Comparative analysis
Comparative analyses enable the identification of biologically meaningful differences between groups of samples. This section describes the template workflows available in the Biomedical Genomics Analysis plugin for two types of such comparative analyses: tumor/normal pair analysis and differential expression analysis.
Tumor/normal pair analysis
Tumor/normal pair analysis involves comparing DNA variants identified in a tumor sample to those found in a matched normal sample from the same individual. Tumor samples may originate from e.g. a tumor tissue biopsy or a liquid tumor biopsy, whereas normal samples are commonly derived from white blood cells.
Key objectives of tumor/normal pair analysis include:
- Identifying somatic variants - those that have been acquired in tumor cells and are present only in the tumor sample.
- Distinguishing germline variants - those inherited and present in all cells from the individual, and therefore found in both the tumor and normal samples.
Accurate variant classification requires careful consideration of sequencing coverage in the normal sample. A variant may appear somatic simply because it was not detected in the normal sample due to low coverage, even though the variant is in fact germline.
Differential expression analysis
Differential expression analysis is used to compare gene or transcript expression levels between defined groups of samples. Such groups may e.g. represent different time points, treatment conditions, or tissue types.
Key objectives of differential expression analysis include:
- Identifying genes or transcripts that are statistically significantly differentially expressed between the defined sample groups.
- Generating supporting visualizations, such as heat maps and PCA plots, and performing pathway enrichment analyses to uncover patterns, outliers, and potential biological insights.
Subsections