1. |
- Kumar, Abhishek, et al.
(författare)
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Familial Cancer Variant Prioritization Pipeline version 2 (FCVPPv2) applied to a papillary thyroid cancer family
- 2018
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Whole-genome sequencing methods in familial cancer are useful to unravel rare clinically important cancer predisposing variants. Here, we present improvements in our pedigree-based familial cancer variant prioritization pipeline referred as FCVPPv2, including 12 tools for evaluating deleteriousness and 5 intolerance scores for missense variants. This pipeline is also capable of assessing non-coding regions by combining FANTOM5 data with sets of tools like Bedtools, ChromHMM, Miranda, SNPnexus and Targetscan. We tested this pipeline in a family with history of a papillary thyroid cancer. Only one variant causing an amino acid change G573R (dbSNP ID rs145736623, NM_019609.4:exon11:c.G1717A:p.G573R) in the carboxypeptidase gene CPXM1 survived our pipeline. This variant is located in a highly conserved region across vertebrates in the peptidase_M14 domain (Pfam ID PF00246). The CPXM1 gene may be involved in adipogenesis and extracellular matrix remodelling and it has been suggested to be a tumour suppressor in breast cancer. However, the presence of the variant in the ExAC database suggests it to be a rare polymorphism or a low-penetrance risk allele. Overall, our pipeline is a comprehensive approach for prediction of predisposing variants for high-risk cancer families, for which a functional characterization is a crucial step to confirm their role in cancer predisposition.
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2. |
- Marschall, Tobias, et al.
(författare)
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Computational pan-genomics : status, promises and challenges
- 2018
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Ingår i: Briefings in Bioinformatics. - : Oxford University Press (OUP). - 1467-5463 .- 1477-4054. ; 19:1, s. 118-135
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Tidskriftsartikel (refereegranskat)abstract
- Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively different computational methods and paradigms are needed. We will witness the rapid extension of computational pan-genomics, a new sub-area of research in computational biology. In this article, we generalize existing definitions and understand a pan-genome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pan-genomics can help address many of the problems currently faced in various domains.
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