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Downing, J. R.

Publications and source records attributed to Downing, J. R..

2 recordsLinked to original sources

Pediatric Cancer Variant Pathogenicity Information Exchange (PeCanPIE): A Cloud-based Platform for Curating and Classifying Germline Variants

Variant interpretation in the era of next-generation sequencing (NGS) is challenging. While many resources and guidelines are available to assist with this task, few integrated end-to-end tools exist. Here we present \"PeCanPIE\" - the Pediatric Cancer Variant Pathogenicity Information Exchange, a web- and cloud-based platform for annotation, identification, and classification of variations in known or putative disease genes. Starting from a set of variants in Variant Call Format (VCF), variants are annotated, ranked by putative pathogenicity, and presented for formal classification using a decision-support interface based on published guidelines from the American College of Medical Genetics and Genomics (ACMG). The system can accept files containing millions of variants and handle single-nucleotide variants (SNVs), simple insertions/deletions (indels), multiple-nucleotide variants (MNVs), and complex substitutions. PeCanPIE has been applied to classify variant pathogenicity in cancer predisposition genes in two large-scale investigations involving >4,000 pediatric cancer patients, and serves as a repository for the expert-reviewed results. While PeCanPIEs web-based interface was designed to be accessible to non-bioinformaticians, its back end pipelines may also be run independently on the cloud, facilitating direct integration and broader adoption. PeCanPIE is publicly available and free for research use.

bioinformatics

Contribution Of Genetic Variation And Developmental Stage To Methylome Dynamics In Myeloid Differentiation

DNA methylation is important to establish a cells developmental identity. It also modulates cellular responses to endogenous developmental stimuli or environmental changes. We designed an in vitro myeloid differentiation model to analyze the genetic and developmental contribution to methylome dynamics using whole-genome bisulfide sequencing and transcriptome sequencing. Using a recursive partitioning approach, we identified 34,502 differentially methylated regions (DMRs) associated with genetic background and/or developmental stimuli. Specifically, 23,792 DMRs (69%) were significantly associated with inter-individual variations, of which 82% were associated with genetic polymorphisms in cis. Notably, inter-individual variations further modified 57 of 212 (26%) developmental DMRs with transcriptomic responses. Our study presents a novel analytical approach to determine the bona fide genetic contribution embedded in outlier patterns of CpG-SNPs in individual methylomes. This approach can be used to study genetic and epigenetic mechanisms underlying differential responses to developmental stimuli, environmental changes, and inter-individual differences in drug responses.

genomics