Gene expression is processed by information from a gene which is used in synthesis of a functional gene product. These products are often proteins, but in non-protein coding genes such as ribosomal RNA (rRNA), transfer RNA (tRNA) or small nuclear RNA (snRNA) genes, the product is a functional RNA. RNA seq can analyze gene expression level between sample groups.
Correlation analysis is especially useful when comparing the gene expression level between time points or case and control. Correlation analysis is usually undertaken before the detailed DEG analysis.
DEG stands for Differentially Expressed Gene.
This shows up and down regulation of genes between samples. This analysis is especially useful for case-control comparative investigations.
SNP analysis is to detect Single-nucleotide
polymorphisms (SNPs) and small insertion and deletions based on known reference genomes.
GO Enrichment Analysis
GO stands for gene ontology. It is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species.
Gene Structure Profiling
Gene Structure Profiling is to predict structure and configuration of gene. This analysis can predict previously unknown gene structure such as alternative spliced forms.
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- Trapnell C, et al., Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010 May;28(5):511-5. Epub 2010 May 2.
- Wang L. et al., DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics. 2010 Jan 1;26(1):136-8. Epub 2009 Oct 24.
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- Gene Ontology Consortium., “The Gene Ontology project in 2008″.Nucleic Acids Res. 36 (Database issue): D440–4. doi:10.1093/nar/gkm883.PMC 2238979. PMID 17984083.
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