Tag Archives: R package

Combining single-cell genomics and computational techniques, a research team including Paul Robson, Ph.D., director of single-cell biology at The Jackson Laboratory (JAX), has defined cell-type composition of cancerous cells from 11 colorectal tumors, as well as adjacent noncancerous cells, a ...

Simulations are essential to find the best compromise between statistical power and cost effectiveness, but also help with the interpretation of conducted RNA-seq experiments. For example, researchers often wonder why their results differ from previous studies, powsim helps here by ...

Several methods have been developed to identify differential correlation (DC) between pairs of molecular features from -omics studies. Most DC methods have only been tested with microarrays and other platforms producing continuous and Gaussian-like data. Sequencing data is in the ...

In gene set analysis, the researchers are interested in determining the gene sets that are significantly correlated with an outcome, e.g. disease status or treatment. With the rapid development of high throughput sequencing technologies, Ribonucleic acid sequencing (RNA-seq) has become ...

Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct ...

Perturbations in the environment lead to distinctive gene expression changes within a cell. Observed over time, those variations can be characterized by single impulse-like progression patterns. Researchers at the University of Bonn have developed ImpulseDE, an R package suited to ...

Although ultrahigh-throughput RNA-Sequencing has become the dominant technology for genome-wide transcriptional profiling, the vast majority of RNA-Seq studies typically profile only tens of samples, and most analytical pipelines are optimized for these smaller studies. However, projects are generating ever-larger data ...

Recent innovation of RNA-seq technology has shed insightful light on the transcriptomic evolution studies, especially on researches of tissue-specific expression evolution. Phylogenetic analysis of transcriptome data may help to identify causal gene expression differences underlying the evolutionary changes in morphological, ...

Determination of haplotypes is important for modelling the phenotypic consequences of genetic variation in diploid organisms, including cis-regulatory control and compound heterozygosity. Karolinska Institute researchers realized that single cell RNA-seq (scRNA-seq) data is well suited for phasing genetic variants, since ...

Data from RNA-seq experiments provide us with many new possibilities to gain insights into biological and disease mechanisms of cellular functioning. However, the reproducibility and robustness of RNA-seq data analysis results is often unclear. This is in part attributed to ...