Statistical and computational methods for single-cell transcriptome sequencing and metagenomics
نام عام مواد
[Thesis]
نام نخستين پديدآور
Perraudeau, Fanny
نام ساير پديدآوران
Dudoit, Sandrine
وضعیت نشر و پخش و غیره
تاریخ نشرو بخش و غیره
2018
یادداشتهای مربوط به پایان نامه ها
کسي که مدرک را اعطا کرده
Dudoit, Sandrine
امتياز متن
2018
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
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.
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )