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Mining single-cell data for cell type-disease associations

Authors: Chen, Kevin;

Mining single-cell data for cell type-disease associations

Abstract

Supplementary Data, including code and tables, used in the manuscript. Supplementary Figures S1-S4: Time course plots for each dataset S5-S8: Drug target classification for selected HPO terms in each dataset Code Input processing for each dataset Generic-CountsToSeurat.R - code for applying sctransform framework to generate Seurat object from counts matrices and metadata EWCE EWCE1-PrepareEWCEInputs.R - code for producing intermediate outputs from Seurat object EWCE2-PerformEWCEEnrichments.R - code for using intermediate outputs to generate enrichments via EWCE hdWGCNA (Gene co-expression analysis) hdWGCNA1-CountsToSeurat.R - code for preparing counts matrices and metadata into Seurat object for use in hdWGCNA hdWGCNA2-SeuratTohdWGCNA.R - code for generating co-expression modules from input Seurat object hdWGCNA3-hdWGCNAEnrichments.R - code for enriching co-expression modules for HPO terms hdWGCNA4-ModuleCellTypeAssociations.R - code for associating co-expression modules with cell types TCseq (Temporal clustering analysis) TCseq1-SeuratToTimeClusters.R - code for constructing temporal clusters from input Seurat object, and performing HPO enrichments on the clusters TCseq2-CombineEnrichments.R - code for collating enrichment results into a single csv file Drug target analysis DrugTargets1-GetOpenTargetsData.py - code for extracting target/disease associations from OpenTargets data DrugTargets2-CoexpressionModule_DrugTarget_Overlap.R - code for determining the distribution of drug targets across co-expression modules DrugTargets3- code for determining if drug targets were found in co-expression modules, as well as if they were in the HPO gene list Supplementary Tables Table descriptions are included in the Excel file.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average