Determining sequencing depth in a single-cell RNA-seq experiment
Martin Jinye Zhang, Vasilis Ntranos, David Tse
Abstract
An underlying question for virtually all single-cell RNA sequencing experiments is how to allocate the limited sequencing budget: deep sequencing of a few cells or shallow sequencing of many cells? Here we present a mathematical framework which reveals that, for estimating many important gene properties, the optimal allocation is to sequence at a depth of around one read per cell per gene. Interestingly, the corresponding optimal estimator is not the widely-used plug-in estimator, but one developed via empirical Bayes.
Topics & Concepts
Single cell sequencingComputational biologyRNA-SeqBayes' theoremEstimatorDeep sequencingDNA sequencingComputer scienceSequence (biology)BiologyRNAGeneBayesian probabilityGeneticsArtificial intelligenceGene expressionMathematicsStatisticsTranscriptomeGenomeMutationExome sequencingSingle-cell and spatial transcriptomicsCancer Genomics and DiagnosticsExtracellular vesicles in disease