Statistical and Computational Methods for Single-cell Transcriptome Sequencing and Metagenomics PDF Download

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Statistical and Computational Methods for Single-cell Transcriptome Sequencing and Metagenomics

Statistical and Computational Methods for Single-cell Transcriptome Sequencing and Metagenomics PDF Author: Fanny Perraudeau
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Languages : en
Pages : 246

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Book Description
I propose statistical methods and software for the analysis of single-cell transcriptome sequencing (scRNA-seq) and metagenomics data. Specifically, I present a general and flexible zero-inflated negative binomial-based wanted variation extraction (ZINB-WaVE) method, which extracts low-dimensional signal from scRNA-seq read counts, accounting for zero inflation (dropouts), over-dispersion, and the discrete nature of the data. Additionally, I introduce an application of the ZINB-WaVE method that identifies excess zero counts and generates gene and cell-specific weights to unlock bulk RNA-seq differential expression pipelines for zero-inflated data, boosting performance for scRNA-seq analysis. Finally, I present a method to estimate bacterial abundances in human metagenomes using full-length 16S sequencing reads.