What is a differential expression analysis?

What is a differential expression analysis?

Differential expression analysis means taking the normalised read count data and performing statistical analysis to discover quantitative changes in expression levels between experimental groups.

How do you set up an RNA-seq experiment?

A typical RNA-seq experiment consists of the following steps:

1. Design Experiment. Set up the experiment to address your questions.
2. RNA Preparation. Isolate and purify input RNA.
3. Prepare Libraries. Convert the RNA to cDNA; add sequencing adapters.
4. Sequence. Sequence cDNAs using a sequencing platform.
5. Analysis.

How many biological replicates are needed in an RNA-seq experiment?

six biological replicates
For future RNA-seq experiments, these results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes.

What are the minimum required samples for RNA-Seq analysis?

recommended a minimum of five samples per group, based on a variety of RNA-Seq datasets, but both they and others noted that much higher sample numbers are necessary to provide adequate power in samples with high gene dispersion, such as in a population comparison of Caucasian and Nigerian derived cells [10, 15].

What is differential gene expression simple terms?

Differential gene expression, commonly abbreviated as DG or DGE analysis refers to the analysis and interpretation of differences in abundance of gene transcripts within a transcriptome (Conesa et al., 2016).

How do you analyze RNA sequencing?

For most RNA‐seq studies, the data analyses consist of the following key steps [5, 6]: (1) quality check and preprocessing of raw sequence reads, (2) mapping reads to a reference genome or transcriptome, (3) counting reads mapped to individual genes or transcripts, (4) identification of differential expression (DE) …

Why is it important to have biological replicates in an RNA seq experiment?

As the figure above illustrates, biological replicates are of greater importance than sequencing depth, which is the total number of reads sequenced per sample. The figure shows the relationship between sequencing depth and number of replicates on the number of differentially expressed genes identified [1].

What is sequence depth?

Sequencing depth (also known as read depth) describes the number of times that a given nucleotide in the genome has been read in an experiment. These overlap regions therefore of necessity have each nucleotide read more than once (Figure 1).

Which is an important decision in an experimental design?

Good experimental design and appropriate analysis is integral to maximising the power of any NGS study. With regard to RNA-Seq, important experimental design decisions include the choice of sequencing depth and number of technical and/or biological replicates to use.

How are multiplex experimental designs used in biology?

Multiplex experimental designs are now readily available, these can be utilised to increase the numbers of samples or replicates profiled at the cost of decreased sequencing depth generated per sample. These strategies impact on the power of the approach to accurately identify differential expression.

Why is replication important to the experimental design?

Ideally, an efficient experimental design will be informed by an understanding of when increasing sequencing depth begins to provide rapidly diminishing returns with regard to transcript detection and DE testing. Replication is vital for robust statistical inference of DE.