Get A Quote Cellecta’s Bioinformatics team offers data analysis services for RNA-Seq or Targeted RNA-Seq (i.e., DriverMap™ EXP assay) raw data. These services provide high-quality data and comprehensive analysis to help you efficiently meet your research goals. Comprehensive analysis ensuring quality data and insightful interpretations Biological replicates assessment to verify the reliability and reproducibility of experiments Differential gene expression (DEG) analysis to identify significant genetic changes Pathway enrichment analysis, including Gene Ontology (GO), KEGG, Reactome, and Disease Ontology (DO) analysis Data visualization through correlation plots, volcano plots, heatmaps, and pathway enrichment charts Our services ensure high-confidence results with accurate titering, allowing you to focus on meaningful insights from your research. Importance of Biological Replicates for Inter-Sample Correlation Biological replicates are crucial for RNA-seq experiments. We assess the correlation of gene expression levels between samples to verify the reliability and reproducibility of experiments. A high correlation coefficient indicates a high similarity between samples, ensuring the quality of the data. Fig. 1: Correlation of gene expression levels between different samples. The closer the correlation coefficient is to 1, the higher the similarity between the samples. Differential Gene Expression (DEG) Analysis Our differential gene expression analysis identifies differentially expressed genes under different conditions. We generate a DEG list and provide data visualizations, including volcano plots, cluster analysis, and pathway enrichment analysis. Volcano Plots: Visualize the distribution of up-regulated and down-regulated genes. Fig. 2: The x-axis in the volcano plot shows the fold change in gene expression between different samples, while the y-axis shows the statistical significance of the difference. Cluster Analysis: Groups genes with similar expression patterns and visualizes them in a heatmap. Fig. 3: Heatmap showing groups of genes with similar expression patterns across different samples. Pathway Enrichment Analysis We conduct enrichment analysis to identify significant biological pathways associated with differentially expressed genes. This includes: Gene Ontology (GO) Analysis: Identifies significantly enriched biological processes, molecular functions, and cellular components. KEGG Pathway Analysis: Identifies significantly enriched metabolic or signal transduction pathways. Reactome Pathway Analysis: Focuses on reactions and biological pathways in human models. Human Disease Ontology (DO) Analysis: Uncovers associations between gene function and human diseases. Fig. 4: Pathway enrichment analysis visualization showing significantly associated biological pathways. Contact us at [email protected] to discuss your RNA-seq bioinformatic analysis needs or request a quote here. Our expert team is here to provide you with high-quality, reliable data analysis to advance your research. FAQs .cbb-frequently-bought-container {display: none!important;}
