Minimum error correction-based haplotype assembly: considerations for long read data

The single nucleotide polymorphism (SNP) is the most widely studied type of genetic variation. A haplotype is defined as the sequence of alleles at SNP sites on each haploid chromosome. Haplotype information is essential in unravelling the genome-phenotype association. Haplotype assembly is a well-known approach for reconstructing haplotypes, exploiting reads generated by DNA sequencing devices. The Minimum Error Correction (MEC) metric is often used for reconstruction of haplotypes from reads. However, problems with the MEC metric have been reported. Here, we investigate the MEC approach to demonstrate that it may result in incorrectly reconstructed haplotypes for devices that produce error-prone long reads. Specifically, we evaluate this approach for devices developed by Illumina, Pacific BioSciences and Oxford Nanopore Technologies. We show that imprecise haplotypes may be reconstructed with a lower MEC than that of the exact haplotype. The performance of MEC is explored for different coverage levels and error rates of data. Our simulation results reveal that in order to avoid incorrect MEC-based haplotypes, a coverage of 25 is needed for reads generated by Pacific BioSciences RS systems.Comment: 17 pages, 6 figure

Algorithmic methods for large-scale genomic and metagenomic data analysis

DNA sequencing technologies have advanced into the realm of big data due to frequent and rapid developments in biologic medicine. This has caused a surge in the necessity of efficient and highly scalable algorithms.This dissertation focuses on central work in read-to-reference alignments, resequencing studies, and metagenomics that were designed with these principles as the guiding reason for their construction.First, consider the computing intensive task of read-to-reference alignments, where the difficulty of aligning reads to a genome is directly related their complexity. We investigated three different formulations of sequence complexity as viable tools for measuring genome complexity along with how they related to short read alignments and found that repeat measures of complexity were best suited for this task. In particular, the fraction of distinct substrings of lengths close to the read length was found to correlate very highly to alignment accuracy in terms of precision and recall. All this demonstrated how to build models to predict accuracy of short read aligners with predictably low errors. As a result, practitioners can select the most accurate aligners for an unknown genome by comparing how different models predict alignment accuracy based on the genomes complexity. Furthermore, accurate recall rate prediction may help practitioners reduce expenses by using just enough reads to get sufficient sequencing coverage.Next, focus on the comprehensive task of resequencing studies for analyzing genetic variants of the human population. By using optimal alignments, we revealed that the current variant profiles contained thousands of insertion/deletion (INDEL) that were constructed in a biased manner. The bias is caused by the existence of many theoretically optimal alignments between the reference genome and reads containing alternative alleles at those INDEL locations. We examined several popular aligners and showed that these aligners could be divided into groups whose alignments yielded INDELs that either strongly agreed or disagreed with reported INDELs. This finding suggests that the agreement or disagreement between the aligners called INDEL and the reported INDEL is merely a result of the arbitrary selection of an optimal alignment. Also of note is LongAGE, a memory efficient of Alignment with Gap Excision (AGE) for defining geneomic variant breakpoints, which enables the precise alignment of longer reads or contigs that potentially contain SVs/CNVs while having a trade off of time compared to AGE.Finally, consider several resource-intensive tasks in metagenomics. We introduce a new algorithmic method for detecting unknown bacteria, those whose genomes have not been sequenced, in microbial communities. Using the 16S ribosomal RNA (16S rRNA) gene instead of the whole genomes information is not only computational efficient, but also economical; an analysis that demonstrates the 16S rRNA gene retains sufficient information to allow us to detect unknown bacteria in the context of oral microbial communities is provided. Furthermore, the main hypothesis that the classification or identification of microbes in metagenomic samples is better done with long reads than with short reads is iterated upon, by investigating the performance of popular metagenomic classifiers on short reads and longer reads assembled from those short reads. Higher overall performance of species classification was achieved simply by assembling short reads.These topics about read-to-reference alignments, resequencing studies, and metagenomics are all key focal points in the pages to come. My dissertation delves deeper into these as I cover the contributions my work has made to the field

Statistical analysis of short template switch mutations in human genomes

Many complex rearrangements arise in human genomes through template switch mutations, which occur during DNA replication when there is a transient polymerase switch to an alternate template nearby in three-dimensional space. These variants are routinely captured at kilobase-to-megabase scales in studies of genetic variation by using methods for structural variant calling. However, the genomic and evolutionary consequences of replication-based rearrangements remain poorly characterised at smaller scales, where they are usually interpreted as complex clusters of independent substitutions, insertions and deletions. In this thesis, I describe statistical methods for the detection and interpretation of short template switch mutations within DNA sequence data. I then use my methods to explore small-scale template switch mutagenesis within human genome evolution, population variation, and cancer. I show that small-scale, replication- based rearrangements are a ubiquitous feature of the germline and somatic mutational landscape of human genomes.European Molecular Biology Laboratory National Institute for Health Researc