Tag Archives: deseq

Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RNA-seq) data analysis. Although there are numerous methods for read count normalization, it remains a challenge to choose an optimal method due to multiple factors contributing to read ...

Differential expression analysis using high-throughput RNA sequencing (RNA-seq) data is widely applied in transcriptomic studies and many software tools have been developed for this purpose. Active development of existing popular tools, together with emergence of new tools means that studies ...

UCSD researchers have assessed the performance of seven normalization methods for single cell RNA-seq using data generated from dilution of RNA samples. Their analyses showed that methods considering spike-in ERCC RNA molecules significantly outperformed those not considering ERCCs. This work ...

RNA-seq is now the technology of choice for genome-wide differential gene expression experiments, but it is not clear how many biological replicates are needed to ensure valid biological interpretation of the results or which statistical tools are best for analyzing ...

Determining differentially expressed genes (DEGs) between biological samples is the key to understand how genotype gives rise to phenotype. RNA-seq and microarray are two main technologies for profiling gene expression levels. However, considerable discrepancy has been found between DEGs detected ...

A team led by researchers at the National Heart Lung and Blood Institute sequenced over 700 individuals from the Drosophila Genetic Reference Panel with the goal of identifying the optimal analysis approach for the detection of differential gene expression among ...

Sequencing is widely used to discover associations between microRNAs (miRNAs) and diseases. However, the negative binomial distribution (NB) and high dimensionality of data obtained using sequencing can lead to low-power results and low reproducibility. Several statistical learning algorithms have been ...

Recently, rapid improvements in technology and decrease in sequencing costs have made RNA-Seq a widely used technique to quantify gene expression levels. Various normalization approaches have been proposed, owing to the importance of normalization in the analysis of RNA-Seq data. ...

This video shows a walk-through of a full 2-condition, 3-replicate RNA-Seq experiment, from loading the data, through QC, quantitation and differential expression analysis using both DESeq2 and SeqMonk’s own Intensity Difference filter. http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative ...