With new technological developments, the number of sequencing applications is continuously expanding, while at the same time sequencing prices are falling. This is resulting in an exponential increase in sequencing data. However, while ‘big data’ brings more...
Read More »RNA-Seq differential expression analysis – an extended review and a new software tool
The correct identification of differentially expressed genes (DEGs) between specific conditions is a key in the understanding phenotypic variation. High...
Read More »Effect of low-expression gene filtering on detection of differentially expressed genes in RNA-seq data
Researchers from the the Georgia Institute of Technology compare methods for filtering RNA-seq low expression genes and investigate the effect of filtering on detection of differentially expressed genes (DEGs). Although RNA-seq technology has improved the dynamic range of gene expression ...
Read More »Removal of redundant contigs from de novo RNA-Seq assemblies via homology search improves accurate detection of differentially expressed genes
For plant species with unsequenced genomes, cDNA contigs created by de novo assembly of RNA-Seq reads are used as reference sequences for comparative analysis of RNA-Seq datasets and the detection of differentially expressed genes (DEGs). Redundancies in such contigs are ...
Read More »A comparative study of techniques for differential expression analysis on RNA-Seq data
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 ...
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