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RNA-Seq Blog Transcriptome Research & Industry News

Statistical Analysis

TWO-SIGMA-G – a new competitive gene set testing framework for scRNA-seq data accounting for inter-gene and cell–cell correlation

Researchers at Harvard T.H. Chan School of Public Health and the University of North Carolina at Cha...
Benchmarking of a Bayesian single cell RNAseq differential gene expression test for dose–response study designs

The application of single-cell RNA sequencing (scRNAseq) for the evaluation of chemicals, drugs, and...
Representation learning of RNA velocity reveals robust cell transitions

RNA velocity is a promising technique for quantifying cellular transitions from single-cell transcri...
Isoform variability is an important source of latent information in RNA-seq data that can be used to improve clinical prediction models.

Most predictive models based on gene expression data do not leverage information related to gene spl...
Powerful eQTL mapping through low coverage RNA sequencing

Mapping genetic variants that regulate gene expression (eQTLs) in large-scale RNA sequencing (RNA-se...

RNA-seq: Impact of RNA degradation on transcript quantification

May 30, 2014 Leave a comment 6,502 Views

The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be corrected via data normalization, ...

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RNA-Seq Blog Transcriptome Research & Industry News

Statistical Analysis

TWO-SIGMA-G – a new competitive gene set testing framework for scRNA-seq data accounting for inter-gene and cell–cell correlation

Benchmarking of a Bayesian single cell RNAseq differential gene expression test for dose–response study designs

Representation learning of RNA velocity reveals robust cell transitions

Isoform variability is an important source of latent information in RNA-seq data that can be used to improve clinical prediction models.

Powerful eQTL mapping through low coverage RNA sequencing

RNA-seq: Impact of RNA degradation on transcript quantification

NEW Illumina Cancer Research Methods Guide – Download now!

viRNAtrap – a package to generate predicted viral contigs from unmapped RNA-seq reads

Featured RNA-Seq Job – Senior Research Scientist, Technology Development

Researchers develop online portal to show how biases in RNA sequences affect gene expression

Transcriptional recording enables noninvasive measurement of the intestinal tract with potential for biomedical research and future biomedical diagnostic applications

ActiveSVM – single-cell mRNA-seq data analysis with a minimal number of genes

scRNA-Seq draws a a roadmap to future personalized medicine for heart defects that develop before birth