عنوان

Statistical and computational methods for single-cell transcriptome sequencing and metagenomics

Number

TL9qb8c96h

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Statistical and computational methods for single-cell transcriptome sequencing and metagenomics

General Material Designation

[Thesis]

First Statement of Responsibility

Perraudeau, Fanny

Subsequent Statement of Responsibility

Dudoit, Sandrine

Date of Publication, Distribution, etc.

2018

Body granting the degree

Dudoit, Sandrine

Text preceding or following the note

2018

Text of Note

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.

Perraudeau, Fanny

Perraudeau, Fanny

UC Berkeley

Electronic name

p

[Thesis]

276903

a

Y