Accurate fetal variant calling in the presence of maternal cell contamination

Abstract

<jats:title>Abstract</jats:title><jats:p>High-throughput sequencing of fetal DNA is a promising and increasingly common method for the discovery of all (or all coding) genetic variants in the fetus, either as part of prenatal screening or diagnosis, or for genetic diagnosis of spontaneous abortions. In many cases, the fetal DNA (from chorionic villi, amniotic fluid, or abortive tissue) can be contaminated with maternal cells, resulting in the mixture of fetal and maternal DNA. This maternal cell contamination (MCC) undermines the assumption, made by traditional variant callers, that each allele in a heterozygous site is covered, on average, by 50% of the reads, and therefore can lead to erroneous genotype calls. We present a panel of methods for reducing the genotyping error in the presence of MCC. All methods start with the output of GATK HaplotypeCaller on the sequencing data for the (contaminated) fetal sample and both of its parents, and additionally rely on information about the MCC fraction (which itself is readily estimated from the high-throughput sequencing data). The first of these methods uses a Bayesian probabilistic model to correct the fetal genotype calls produced by MCC-unaware HaplotypeCaller. The other two methods “learn” the genotype-correction model from examples. We use simulated contaminated fetal data to train and test the models. Using the test sets, we show that all three methods lead to substantially improved accuracy when compared with the original MCC-unaware HaplotypeCaller calls. We then apply the best-performing method to three chorionic villus samples from spontaneously terminated pregnancies.</jats:p><jats:sec><jats:title>Code and training data availability</jats:title><jats:p><jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/bazykinlab/ML-maternal-cell-contamination">https://github.com/bazykinlab/ML-maternal-cell-contamination</jats:ext-link></jats:p></jats:sec>

Estimation of intrafamilial DNA contamination in family trio genome sequencing using deviation from Mendelian inheritance

“…TrioMix uses genotypes directly inferred from the family relationship to estimate the DNA mixture fraction. We are aware of only one other tool that estimates maternal contamination for trio data, which also uses Mendelian inheritance to estimate contamination levels for adjusting the genotype calls in the presence of maternal DNA contamination (Nabieva et al 2020). In TrioMix, we implemented a comprehensive and robust statistical framework using maximum likelihood to estimate contamination between family members for single-source and multiple-source contamination cases.…”