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Biology subjects

Christensen, M. H.

Publications and source records attributed to Christensen, M. H..

2 recordsLinked to original sources
bioRxiv2022

DREAMS: Deep Read-level Error Model for Sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

Circulating tumor DNA detection using Next-Generation Sequencing (NGS) data of plasma DNA is promising for cancer identification and characterization. However, the tumor signal in the blood is often low and difficult to distinguish from errors. We present DREAMS (Deep Read-level Modelling of Sequencing-errors) for estimating error rates of individual read positions. Using DREAMS, we developed statistical methods for variant calling (DREAMS-vc) and cancer detection (DREAMS-cc). For evaluation, we generated deep targeted NGS data of matching tumor and plasma DNA from 85 colorectal cancer patients. The DREAMS approach performed better than state-of-the-art methods for variant calling and cancer detection.

bioinformatics↗
bioRxiv2022

Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns

DNA repair deficiencies in cancers may result in characteristic mutational patterns, as exemplified by deficiency of BRCA1/2 and efficacy prediction for PARP-inhibitors. We trained and evaluated predictive models for loss-of-function (LOF) of 145 individual DDR genes based on genome-wide mutational patterns, including structural variants, indels, and base-substitution signatures. We identified 24 genes whose deficiency could be predicted with good accuracy, including expected mutational patterns for BRCA1/2, MSH3/6, TP53, and CDK12 LOF variants. CDK12 is associated with tandem-duplications, and we here demonstrate that this association can accurately predict gene deficiency in prostate cancers (area under the ROC curve=0.97). Our novel associations include mono- or biallelic LOF variants of ATRX, IDH1, HERC2, CDKN2A, PTEN, and SMARCA4, and our systematic approach yielded a catalogue of predictive models, which may provide targets for further research and development of treatment, and potentially help guide therapy.

genomics↗