSeq decontamination program.
Proper citation: SCRuB (RRID:SCR_023518) Copy
https://github.com/genome/bam-readcount
Software tool that runs on BAM or CRAM file and generates low level information about sequencing data at specific nucleotide positions. Its outputs include observed bases, readcounts, summarized mapping and base qualities, strandedness information, mismatch counts, and position within the reads.
Proper citation: bam readcount (RRID:SCR_023653) Copy
http://www.stanford.edu/group/exonarray/cgi-bin/plot_selector.pl
Transcriptome database of acutely isolated purified astrocytes, neurons, and oligodendrocytes. Provides improved cell-type-specific markers for better understanding of neural development, function, and disease.
Proper citation: Exon Array Browser (RRID:SCR_008712) Copy
http://www.rhesusbase.org/drugDisc/CAM.jsp
OKCAM (Ontology-based Knowledgebase for Cell Adhesion Molecules) is an online resource for human genes known or predicted to be related to the processes of cell adhesion. These genes include members of the cadherin, immunoglobulin/FibronectinIII (IgFn), integrin, neurexin, neuroligin, and catenin families. Totally 496 human CAM genes were compiled and annotated. We have mapped these genes onto a novel cell adhesion molecule ontology (CAMO) that provides a hierarchical description of cell adhesion molecules and their functions. It is intended to provide a means to facilitate better and better understanding of the global and specific properties of CAMs through their genomic features, regulatory modes, expression patterns and disease associations become clearer. You may browse by CAM ontology, Chromosomes and Full Gene list.
Proper citation: OKCAM: Ontology-based Knowledgebase for Cell Adhesion Molecules (RRID:SCR_010696) Copy
https://genome-cancer.ucsc.edu/
A suite of web-based tools to visualize, integrate and analyze cancer genomics and its associated clinical data. It is possible to display your own clinical data within one of their datasets.
Proper citation: UCSC Cancer Genomics Browser (RRID:SCR_011796) Copy
A web-based application designed with an easy-to-use interface to facilitate the high-throughput assessment and prioritization of genes and missense alterations important for cancer tumorigenesis.
Proper citation: CRAVAT (RRID:SCR_012776) Copy
https://www.robotreviewer.net/
Software tool as machine learning system that automatically assesses bias in clinical trials. From PDF formatted trial report determines risks of bias for domains defined by Cochrane Risk of Bias (RoB) tool, and extracts supporting text for these judgments.
Proper citation: Robot Reviewer (RRID:SCR_018961) Copy
http://code.google.com/p/annotare/
A software tool for annotating biomedical investigations and the resulting data, then producing a MAGE-TAB file. This software is a standalone desktop which features: an editor function, an annotation modifier, incorporation of terms from biomedical ontologies, standard templates for common experiment types, a design aid to help create a new document, and a validator that checks for syntactic and semantic violations.
Proper citation: Annotare (RRID:SCR_000319) Copy
http://bioconductor.org/packages/release/bioc/html/nondetects.html
Software R package to model and impute non-detects in results of qPCR experiments.Used to directly model non-detects as missing data.
Proper citation: nondetects (RRID:SCR_001702) Copy
http://www.pathology.med.ohio-state.edu/HTRN/apc/default.asp
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The Adenoma Polyp Tissue Bank (APTB) receives whole blood from patients enrolled in the Prevention of Sporadic Colorectal Adenomas with Celecoxib clinical trial. We have reached our accrual on blood submissions, so we will no longer be receiving blood specimens The objectives of this trial are as follows: A. To determine the efficacy and safety of celecoxib versus placebo in preventing the occurrence of newly detected colorectal adenomas in subjects at increased risk for colorectal carcinoma. In addition to incidence, other established risk factors will be evaluated for their association with occurrence of new colorectal adenomas, including cancer family history and adenoma size, histopathologic grade, multiplicity and location. Primary assessment of treatment efficacy will be the reduction in the number of subjects with adenomas at colonoscopy after Year 1 and Year 3 of study drug use. Secondary assessments of treatment efficacy will be 1) the number of adenomas 2) the histopathologic grade of adenomas and 3) the size of adenomas, also measured after one year and three years of study drug use. These factors will be incorporated into a risk model for predicting adenoma occurrence and response to celecoxib. B. To determine the efficacy of celecoxib versus placebo in modulating one or more of a panel of biomarkers for colorectal cancer at the cellular and molecular level sampled in a subset of subjects at selective sites at baseline and after Year 1 and Year 3 of study drug use. These biomarkers will include measurements of aberrant crypt foci (ACF), proliferation (index and crypt distribution), apoptosis (index and crypt distribution), COX expression and activity. If modulation of one or more mucosal biomarkers occur, we will explore whether it correlates with the development of incident colorectal neoplasia (adenomas/carcinomas), thereby attempting to validate the surrogacy of that biomarker. C. To develop a specimen bank. Serum and white blood cells are isolated from whole blood and adenoma tissue blocks and slides are banked. Banked specimens will become available for use in correlative science studies at a later point. This project began in 1999 and will be extended through 2006. The lead principal investigator is Monica M. Bertagnolli, MD, Brigham and Women''s Hospital, Boston, MA, and the APTB Director is Scott Jewell, Ph.D., Department of Pathology, The Ohio State University. The APTB is supported by the NIH, NCI Division of Cancer Prevention, in connection with the Strang Cancer Prevention Center, Cornell University, New York., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Adenoma Polyp Tissue Bank (RRID:SCR_005366) Copy
https://www.sbpdiscovery.org/biomedical-research/shared-resources/cancer-metabolism
Facility that aims to investigate role of metabolism in cancer on cellular and organismal level, combining in vitro and in vivo analysis. Comprehensive metabolic facility, including stable isotope tracing and flux analysis. Provides analysis of metabolism using specialist instruments and methodologies, together with advice on planning experiments and analyzing data. All instruments and approaches are available on fee-for-service basis to Cancer Center scientists, but alsoto outside users. Samples for most services can be shipped, but Seahorse analyzer users need to be local so they can bring live cells for analysis.
Proper citation: Sanford Burnham Prebys Medical Discovery Institute Cancer Metabolism Core Facility (RRID:SCR_014873) Copy
http://www.salk.edu/science/core-facilities/integrative-genomics-and-bioinformatics-core/
Core facility established to assist the Salk community with integrating genomics data into their research. The primary focus of the core is to provide analysis support for next-generation sequencing applications.
Proper citation: Salk Institute Razavi Newman Integrative Genomics and Bioinformatics Core Facility (IGC) (RRID:SCR_014842) Copy
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