Differential expression analysis of single-cell rna-seq data: current statistical approaches and outstanding challenges
With the advent of single-cell RNA-sequencing (scRNA-seq), it is possible to measure the
expression dynamics of genes at the single-cell level. Through scRNA-seq, a huge amount …
expression dynamics of genes at the single-cell level. Through scRNA-seq, a huge amount …
A comprehensive survey of statistical approaches for differential expression analysis in single-cell RNA sequencing studies
Single-cell RNA-sequencing (scRNA-seq) is a recent high-throughput sequencing
technique for studying gene expressions at the cell level. Differential Expression (DE) …
technique for studying gene expressions at the cell level. Differential Expression (DE) …
Fifteen years of gene set analysis for high-throughput genomic data: a review of statistical approaches and future challenges
Over the last decade, gene set analysis has become the first choice for gaining insights into
underlying complex biology of diseases through gene expression and gene association …
underlying complex biology of diseases through gene expression and gene association …
Multigroup prediction in lung cancer patients and comparative controls using signature of volatile organic compounds in breath samples
Early detection of lung cancer is a crucial factor for increasing its survival rates among the
detected patients. The presence of carbonyl volatile organic compounds (VOCs) in exhaled …
detected patients. The presence of carbonyl volatile organic compounds (VOCs) in exhaled …
A framework for comparison and assessment of synthetic RNA-seq data
F Shakola, D Palejev, I Ivanov - Genes, 2022 - mdpi.com
The ever-growing number of methods for the generation of synthetic bulk and single cell
RNA-seq data have multiple and diverse applications. They are often aimed at …
RNA-seq data have multiple and diverse applications. They are often aimed at …
Gene selection for microarray data classification via adaptive hypergraph embedded dictionary learning
Due to the rapid development of DNA microarray technology, a large number of microarray
data come into being and classifying these data has been verified useful for cancer …
data come into being and classifying these data has been verified useful for cancer …
Statistical approach for biologically relevant gene selection from high-throughput gene expression data
Selection of biologically relevant genes from high-dimensional expression data is a key
research problem in gene expression genomics. Most of the available gene selection …
research problem in gene expression genomics. Most of the available gene selection …
FMDVSerPred: A novel computational solution for foot-and-mouth disease virus classification and serotype prediction prevalent in Asia using VP1 nucleotide …
Background: Three serotypes of Foot-and-mouth disease (FMD) virus have been circulating
in Asia, which are commonly identified by serological assays. Such tests are timeconsuming …
in Asia, which are commonly identified by serological assays. Such tests are timeconsuming …
Five years of gene networks modeling in single-cell RNA-sequencing studies: current approaches and outstanding challenges
Single-cell RNA-sequencing (scRNA-seq) is a rapidly growing field in transcriptomics, which
generates a tremendous amount of gene expression data at the single-cell level. Improved …
generates a tremendous amount of gene expression data at the single-cell level. Improved …
Single-cell transcriptomics: background, technologies, applications, and challenges
L Duhan, D Kumari, M Naime, VS Parmar… - Molecular Biology …, 2024 - Springer
Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and
transient cell states that are barely visible in the bulk. This technology reveals the …
transient cell states that are barely visible in the bulk. This technology reveals the …