Ideafix: A decision tree-based method for the refinement of variants in FFPE DNA sequencing data

Ideafix: A decision tree-based method for the refinement of variants in FFPE DNA sequencing data

Increasingly, treatment decisions for cancer patients are being made from next-generation sequencing results generated from formalin-fixed and paraffin-embedded (FFPE) biopsies. However, this material is prone to sequence artefacts that cannot be easily identified. In order to address this issue, we...

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Bibliographic Details
Main Authors: Calvo, B. (Author), Lawrie, C. (Author), Tellaetxe-Abete, M. (Author)
Format: Article
Language:English
Published: Oxford University Press 2021
Subjects:
algorithm
Article
artifact
biopsy
breast cancer
clinical article
cross linking
cross validation
cytosine
deamination
decision tree
DNA fragmentation
DNA sequencing
esophagus tumor
feature extraction
formaldehyde
formalin fixed and paraffin embedded biopsy
gene frequency
genetic variability
human
human tissue
learning algorithm
leave one sample out cross validation
liver cancer
machine learning
paraffin
random forest
stomach tumor
whole exome sequencing
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