Sheffield local group seminar on Bioinformatics

Lyn Taylor (PHASTAR) on behalf of the Sheffield Local RSS group organised a seminar on Bioinformatics which took place on the 27 February 2020. The speakers were Mark Dunning (director), Tim Freeman (PhD student) and Sokratis Kariotis (PhD student) all from the Sheffield Bioinformatics Core.

Mark began with an introduction to the 'Statistical and Data Analysis Challenges in Bioinformatics'. Bioinformatics is a multi-disciplinary subject that combines aspects of biology, computer science and statistics. Modern experimental techniques are able to generate vast amounts of data that can profile an individual's genome and offer insights into the development of disease and potential novel therapeutics. In this talk, Mark described the challenges faced by Bioinformaticians trying to deal with such data on a daily basis and the opportunities for collaboration with other disciplines to develop new analytical methods.

Following the introduction, Tim presented on 'Identifying genomic loci susceptible to systematic sequencing bias in clinical whole genomes'. Accurate next-generation sequencing (NGS) of genetic variants is key to many areas of science and medicine, such as cataloguing population genetic variation and diagnosing genetic diseases. Certain genomic positions can be prone to higher rates of systematic sequencing and alignment bias that limit accuracy, resulting in false positive variant calls.

Current standard practices to differentiate between loci that can and cannot be sequenced with high confidence utilise consensus between different sequencing methods as a proxy for sequencing confidence. These practices have significant limitations and alternative methods are required to overcome these. Tim described how their group have developed a novel statistical method based on summarising sequenced reads from whole genome clinical samples and cataloguing them in 'Incremental Databases' (IncDBs) that maintain individual confidentiality. Allele statistics were catalogued for each genomic position that consistently showed systematic biases with the corresponding NGS sequencing pipeline. They found systematic biases present at ~1‑3% of the human autosomal genome across five patient cohorts and identified which genomic regions were more or less prone to systematic biases, including large homopolymer flanks (OR=23.29-33.69) and the NIST high confidence genomic regions (OR=0.154-0.191). They confirmed their predictions on a gold-standard reference genome and showed that these systematic biases can lead to suspect variant calls within clinical panels. The results recommend increased caution to address systematic biases in whole genome sequencing and alignment. This study provides the implementation of a simple statistical approach to enhance quality control of clinically sequenced samples by flagging variants at suspect loci for further analysis or exclusion.

The seminar concluded with a presentation by Sokratis on 'Cluster analysis of whole-blood gene expression to uncover heterogeneity of Idiopathic Pulmonary Arterial Hypertension (IPAH), a difficult-to-diagnose rare disease that has mostly unknown causes and describes a heterogeneous group of conditions. Its diagnosis can often be delayed by up to three years from the first symptom as the disease is defined by a diagnosis of exclusion of other forms of PAH which leads to a heterogeneous population of patients and a difficulty to define IPAH structure. To decipher the features that characterise a health condition or a clinical phenotype, this study selects two robust and consistent spectral clustering models utilising RNA profiles to discriminate between finer independent sample subgroups. The clustering models extracted five pure IPAH and four mixed (IPAH/healthy) groups and the presence of significantly enriched clinical or genetic features was explored.

Discussion continued at the University Arms for food and drinks!

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