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Clustering-independent estimation of cell abundances in bulk tissues using single-cell RNA-seq data

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.02.06.527318Source: DataRank Database

Clustering-independent estimation of cell abundances in bulk tissues using single-cell RNA-seq data is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 2 times.

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Enrichment:Funding (2 grants)OA: greenTopics (29)IDs (PubMed, OpenAlex)

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Authors (6)

Javier Montelongo ORCID,Robert Hu ORCID,Elijah Gunther ORCID,Patrick Nicodemus,Pablo G. Cámara ORCID

Live enrichment

PubMed:36798206 OpenAlex:https://openalex.org/W4319344625

National Institutes of Health

Grant: 1U01CA269409-01A1

A data-driven bioinformatics platform for the design and analysis of multiplexed antibody-based cytometry experiments in cancer research

National Institutes of Health

Grant: 1R25HG010323-01A1

Diversity Action Plan at the University of Pennsylvania (Penn) Genomics Program (DAPPG)

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/02/07/2023.02.06.527318.full.pdf

repositoryhttps://doi.org/10.1101/2023.02.06.527318

repositoryhttps://pubmed.ncbi.nlm.nih.gov/36798206

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/9934539

Fields of Study

Single-cell and spatial transcriptomicsExtracellular vesicles in diseaseImmune cells in cancer0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Cluster analysisEstimationComputer scienceCellRNA-SeqComputational biologyRNAData miningBiologyArtificial intelligenceGeneticsGene expressionTranscriptomeGeneEngineeringSequence Analysis, RNAGene Expression ProfilingArticleSingle-Cell Gene Expression AnalysisEpendymomaHumansMicrogliaSingle-Cell Analysis