Can RNA-seq be used to compare levels of expression of two genes?
The advantage of RNA-Seq over microarrays is that it provides an unbiased insight into all transcripts (Zhao et al., 2014). Thus, RNA-Seq is generally reliable for accurately measuring gene expression level changes.
What is clustering in RNA-seq?
Clustering RNA-seq data is used as an exploratory tool that allows the user to organize and visualize relationships between groups of genes, and to select certain genes for further consideration.
Does RNA-seq measure gene expression?
RNA-seq is a novel methodology based on NGS that enables to investigate differential gene expression at high resolution. In RNA-seq studies, gene expression levels are measured by counts, i.e. by the number of reads mapped on each gene.
How does gene cluster contribute to gene expression?
Under the coregulation model, genes are organized into clusters, each consisting of a single promoter and a cluster of coding sequences, which are therefore co-regulated, showing coordinated gene expression.
Is RNA sequencing faster than microarrays?
“mRNA-Seq offers improved specificity, so it’s better at detecting transcripts, and specifically isoforms, than microarrays. It’s also more sensitive in detecting differential expression and offers increased dynamic range.”
What is a disadvantage of using RNA-Seq for gene identification?
RNA-Seq is best used to identify new biomarkers, gene variants, or mutations, but is especially inefficient if gene markers have already been identified and consequently all the information of interest comes from this focused subset of genes.
What can you do with RNA-Seq data?
In addition to mRNA transcripts, RNA-Seq can look at different populations of RNA to include total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling. RNA-Seq can also be used to determine exon/intron boundaries and verify or amend previously annotated 5′ and 3′ gene boundaries.
How do you identify a gene cluster?
Gene clusters are identified by locating key catalytic domains of these signature enzymes, namely adenylation (‘A’) domain for NRPS and acyltransferase (‘AT’) domain for PKS.
When is fuzzy clustering used?
Fuzzy logic principles can be used to cluster multidimensional data, assigning each point a membership in each cluster center from 0 to 100 percent. This can be very powerful compared to traditional hard-threshold clustering where every point is assigned a crisp, exact label.