MOTIVATION: Short tandem repeats (STRs) are regions of a genome containing many consecutive copies of the same short motif, possibly with small variations. Analysis of STRs has many clinical uses but is limited by technology mainly due to STRs surpassing the used read length. Nanopore sequencing, as one of long-read sequencing technologies, produces very long reads, thus offering more possibilities to study and analyze STRs. Basecalling of nanopore reads is however particularly unreliable in repeating regions, and therefore direct analysis from raw nanopore data is required. RESULTS: Here, we present WarpSTR, a novel method for characterizing both simple and complex tandem repeats directly from raw nanopore signals using a finite-state automaton and a search algorithm analogous to dynamic time warping. By applying this approach to determine the lengths of 241 STRs, we demonstrate that our approach decreases the mean absolute error of the STR length estimate compared to basecalling and STRique. AVAILABILITY AND IMPLEMENTATION: WarpSTR is freely available at https://github.com/fmfi-compbio/warpstr.

MOTIVATION: Non-invasive prenatal testing or NIPT is currently among the top researched topic in obstetric care. While the performance of the current state-of-the-art NIPT solutions achieve high sensitivity and specificity, they still struggle with a considerable number of samples that cannot be concluded with certainty. Such uninformative results are often subject to repeated blood sampling and re-analysis, usually after two weeks, and this period may cause a stress to the future mothers as well as increase the overall cost of the test. RESULTS: We propose a supplementary method to traditional z-scores to reduce the number of such uninformative calls. The method is based on a novel analysis of the length profile of circulating cell free DNA which compares the change in such profiles when random-based and length-based elimination of some fragments is performed. The proposed method is not as accurate as the standard z-score; however, our results suggest that combination of these two independent methods correctly resolves a substantial portion of healthy samples with an uninformative result. Additionally, we discuss how the proposed method can be used to identify maternal aberrations, thus reducing the risk of false positive and false negative calls. AVAILABILITY AND IMPLEMENTATION: The open-source code of the proposed methods, together with test data, is freely available for non-commercial users at github web page https://github.com/jbudis/lambda. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

MOTIVATION: Short tandem repeats (STRs) are stretches of repetitive DNA in which short sequences, typically made of 2-6 nucleotides, are repeated several times. Since STRs have many important biological roles and also belong to the most polymorphic parts of the human genome, they became utilized in several molecular-genetic applications. Precise genotyping of STR alleles, therefore, was of high relevance during the last decades. Despite this, massively parallel sequencing (MPS) still lacks the analysis methods to fully utilize the information value of STRs in genome scale assays. RESULTS: We propose an alignment-free algorithm, called Dante, for genotyping and characterization of STR alleles at user-specified known loci based on sequence reads originating from STR loci of interest. The method accounts for natural deviations from the expected sequence, such as variation in the repeat count, sequencing errors, ambiguous bases and complex loci containing several different motifs. In addition, we implemented a correction for copy number defects caused by the polymerase induced stutter effect as well as a prediction of STR expansions that, according to the conventional view, cannot be fully captured by inherently short MPS reads. We tested Dante on simulated datasets and on datasets obtained by targeted sequencing of protein coding parts of thousands of selected clinically relevant genes. In both these datasets, Dante outperformed HipSTR and GATK genotyping tools. Furthermore, Dante was able to predict allele expansions in all tested clinical cases. AVAILABILITY AND IMPLEMENTATION: Dante is open source software, freely available for download at https://github.com/jbudis/dante. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.