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http://www.broadinstitute.org/
Biomedical and genomic research center located in Cambridge, Massachusetts, United States. Nonprofit research organization under the name Broad Institute Inc., and is partners with Massachusetts Institute of Technology, Harvard University, and the five Harvard teaching hospitals. Dedicated to advance understanding of biology and treatment of human disease to improve human health.
Proper citation: Broad Institute (RRID:SCR_007073) Copy
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
https://singlecell.broadinstitute.org/single_cell
Portal specializes in visualizing and disseminating single cell data. Allows you to use natural language and faceted search to discover other scientists’ research and share your own findings. Each study includes information on cell types, singular or multiple gene expression, and spatial transcriptomics. Interactive visualizations allow to explore cell clusters and search for related genes.
Proper citation: Single Cell Portal (RRID:SCR_014816) Copy
Software pipeline for single-nucleus RNAseq data generated by Smart-seq2 assays.Used to simultaneously process multiple libraries of single nuclei Smart-seq2 and Smart-seq4 data. For each library (nucleus), the pipeline trims paired FASTQ files, aligns trimmed reads to the genome, counts intronic and exonic reads, and calculates quality control metrics. Counts and metrics for all libraries are combined into merged Loom formatted count matrix.
Proper citation: Smart-seq2 Single Nucleus Multi Sample Pipeline (RRID:SCR_021312) Copy
https://pegasus.readthedocs.io/en/stable
Software package for massive single cell data processing. Enables analysis of million scale single cell RNA-seq data and is functionally comparable to Seurat and SCANPY. Command line tool, Python package and base for Cloud based analysis workflows. Supports variety of analysis tasks, such as cell and gene level quality control, highly variable gene selection, dimension reduction, kNN graph building, data integration, clustering, differential expression analysis and putative cell type annotation.
Proper citation: Pegasus (RRID:SCR_021645) Copy
https://app.terra.bio/#workspaces/pathogen-genomic-surveillance/COVID-19
Broad Terra cloud workspace for best practices with COVID-19 genomics data. Raw COVID-19 sequencing data from NCBI Sequence Read Archive. Workflows for genome assembly, quality control, metagenomic classification, and aggregate statistics.
Proper citation: Broad Terra cloud commons for pathogen surveillance (RRID:SCR_018278) Copy
https://broadinstitute.github.io/warp/docs/Pipelines/Single_Cell_ATAC_Seq_Pipeline/README
Pipeline developed in collaboration with Bing Ren lab and supports processing of BICCN single-cell/nucleus ATAC-seq datasets. Pipeline uses python module SnapTools to align and process paired reads in form of FASTQ files. Produces hdf5-structured Snap file that includes cell-by-bin count matrix. Final outputs also include GA4GH compliant aligned BAM and QC metrics.
Proper citation: scATAC Pipeline (RRID:SCR_018919) Copy
https://broadinstitute.github.io/warp/docs/Pipelines/CEMBA_MethylC_Seq_Pipeline/README
Software pipeline that supports processing of multiplexed single nuclei bisulfite sequencing data to detect methylated bases. Alignment and methylated base calling pipeline that trims adaptors, attaches cell barcodes, aligns reads to genome, filters reads based on quality and creates both VCF and ALLC file with Emethylation site coverage.
Proper citation: CEMBA MethylC Seq Pipeline (RRID:SCR_021219) Copy
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The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant U24DK097771.
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