Comparison and evaluation of statistical error models for scRNA-seq
S Choudhary, R Satija - Genome biology, 2022 - Springer
Background Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple
sources, including biological variation in cellular state as well as technical variation …
sources, including biological variation in cellular state as well as technical variation …
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
In comparative high-throughput sequencing assays, a fundamental task is the analysis of
count data, such as read counts per gene in RNA-seq, for evidence of systematic changes …
count data, such as read counts per gene in RNA-seq, for evidence of systematic changes …
Waste not, want not: why rarefying microbiome data is inadmissible
PJ McMurdie, S Holmes - PLoS computational biology, 2014 - journals.plos.org
Current practice in the normalization of microbiome count data is inefficient in the statistical
sense. For apparently historical reasons, the common approach is either to use simple …
sense. For apparently historical reasons, the common approach is either to use simple …
voom: Precision weights unlock linear model analysis tools for RNA-seq read counts
New normal linear modeling strategies are presented for analyzing read counts from RNA-
seq experiments. The voom method estimates the mean-variance relationship of the log …
seq experiments. The voom method estimates the mean-variance relationship of the log …
Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation
A flexible statistical framework is developed for the analysis of read counts from RNA-Seq
gene expression studies. It provides the ability to analyse complex experiments involving …
gene expression studies. It provides the ability to analyse complex experiments involving …
Count-based differential expression analysis of RNA sequencing data using R and Bioconductor
RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in
many areas of biology, including studies into gene regulation, development and disease. Of …
many areas of biology, including studies into gene regulation, development and disease. Of …
A comparison of methods for differential expression analysis of RNA-seq data
C Soneson, M Delorenzi - BMC bioinformatics, 2013 - Springer
Background Finding genes that are differentially expressed between conditions is an
integral part of understanding the molecular basis of phenotypic variation. In the past …
integral part of understanding the molecular basis of phenotypic variation. In the past …
EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments
N Leng, JA Dawson, JA Thomson, V Ruotti… - …, 2013 - academic.oup.com
Motivation: Messenger RNA expression is important in normal development and
differentiation, as well as in manifestation of disease. RNA-seq experiments allow for the …
differentiation, as well as in manifestation of disease. RNA-seq experiments allow for the …
Statistical analysis of microbiome data: the challenge of sparsity
AY Pan - Current Opinion in Endocrine and Metabolic Research, 2021 - Elsevier
Microbiomes not only exist across many different body sites in human beings but also
interact dynamically with the host and environment. The unique feature and complexity of …
interact dynamically with the host and environment. The unique feature and complexity of …
Statistical and bioinformatics analysis of data from bulk and single-cell RNA sequencing experiments
X Yu, F Abbas-Aghababazadeh, YA Chen… - Translational …, 2021 - Springer
High-throughput sequencing (HTS) has revolutionized researchers' ability to study the
human transcriptome, particularly as it relates to cancer. Recently, HTS technology has …
human transcriptome, particularly as it relates to cancer. Recently, HTS technology has …