Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications
doi: 10.1186/s13059-018-1406-4 , 10.1101/250126 , 10.5167/uzh-186233 , 10.60692/j84g0-fwq75 , 10.60692/dfz28-5df43
pmid: 29478411
pmc: PMC6251479
handle: 11577/3280604 , 1854/LU-8557546
doi: 10.1186/s13059-018-1406-4 , 10.1101/250126 , 10.5167/uzh-186233 , 10.60692/j84g0-fwq75 , 10.60692/dfz28-5df43
pmid: 29478411
pmc: PMC6251479
handle: 11577/3280604 , 1854/LU-8557546
Observation weights unlock bulk RNA-seq tools for zero inflation and single-cell applications
AbstractDropout events in single-cell transcriptome sequencing (scRNA-seq) cause many transcripts to go undetected and induce an excess of zero read counts, leading to power issues in differential expression (DE) analysis. This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. Recent evaluations, however, have shown that dedicated scRNA-seq tools provide no advantage compared to traditional bulk RNA-seq tools. We introduce a weighting strategy, based on a zero-inflated negative binomial (ZINB) model, that identifies excess zero counts and generates gene and cell-specific weights to unlock bulk RNA-seq DE pipelines for zero-inflated data, boosting performance for scRNA-seq.
- HUN-REN Research Centre for Natural Sciences Hungary
- PSL Research University France
- Ghent University Belgium
- Cornell University United States
- University of California, Berkeley United States
Cancer Research, sequence variation, Method, QH426-470, Gene, 1307 Cell Biology, Single-cell RNA sequencing, Computational biology, MAMMALIAN-CELLS, Droplet-based Sequencing, HETEROGENEITY, RNA-Seq, Biology (General), GENE-EXPRESSION, Lineage Tracking, Statistics, Life Sciences, Zero-inflated negative binomial, Biological Sciences, Comprehensive Integration of Single-Cell Transcriptomic Data, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 10124 Institute of Molecular Life Sciences, FOS: Philosophy, ethics and religion, sequence alignment, Single-Cell Analysis, Sequence Analysis, PACKAGE, 330, SEQUENCING DATA, Bioinformatics, QH301-705.5, Bioinformatics and Computational Biology, Differential expression; Single-cell RNA sequencing; Weights; Zero-inflated negative binomial;, Differential expression, 1311 Genetics, Weights, Information and Computing Sciences, Biochemistry, Genetics and Molecular Biology, FOS: Mathematics, Genetics, TRANSCRIPTOMICS, RNA Sequencing Data Analysis, Molecular Biology, Biology, Sequence Analysis, RNA, Gene Expression Profiling, Zero (linguistics), Biology and Life Sciences, Linguistics, Computer science, Genomic Landscape of Cancer and Mutational Signatures, Philosophy, 1105 Ecology, Evolution, Behavior and Systematics, DIFFERENTIAL EXPRESSION ANALYSIS, FOS: Biological sciences, FOS: Languages and literature, Poisson distribution, 570 Life sciences; biology, RNA, Negative binomial distribution, Gene expression, Transcriptome, Environmental Sciences, Software, Mathematics
Cancer Research, sequence variation, Method, QH426-470, Gene, 1307 Cell Biology, Single-cell RNA sequencing, Computational biology, MAMMALIAN-CELLS, Droplet-based Sequencing, HETEROGENEITY, RNA-Seq, Biology (General), GENE-EXPRESSION, Lineage Tracking, Statistics, Life Sciences, Zero-inflated negative binomial, Biological Sciences, Comprehensive Integration of Single-Cell Transcriptomic Data, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 10124 Institute of Molecular Life Sciences, FOS: Philosophy, ethics and religion, sequence alignment, Single-Cell Analysis, Sequence Analysis, PACKAGE, 330, SEQUENCING DATA, Bioinformatics, QH301-705.5, Bioinformatics and Computational Biology, Differential expression; Single-cell RNA sequencing; Weights; Zero-inflated negative binomial;, Differential expression, 1311 Genetics, Weights, Information and Computing Sciences, Biochemistry, Genetics and Molecular Biology, FOS: Mathematics, Genetics, TRANSCRIPTOMICS, RNA Sequencing Data Analysis, Molecular Biology, Biology, Sequence Analysis, RNA, Gene Expression Profiling, Zero (linguistics), Biology and Life Sciences, Linguistics, Computer science, Genomic Landscape of Cancer and Mutational Signatures, Philosophy, 1105 Ecology, Evolution, Behavior and Systematics, DIFFERENTIAL EXPRESSION ANALYSIS, FOS: Biological sciences, FOS: Languages and literature, Poisson distribution, 570 Life sciences; biology, RNA, Negative binomial distribution, Gene expression, Transcriptome, Environmental Sciences, Software, Mathematics
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