iDEP – an integrated web application for differential expression and pathway analysis of RNA-Seq data

January 31, 2019 Leave a comment 5,951 Views

RNA-seq is widely used for transcriptomic profiling, but the bioinformatics analysis of resultant data can be time-consuming and challenging, especially for biologists. Researchers at South Dakota State University...

A mew machine learning-based framework for mapping uncertainty analysis in RNA-Seq read alignment and gene expression estimation

August 31, 2018 Leave a comment 4,480 Views

One of the main benefits of using modern RNA-Sequencing (RNA-Seq) technology is the more accurate gene expression estimations compared with previous generations of expression data, such as the microarray. However, numerous issues can result...

Interpretation of differential gene expression results of RNA-seq data

August 15, 2018 Leave a comment 9,393 Views

Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many...

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Tag Archives: South Dakota State University

iDEP – an integrated web application for differential expression and pathway analysis of RNA-Seq data

A mew machine learning-based framework for mapping uncertainty analysis in RNA-Seq read alignment and gene expression estimation

Interpretation of differential gene expression results of RNA-seq data

circFL-seq – identification and quantification of full-length circRNAs for large-scale screening of functional circRNAs

Performances of targeted RNA sequencing for the analysis of fusion transcripts, gene mutation, and expression

RNA sequencing study receives Creative Representations of Research Impact Award

Two cancer research studies demonstrate use of RNA sequencing for precision oncology

Automated annotation of rare-cell types from single-cell RNA-sequencing data through synthetic oversampling

RNA Sequencing reveals mechanisms of large exon splicing during vertebrate evolution

Computational merging of large single-cell RNA sequencing datasets paints a transcriptomic picture of muscle repair