RNA Seq Services
Sequencing RNA provides both abundance and sequence information yielding a deep understanding of gene expression.
RNA Seq services from Canopy Biosciences are designed to be collaborative and customer friendly so your focus is on your data.
Our approach to RNA Seq projects is customer centric with consultative discussion on study goals, sample type, and best library prep methodology for your experiment.
Canopy Biosciences recognizes the complex nature of RNA Seq experiments, so we approach each project with a collaborative intent. However, to kick off the experimental design, we’ve launched 3 package offerings: mRNA Seq, Total RNA Seq and FFPE RNA Seq. To start a conversation with a scientist about your experiment, fill out a project inquiry.
Sequencing coverage, or read depth, is an important variable of any RNA seq experiment. It refers to the number of unique reads that include a nucleotide in the reconstructed sequence; the average number of times a base is read.
In RNA seq, this indicates the sequence but also the frequency of the RNA molecule, giving way to expression level analysis. Our goal is to design your experiment with optimum read depth.
Differential Gene Expression Analysis
We have a custom bioinformatics pipeline that demultiplexes and analyzes sequencing data. As part of our service, differential expression analysis is performed to assess differences between experimental groups. Gene Ontology (GO) terms and KEGG pathways are annotated, noting critical genes. Changes within these genes are calculated, clustered and the expression profile is created. The statistical significance of these expression changes is then determined.
Interested in the Differential Gene Expression Analysis pipeline?
Data Analysis Report
What to do with all this data? RNA seq experiments result in large complex data sets including sequencing fastq files and bioinformatics pipeline files. Let us sort through it and provide an organized report highlighting the sequencing run, the comparison data between your treatment groups, significant changes in gene expression and pathway analysis. Once you know where to focus, you can dig into the raw data yourself- but we’ve given you a starting point.