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MCProj: metacell projection for interpretable and quantitative use of transcriptional atlases
by
Lifshitz, Aviezer
, Ben-Kiki, Oren
, Raz, Ofir
, Brook, Dror
, Tanay, Amos
, Bercovich, Akhiad
in
Algorithms
/ Animal Genetics and Genomics
/ Annotations
/ Bioinformatics
/ Biomedical and Life Sciences
/ blood
/ Cell cycle
/ data collection
/ Datasets
/ Evolutionary Biology
/ Gene expression
/ genes
/ Genomics
/ Human Genetics
/ Life Sciences
/ Method
/ Microbial Genetics and Genomics
/ Plant Genetics and Genomics
/ transcription (genetics)
2023
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MCProj: metacell projection for interpretable and quantitative use of transcriptional atlases
by
Lifshitz, Aviezer
, Ben-Kiki, Oren
, Raz, Ofir
, Brook, Dror
, Tanay, Amos
, Bercovich, Akhiad
in
Algorithms
/ Animal Genetics and Genomics
/ Annotations
/ Bioinformatics
/ Biomedical and Life Sciences
/ blood
/ Cell cycle
/ data collection
/ Datasets
/ Evolutionary Biology
/ Gene expression
/ genes
/ Genomics
/ Human Genetics
/ Life Sciences
/ Method
/ Microbial Genetics and Genomics
/ Plant Genetics and Genomics
/ transcription (genetics)
2023
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Do you wish to request the book?
MCProj: metacell projection for interpretable and quantitative use of transcriptional atlases
by
Lifshitz, Aviezer
, Ben-Kiki, Oren
, Raz, Ofir
, Brook, Dror
, Tanay, Amos
, Bercovich, Akhiad
in
Algorithms
/ Animal Genetics and Genomics
/ Annotations
/ Bioinformatics
/ Biomedical and Life Sciences
/ blood
/ Cell cycle
/ data collection
/ Datasets
/ Evolutionary Biology
/ Gene expression
/ genes
/ Genomics
/ Human Genetics
/ Life Sciences
/ Method
/ Microbial Genetics and Genomics
/ Plant Genetics and Genomics
/ transcription (genetics)
2023
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MCProj: metacell projection for interpretable and quantitative use of transcriptional atlases
Journal Article
MCProj: metacell projection for interpretable and quantitative use of transcriptional atlases
2023
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Overview
We describe MCProj—an algorithm for analyzing query scRNA-seq data by projections over reference single-cell atlases. We represent the reference as a manifold of annotated metacell gene expression distributions. We then interpret query metacells as mixtures of atlas distributions while correcting for technology-specific gene biases. This approach distinguishes and tags query cells that are consistent with atlas states from unobserved (novel or artifactual) behaviors. It also identifies expression differences observed in successfully mapped query states. We showcase MCProj functionality by projecting scRNA-seq data on a blood cell atlas, deriving precise, quantitative, and interpretable results across technologies and datasets.
Publisher
BioMed Central,Springer Nature B.V,BMC
Subject
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