cellhub

Cellhub provides an end-to-end scaleable workflow for the pre-processing, warehousing and analysis of data from millions of single-cells. It aims to bring together best practice solutions, including for read alignment (Cellranger), ambient RNA correction (CellBender), de-multiplexing and de-hashing (GMMDemux), cell type prediction (singleR) and cluster analysis (Scanpy) into a cohesive set of easy to use analysis pipelines. It relies on the cgat-core workflow management system to leverage the power of high-performance compute clusters for high-throughput parallel processing. Pipelines cross-talk via a defined API allowing for easy extension or modification of the workflow. Cells and their associated qc-statistics and metadata are indexed in a central SQLite database from which arbitrary subsets can be fetched for downstream analysis in anndata format. The clustering pipeline allows rapid evaluation of different pre-processing and integration strategies at different clustering resolutions, through generation of pdf reports and cellxgene objects.

Cellhub was originally developed to support the single-cell component of the University of Oxford’s COMBAT COVID-19 project.

Cellhub is currently alpha software. More detailed examples and tutorials will follow soon.

• Workflow Overview
  • Introduction
  • 1. Primary analysis
  • 2. Secondary analysis
  • 3. Loading results into the cell database
  • 4. Fetching of cells for downstream analysis
  • 5. Assessment of cell quality, pre-processing and integration
  • 6. Clustering analysis
• Installation
  • Dependencies
  • Installation
• Usage
  • Configuring and running pipelines
  • Getting Started
• Examples
  • IFNb PBMC example
• Pipelines
  • pipeline_adt_norm.py
  • gexdepth()
  • gexdepthAPI()
  • adtdepth()
  • adtdepthAPI()
  • adt_plot_norm()
  • dsb_norm()
  • dsbAPI()
  • median_norm()
  • medianAPI()
  • clr_norm()
  • clrAPI()
  • plot()
  • full()
  • pipeline_ambient_rna.py
  • ambient_rna_per_input()
  • ambient_rna_compare()
  • plot()
  • full()
  • pipeline_annotation.py
  • fetchEnsembl()
  • ensemblAPI()
  • fetchKegg()
  • keggAPI()
  • pipeline_cellbender.py
  • cellbender()
  • h5API()
  • mtx()
  • mtxAPI()
  • full()
  • useCounts()
  • pipeline_celldb.py
  • connect()
  • load_samples()
  • load_gex_qcmetrics()
  • load_gex_scrublet()
  • load_singleR()
  • load_gmm_demux()
  • load_demuxEM()
  • final()
  • pipeline_cellranger_multi.py
  • taskSummary()
  • config()
  • cellrangerMulti()
  • mtxAPI()
  • h5API()
  • postProcessVDJ()
  • vdjAPI()
  • full()
  • useCounts()
  • pipeline_cell_qc.py
  • qcmetrics()
  • qcmetricsAPI()
  • scrublet()
  • scrubletAPI()
  • plot()
  • full()
  • pipeline_cluster.py
  • taskSummary()
  • preflight()
  • metadata()
  • loom()
  • neighbourGraph()
  • scanpyCluster()
  • cluster()
  • compareClusters()
  • clustree()
  • paga()
  • UMAP()
  • plotRdimsFactors()
  • plotRdimsClusters()
  • plotRdimsSingleR()
  • plotSingleR()
  • summariseSingleR()
  • plotGroupNumbers()
  • clusterStats()
  • findMarkers()
  • summariseMarkers()
  • topMarkerHeatmap()
  • dePlots()
  • markerPlots()
  • plotMarkerNumbers()
  • markers()
  • parseGMTs()
  • genesetAnalysis()
  • summariseGenesetAnalysis()
  • genesets()
  • plots()
  • latexVars()
  • summaryReportSource()
  • summaryReport()
  • markerReportSource()
  • markerReport()
  • export()
  • report()
  • cellxgene()
  • pipeline_dehash.py
  • gmmDemux()
  • gmmAPI()
  • hashCountCSV()
  • demuxEM()
  • parseDemuxEM()
  • demuxemAPI()
  • pipeline_emptydrops.py
  • emptyDrops()
  • meanReads()
  • full()
  • pipeline_fetch_cells.py
  • fetchCells()
  • GEX()
  • ADT()
  • pipeline_singleR.py
  • genSingleRjobs()
  • singleR()
  • concatenate()
  • summary()
  • singleRAPI()
  • pipeline_velocyto.py
  • checkInputs()
  • genClusterJobs()
  • sortBam()
  • runVelocyto()
  • full()
• cellhub.tasks
  • parameters.py
  • write_config_files()
  • get_parameter_file()
  • setup.py
  • setup
  • api.py
  • api
  • profile.py
  • is_tool()
  • cellbender.py
  • anndata_from_h5()
  • dict_from_h5()
• Contributing
  • Repository layout
  • Style guide
  • Writing pipelines
  • Writing pipeline tasks
  • Cell indexing
  • Yaml configuration file naming
  • Compiling the documentation locally

Indices and tables

• Index

• Module Index

• Search Page