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https://cumulus.readthedocs.io/en/stable

Software tool as cloud based single cell genomics and spatial transcriptomics data analysis framework that is scalable to massive amounts of data and able to process variety of data types. Consists of cloud analysis workflow, Python analysis package and visualization application. Supports analysis of single-cell RNA-seq, CITE-seq, Perturb-seq, single-cell ATAC-seq, single-cell immune repertoire and spatial transcriptomics data.

Proper citation: Cumulus (RRID:SCR_021644) Copy   

•   Source: SciCrunch Registry

https://github.com/kukionfr/VAMPIRE_open

Software tool for analysis of cell and nuclear morphology from fluorescence or bright field images. Enables profiling and classification of cells into shape modes based on equidistant points along cell and nuclear contours. Robust method to quantify cell morphological heterogeneity.

Proper citation: VAMPIRE (RRID:SCR_021721) Copy   

•   Source: SciCrunch Registry

https://github.com/vlink/marge

Software package that integrates genome wide genetic variation with epigenetic data to identify collaborative transcription factor pairs. Optimized to work with chromatin accessibility assays such as ATAC-seq or DNase I hypersensitivity, as well as transcription factor binding data collected by ChIP-seq. Used to identify combinations of cell type specific transcription factors while simultaneously interpreting functional effects of non-coding genetic variation.

Proper citation: Motif Mutation Analysis for Regulatory Genomic Elements (RRID:SCR_021902) Copy   

•   Source: SciCrunch Registry

https://github.com/QTIM-Lab/DeepNeuro

Software Python package for neuroimaging data. Framework to design and train neural network architectures. Used in medical imaging community to ensure consistent performance of networks across variable users, institutions, and scanners.

Proper citation: DeepNeuro (RRID:SCR_016911) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://www.med.upenn.edu/cbica/captk/

Software platform for analysis of radiographic cancer images. Used as quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

Proper citation: Cancer Imaging Phenomics Toolkit (RRID:SCR_017323) Copy   

•   Source: SciCrunch Registry

https://github.com/caleblareau/mgatk

Software python-based command line interface for processing .bam files with mitochondrial reads and generating high-quality heteroplasmy estimation from sequencing data. This package places a special emphasis on mitochondrial genotypes generated from single-cell genomics data, primarily mtscATAC-seq, but is generally applicable across other assays.

Proper citation: mgatk (RRID:SCR_021159) Copy   

•   Source: SciCrunch Registry

https://github.com/humanlongevity/HLA

Software tool for fast and accurate HLA typing from short read sequence data. Iteratively refines mapping results at amino acid level to achieve four digit typing accuracy for both class I and II HLA genes, taking only 3 min to process 30× whole genome BAM file on desktop computer.

Proper citation: xHLA (RRID:SCR_022277) Copy   

•   Source: SciCrunch Registry

https://github.com/RabadanLab/arcasHLA

Software tool for high resolution HLA typing from RNAseq. Fast and accurate in silico inference of HLA genotypes from RNA-seq.

Proper citation: arcasHLA (RRID:SCR_022286) Copy   

•   Source: SciCrunch Registry

https://ccsp.hms.harvard.edu/

Center includes studies for responsiveness and resistance to anti cancer drugs. Committed to training students and postdocs, promoting junior faculty and ensuring that data and software are reproducible, reliable and publicly accessible. Member of National Cancer Institute’s Cancer Systems Biology Consortium.

Proper citation: Harvard Medical School Center for Cancer Systems Pharmacology (RRID:SCR_022831) Copy   

•   Source: SciCrunch Registry

https://weghornlab.org/software.html

Software tool which derives gene-specific probabilistic estimates of the strength of negative and positive selection in cancer.

Proper citation: CBaSE (RRID:SCR_027765) Copy   

•   Source: SciCrunch Registry

https://github.com/McGranahanLab/TcellExTRECT

Software R package to calculate T cell fractions from WES data from hg19 or hg38 aligned genomes.

Proper citation: T Cell ExTRECT (RRID:SCR_027742) Copy   

•   Source: SciCrunch Registry

https://github.com/vanallenlab/comut

Software Python library for creating comutation plots to visualize genomic and phenotypic information. Used for visualizing genomic and phenotypic information via comutation plots.

Proper citation: CoMUT (RRID:SCR_027745) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/sivic/

Software framework and application suite for processing and visualization of DICOM MR Spectroscopy data. Through the use of DICOM, SIVIC aims to facilitate the application of MRS in medical imaging studies.

Proper citation: Spectroscopic Imaging, VIsualization, and Computing (SIVIC) (RRID:SCR_027875) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/tximeta.html

Software R package for reference sequence checksums for provenance identification in RNA-seq. Performs numerous annotation and metadata gathering tasks on behalf of users during the import of transcript counts and abundance from quantification tools such as salmon. Data are imported as SummarizedExperiment objects with associated GenomicRanges metadata. Correct metadata is added automatically via reference sequence digests, facilitating genomic analyses and assisting in computational reproducibility.

Proper citation: tximeta (RRID:SCR_028005) Copy   

•   Source: SciCrunch Registry

https://github.com/SalasLab/HiTIMED

Software DNA methylation-based algorithm, to estimate cell proportions in tumor microenvironment. Profiles tumor, immune, and angiogenic components, allowing researchers to study tumor composition and its clinical implications using archival biospecimens.

Proper citation: HiTIMED (RRID:SCR_028180) Copy   

•   Source: SciCrunch Registry

https://github.com/brentp/somalier

Software application for rapid relatedness estimation for cancer and germline studies using efficient genome sketches extract informative sites, evaluate relatedness, and perform quality-control on BAM/CRAM/BCF/VCF/GVCF. Used for rapid relatedness estimation for cancer and germline studies using efficient genome sketches.

Proper citation: somalier (RRID:SCR_028167) Copy   

•   Source: SciCrunch Registry

https://oncodb.org/

Database offers integrated multi-omic data for patients across 33 cancer types. It encompasses gene expression, DNA methylation, somatic mutations, proteomic profiles, and chromatin accessibility, drawing from TCGA, GTEx, and CPTAC projects. Users can compare gene expression, DNA methylation, and protein levels between tumor and normal tissues, identifying differentially expressed genes and proteins, and examining gene-to-gene correlations. Provides oncogene mutation profiles and allows for survival analysis based on gene expression and methylation, linked to clinical parameters. Facilitates exploration of multi-omic correlations, such as gene expression with DNA methylation, and their variations with mutation status. Extends its analytical capabilities to include six major oncoviruses, offering insights into their impact on gene expression, methylation, and patient survival.

Proper citation: OncoDB (RRID:SCR_028340) Copy   

•   Source: SciCrunch Registry