BMC Genomics · 2023 · 25 citations · 12 references
Life SciencesCell BiologyMolecular BiologyGene ExpressionGenomicsTranscriptomicsBulk Rna SequencingBulk TranscriptomicsDifferential Expression AnalysisDifferential Gene Expression AnalysisSingle-cell Rna Sequencing AnalysisSingle-cell TranscriptomicsBulk Rna Expression ProfilingBulk Rna Sequencing Differential ExpressionDifferential Transcript ExpressionInduced Pluripotent Stem CellsRna Sequencing (Rna-seq)Single-cell Differential ExpressionSingle-cell Differential Expression AnalysisSingle-cell Rna Sequencing
BACKGROUND: A common feature of single-cell RNA-seq (scRNA-seq) data is that the number of cells in a cell cluster may vary widely, ranging from a few dozen to several thousand. It is not clear whether scRNA-seq data from a small number of cells allow robust identification of differentially expressed genes (DEGs) with various characteristics. RESULTS: We addressed this question by performing scRNA-seq and poly(A)-dependent bulk RNA-seq in comparable aliquots of human induced pluripotent stem cells-derived, purified vascular endothelial and smooth muscle cells. We found that scRNA-seq data needed to have 2,000 or more cells in a cluster to identify the majority of DEGs that would show modest differences in a bulk RNA-seq analysis. On the other hand, clusters with as few as 50-100 cells may be sufficient for identifying the majority of DEGs that would have extremely small p values or transcript abundance greater than a few hundred transcripts per million in a bulk RNA-seq analysis. CONCLUSION: Findings of the current study provide a quantitative reference for designing studies that aim for identifying DEGs for specific cell clusters using scRNA-seq data and for interpreting results of such studies.
12
STAR: ultrafast universal RNA-seq aligner
Alexander Dobin, Carrie Davis, Felix Schlesinger et al. · Bioinformatics · 2012 · 56.2K citations · Full text
Matplotlib: A 2D Graphics Environment
John D. Hunter · Computing in Science & Engineering · 2007 · 39.6K citations
HTSeq—a Python framework to work with high-throughput sequencing data
Simon Anders, Paul Theodor Pyl, Wolfgang Huber · Bioinformatics · 2014 · 22.7K citations · Full text
Integrated analysis of multimodal single-cell data
Yuhan Hao, Stephanie Hao, Erica Andersen‐Nissen et al. · Cell · 2021 · 16K citations · Full text