What does it mean when a gene is differentially expressed?
A gene is declared differentially expressed if a difference or change observed in read counts or expression levels/index between two experimental conditions is statistically significant.
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.
What are differentially expressed genes and why they are important?
Differential gene expression is important to understand the biological differences between healthy and diseased states. Two common sources of differential gene expression data are microarray studies and the biomedical literature.
What is RPKM used for?
To normalize these dependencies, RPKM (reads per kilobase of transcript per million reads mapped) and TPM (transcripts per million) are used to measure gene or transcript expression levels.
What is differentially expressed proteins?
A protein was considered to be expressed differentially if there was >two-fold difference in the spectral count ratios between the two samples.
How do different cell types differentially express genes?
How Do Different Cells Express the Genes They Need? Only a fraction of the genes in a cell are expressed at any one time. The variety of gene expression profiles characteristic of different cell types arise because these cells have distinct sets of transcription regulators.
What does acetylation do to proteins?
Acetylation neutralizes the positive charge of lysine and thus affects diverse aspects of protein function, such as stability, enzymatic activity, subcellular localization and interaction with other macromolecules in the cell.
What does a high RPKM mean?
Following this, one gene having higher RPKM means there is more of it around. So you should be able to safely say that the gene with RPKM 2000 is more expressed than the RPKM 100.
How is differential gene expression ( dge ) analysis used?
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many applications of RNA-seq data analysis.
What is the purpose of differential expression testing?
The goal of differential expression testing is to determine which genes are expressed at different levels between conditions. These genes can offer biological insight into the processes affected by the condition (s) of interest.
What should the correlation value be for differential gene expression?
Since the majority of genes are not differentially expressed, samples generally have high correlations with each other (values higher than 0.80). Samples below 0.80 may indicate an outlier in your data and/or sample contamination.
How is the number of reads related to differential expression?
The higher the number of counts, the more reads associated with that gene, and the assumption that there was a higher level of expression of that gene in the sample. The differential expression analysis steps are shown in the flowchart below in green.