Highlights
- •We analysed allelic drop-outs in STR massively parallel sequencing (MPS) data.
- •We extended the capillary electrophoresis (CE) peak height models to model the coverage of MPS data.
- •The coverage model accounts for the large marker imbalances seen with MPS data.
- •We also took into account the increased complexity of the stutter behaviour due to the enhanced resolution of the allelic sequences.
- •We investigated the performance of the coverage model by comparing observed and expected Brier scores.
Abstract
We used a Poisson-gamma model to analyse the allele coverage of autosomal short tandem
repeat (STR) systems obtained by massively parallel sequencing (MPS). The Poisson-gamma
coverage model was created using the peak height models from capillary electrophoresis
(CE) based detection of PCR products as a starting point. The CE models were modified
to account for the differences between CE and MPS signals by accounting for the large
marker imbalances seen for MPS data and by using the Poisson-gamma distribution instead
of the normal, log-normal, or gamma distributions that were applied for CE data. We
took two approaches to estimate the marker imbalance parameters by (1) using a work-flow
data base, and (2) using the results of replicate investigations of the samples.
The Poisson-gamma model was used to estimate the rate of drop-outs of (1) single contributor
dilution series experiments and (2) the minor contributor in two-person mixture samples.
We examined the predictive capabilities of the model by comparing the observed and
expected Brier scores of each sample. We derived the expected Brier scores and their
variances to create asymptotic confidence intervals of the Brier scores. We found
that the Poisson-gamma model performed well when using the work-flow data base, but
that the replicate approach is not necessarily a viable option.
Keywords
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Article info
Publication history
Published online: July 25, 2018
Accepted:
July 23,
2018
Received in revised form:
July 14,
2018
Received:
March 21,
2018
Identification
Copyright
© 2018 Elsevier B.V. All rights reserved.
