Abstract

SNPnexus is a web-based annotation tool for the analysis and interpretation of both known and novel sequencing variations. Since its last release, SNPnexus has received continual updates to expand the range and depth of annotations provided. SNPnexus has undergone a complete overhaul of the underlying infrastructure to accommodate faster computational times. The scope for data annotation has been substantially expanded to enhance biological interpretations of queried variants. This includes the addition of pathway analysis for the identification of enriched biological pathways and molecular processes. We have further expanded the range of user directed annotation fields available for the study of cancer sequencing data. These new additions facilitate investigations into cancer driver variants and targetable molecular alterations within input datasets. New user directed filtering options have been coupled with the addition of interactive graphical and visualization tools. These improvements streamline the analysis of variants derived from large sequencing datasets for the identification of biologically and clinically significant subsets in the data. SNPnexus is the most comprehensible web-based application currently available and these new set of updates ensures that it remains a state-of-the-art tool for researchers. SNPnexus is freely available at https://www.snp-nexus.org.

Highlights

  • Current high-throughput sequencing technologies produce vast amounts of variation data

  • Most of the data sources have been pre-processed and converted to BED format that allows for the use of Tabix [9] for a fast query of data based on chromosomal position; many annotations for known dbSNPs have been precomputed and stored on a MongoDB [10] database; and some annotations, namely the DeepSEA [11] scoring algorithm for non-coding variants and the Cancer Genome Interpreter, are installed in the server and executed when required for the input set

  • The new architecture and the pre-processing of the data sources have improved the overall performance of the system especially notable in a drastic reduction of the annotation processing times

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Summary

Introduction

Current high-throughput sequencing technologies produce vast amounts of variation data. Screening of phenotypically-relevant variants requires the integration of genomic annotation data with a broad range of other annotation categories to allow users to determine possible consequences of the queried alterations.

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