Expression and Quantification

Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes ...

RNA-seq techniques generate massive amounts of expression data. Several pipelines (e.g. Tophat and Cufflinks) are broadly applied to analyse these data sets. However, accessing and handling the analytical output remains challenging for non-experts. Researchers at the Helmholtz Center Munich now ...

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological ...

compcodeR is an R package for benchmarking of differential expression analysis methods, in particular methods developed for analyzing RNA-seq data. The package provides functionality for simulating realistic RNA-seq count data sets, an interface to several of the most commonly used ...

The main goal of the whole transcriptome analysis is to correctly identify all expressed transcripts within a specific cell/tissue – at a particular stage and condition – to determine their structures and to measure their abundances. RNA-seq data promise to ...

The inference of gene co-expression networks is a valuable resource for novel hypotheses in experimental research. Routine high-throughput microarray transcript profiling experiments and the rapid development of next-generation sequencing (NGS) technologies generate a large amount of publicly available data, enabling ...

“Sailfish” Method Could Pay Dividends as Genomic Medicine Expands Contact: Byron Spice  / 412-268-9068  / [email protected] PITTSBURGH—With gene expression analysis growing in importance for both basic researchers and medical practitioners, researchers at Carnegie Mellon University and the University of Maryland ...

Next-generation sequencing (NGS) has advanced the application of high-throughput sequencing technologies in genetic and genomic variation analysis. Due to the large dynamic range of expression levels, RNA-seq is more prone to detect transcripts with low expression. It is clear that ...

High-throughput sequencing is now regularly used for studies of the transcriptome (RNA-seq), particularly for comparisons among experimental conditions. For the time being, a limited number of biological replicates are typically considered in such experiments, leading to low detection power for ...

CAGE (cap analysis gene expression) and RNA-seq are two major technologies used to identify transcript abundances as well as structures. They measure expression by sequencing from either the 5′ end of capped molecules (CAGE) or tags randomly distributed along the ...