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The wealth of routinely processed formalin-fixed and paraffin-embedded (FFPE) cancer biopsies is potentially a tremendous resource for cancer genomics research. However, the presence of formalin-induced artifactual mutations in FFPE material can confound mutational analyses. Our de-noising algorithm, FFPEsig, removes FFPE-related artifactual mutations enabling the inference of biological mutational signatures. In this chapter, we focus on the practical use of FFPEsig, offering a detailed guidance from both the wet-lab experimental and bioinformatics analysis perspectives. Our aim is to assist users to generate robust and significant results using FFPEsig.

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Using FFPEsig to Remove Formalin-Induced Artifacts and Characterize Mutational Signatures in Cancer

  • 实验方案

  • 发表日期：

    2025年

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  • Qingli Guo,
  • Ann-Marie Baker,
  • Ville Mustonen,
  • Trevor A. Graham

摘要

The wealth of routinely processed formalin-fixed and paraffin-embedded (FFPE) cancer biopsies is potentially a tremendous resource for cancer genomics research. However, the presence of formalin-induced artifactual mutations in FFPE material can confound mutational analyses. Our de-noising algorithm, FFPEsig, removes FFPE-related artifactual mutations enabling the inference of biological mutational signatures. In this chapter, we focus on the practical use of FFPEsig, offering a detailed guidance from both the wet-lab experimental and bioinformatics analysis perspectives. Our aim is to assist users to generate robust and significant results using FFPEsig.