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RNA-seq and whole exome sequencing

We have analyzed data from matched tumor/normal samples from two uveal melanomas patients with easy-to-use workflows implemented in CLC Cancer Research Workbench to investigate the benefits of RNA-seq compared to whole exome sequencing.

Data analysis

For data analysis, CLC Cancer Research Workbench provides ready-to-use workflows combining tools like read mapping, annotation, and reporting.

For variant calling, we use the “Identify Variants” workflow and tumor-specific variants are identified using the “Filter Germline Variants from Tumor Normal Pair” workflow.
Following variant calling and filtering, variants from the whole exome sequencing and the RNA-seq data are compared.

Conclusions

  • CLC Cancer Research Workbench provides easy-to-use workflows that include algorithms for read mapping, variant calling, filtering, and annotation.
  • The tool “Identify Known Mutations from Sample Mappings” provides a more reliable method compared with variant calling to recover variants previously detected in WES data.
  • The analysis of whole exome sequencing and RNA-seq data sets can easily be combined using the tools provided in CLC Cancer Research Workbench .
  • In comparison to WES, RNA-seq reports only those candidate variants being expressed.

Get more information about comparison of variant calling from whole exome and transcriptome sequencing data using CLC Cancer Research Workbench:

Application note
Poster