We develop methods to filter genes for reliable quantification and to calibrate biological variation. ![]() We find that transcriptomes differ globally across tissues with regard to the number of genes expressed, the average expression patterns, and within-cell-type variation patterns. We present high quality deep read-depth single-cell RNA sequencing for 91 cells from five mouse tissues and 18 cells from two rat tissues, along with 30 control samples of bulk RNA diluted to single-cell levels. Additionally, single-cell transcriptomics presents unique analysis challenges that need to be addressed to answer this question. ![]() This brings into question the relationship between transcriptome states and cell phenotypes. Differentiation of metazoan cells requires execution of different gene expression programs but recent single-cell transcriptome profiling has revealed considerable variation within cells of seeming identical phenotype.
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