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https://github.com/dviraran/xCell

Software R package for generating cell type scores and R scripts for development of xCell. Web tool that performs cell type enrichment analysis from gene expression data for immune and stroma cell types. Used for Cell types enrichment analysis.

Proper citation: xCell (RRID:SCR_026446) Copy   

•   Source: SciCrunch Registry

https://pathoman.mskcc.org/

Web application to automate germline genomic variant curation from clinical sequencing based on ACMG guidelines. Aggregates multiple tracks of genomic, protein and disease specific information from public sources.

Proper citation: PathoMAN (RRID:SCR_026552) Copy   

•   Source: SciCrunch Registry

https://github.com/QuackenbushLab/NetworkDataCompanion

Software R library of utilities for performing analyses on TCGA and GTEx data using the Network Zoo. Streamlines routine steps in TCGA data processing, including filtering and mapping gene and sample identifiers between modalities and allows modality-specific data transformation, such as normalization and cleaning.

Proper citation: NetworkDataCompanion (RRID:SCR_026532) Copy   

•   Source: SciCrunch Registry

https://ibeximagingcommunity.github.io/ibex_imaging_knowledge_base/

Open, global repository as central resource for reagents, protocols, panels, publications, software, and datasets. In addition to IBEX, we support standard, single cycle multiplexed imaging (Multiplexed 2D imaging), volume imaging of cleared tissues with clearing enhanced 3D (Ce3D), highly multiplexed 3D imaging (Ce3D-IBEX), and extension of the IBEX dye inactivation protocol to the Leica Cell DIVE (Cell DIVE-IBEX). Committed to sharing knowledge related to multiplexed imaging. Antibody validation community knowledgebase.

Proper citation: IBEX Knowledge Base (RRID:SCR_025296) Copy   

•   Source: SciCrunch Registry

https://github.com/GregorySchwartz/too-many-cells

Software suite of tools, algorithms, and visualizations focusing on relationships between cell clades. This includes new ways of clustering, plotting, choosing differential expression comparisons. Identifies and visualizes relationships of single-cell clades.

Proper citation: TooManyCells (RRID:SCR_025328) 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

https://discover.nci.nih.gov/rsconnect/cellminercdb/

Web application integrating cancer cell line pharmacogenomics. Enables exploration and analysis of cancer cell line pharmacogenomic data across different sources. Focuses on cancer patient-derived human cell line molecular and pharmacological data. CellMinerCDB (v1.2) includes several improvements.

Proper citation: CellMinerCDB (RRID:SCR_025649) Copy   

•   Source: SciCrunch Registry

https://www.borch.dev/uploads/screpertoire/

Software R toolkit for analyzing single-cell immune repertoire profiling. Used for single-cell immune receptor analysis.

Proper citation: scRepertoire (RRID:SCR_025691) Copy   

•   Source: SciCrunch Registry

https://ctl.cornell.edu/industry/mrdetect-license-request/

Software application to estimate presence of MRD in plasma cfDNA WGS through evaluation of matched tumour-derived mutations (SNVs or CNVs).

Proper citation: MRDetect (RRID:SCR_024766) Copy   

•   Source: SciCrunch Registry

https://www.minerva.im/

Software tools for interactive viewing and fast sharing of large image data. Comprises Minerva Author, a tool to create and annotate images, and Minerva Story, a narrative image viewer for web hosting. Used for interpreting and interacting with complex images, organized around guided analysis approach. Enables fast sharing of large image data that is stored on Amazon S3 and viewed using zoomable image viewer implemented using OpenSeadragon, making it ideal for integration into multi-omic browsers for data dissemination of tissue atlases.

Proper citation: Minerva (RRID:SCR_024750) Copy   

•   Source: SciCrunch Registry

https://scimap.xyz

Software toolkit for analyzing spatial molecular data. Underlying framework is generalizable to spatial datasets mapped to XY coordinates. Package uses anndata framework making it easy to integrate with other popular single-cell analysis toolkits. It includes preprocessing, phenotyping, visualization, clustering, spatial analysis and differential spatial testing. Python based implementation efficiently deals with large datasets of millions of cells.

Proper citation: scimap (RRID:SCR_024751) Copy   

•   Source: SciCrunch Registry

https://reprint-apms.org/?q=chooseworkflow

Database of Mass Spectrometry contaminants and pipeline for Affinity Purification coupled with Mass Spectrometry analysis. Contaminant repository for affinity purification mass spectrometry data. Database of standardized negative controls. Used to identify protein-protein interactions.

Proper citation: CRAPome (RRID:SCR_025008) Copy   

•   Source: SciCrunch Registry

https://redu.ucsd.edu/

Software framework to find and re-analyze public Mass Spectrometry data. Used to find uniformly formatted public MS/MS data in the Global Natural Product Social Molecular Networking Platform (GNPS) via formatted metadata. New or previously collected data can be added provided they adhere to the ReDU metadata standards (the implemented drag-and-drop validator is applicable to any scientific data) and data are available in GNPS/MassIVE.

Proper citation: ReDU (RRID:SCR_025105) Copy   

•   Source: SciCrunch Registry

http://www.midasplatform.org/

Open-source toolkit that enables the rapid creation of tailored, web-enabled data storage and provides a cohesive system for data management, visualization, and processing. At its core, Midas Platform is implemented as a PHP modular framework with a backend database (PostGreSQL, MySQL and non-relational databases). While the Midas Platform system can be installed and deployed without any customization, the framework has been designed with customization in mind. As building one system to fit all is not optimal, the framework has been extended to support plugins and layouts. Through integration with a range of other open-source toolkits, applications, or internal proprietary workflows, Midas Platform offers a solid foundation to meet the needs of data-centric computing. Midas Platform provides a variety of data access methods, including web, file system and DICOM server interfaces, and facilitates extending the methods in which data is stored to other relational and non-relational databases.

Proper citation: Midas Platform (RRID:SCR_002186) Copy   

•   Source: SciCrunch Registry

http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

•   Source: SciCrunch Registry

https://lsom.uthscsa.edu/dcsa/research/cores-facilities/optical-imaging/

Service resource which makes imaging technology available to investigators on UTHSCSA campus and neighboring scientific community. Core Optical Imaging Facility offers access to technology for imaging of living cells, tissues, and animals, consultation, education and assistance regarding theory and application of optical imaging techniques, technical advice on specimen preparation techniques and probe selection.

Proper citation: Texas University Health Science Center at San Antonio Long School of Medicine Department of Cell Systems and Anatomy Optical Imaging Core Facility (RRID:SCR_012171) Copy   

•   Source: SciCrunch Registry

https://www.moffitt.org/research-science/shared-resources/tissue/

Biorepository resource with mission of proper collection, handling, processing and storage of irreplaceable biological specimens to support spectrum of related basic science, translational and clinical research. Provides expertise in nucleic acid extractions, quantification, aliquoting and quality assurance; liquid specimen centrifugation, processing and aliquoting; histological tissue processing, immunohistochemistry and tissue microarray microtomy; pathologist consultation services. Tissue Core operations are divided into four distinct pillars of service that work collaboratively to ensure specimen quality is maintained from procurement to preservation.

Proper citation: Moffitt Cancer Center Tissue Core Facility (RRID:SCR_012364) Copy   

•   Source: SciCrunch Registry

https://github.com/calico/borzoi

Software package to access the Borzoi models, which are convolutional neural networks trained to predict RNA-seq coverage at 32bp resolution given 524kb input sequences.

Proper citation: Borzoi (RRID:SCR_026619) Copy   

•   Source: SciCrunch Registry

https://petab.readthedocs.io/en/latest/

Repository contains PEtab specifications and additional documentation. Data format for specifying parameter estimation problems in systems biology. SBML and TSV based data format for parameter estimation problems in systems biology. Human- and computer- readable format for representing parameter estimation problems in systems biology.

Proper citation: PEtab (RRID:SCR_026915) Copy   

•   Source: SciCrunch Registry

https://github.com/AlexandrovLab/SigProfilerAssignment

Software tool for assignment of known mutational signatures to individual samples and individual somatic mutations.

Proper citation: SigProfilerAssignment (RRID:SCR_026899) Copy   

•   Source: SciCrunch Registry