Vanno: a visualization-aided variant annotation tool

P2T2: Protein Panoramic annoTation Tool for the interpretation of protein coding genetic variants

MOTIVATION

Genomic data are prevalent, leading to frequent encounters with uninterpreted variants or mutations with unknown mechanisms of effect. Researchers must manually aggregate data from multiple sources and across related proteins, mentally translating effects between the genome and proteome, to attempt to understand mechanisms.

MATERIALS AND METHODS

P2T2 presents diverse data and annotation types in a unified protein-centric view, facilitating the interpretation of coding variants and hypothesis generation. Information from primary sequence, domain, motif, and structural levels are presented and also organized into the first Paralog Annotation Analysis across the human proteome.

RESULTS

Our tool assists research efforts to interpret genomic variation by aggregating diverse, relevant, and proteome-wide information into a unified interactive web-based interface. Additionally, we provide a REST API enabling automated data queries, or repurposing data for other studies.

CONCLUSION

The unified protein-centric interface presented in P2T2 will help researchers interpret novel variants identified through next-generation sequencing. Code and server link available at github.com/GenomicInterpretation/p2t2.

A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data

The Cancer Genome Atlas (TCGA) is a publicly funded project that aims to catalog and discover major cancer-causing genomic alterations with the goal of creating a comprehensive ‘atlas’ of cancer genomic profiles. The availability of this genome-wide information provides an unprecedented opportunity to expand our knowledge of tumourigenesis. Computational analytics and mining are frequently used as effective tools for exploring this byzantine series of biological and biomedical data. However, some of the more advanced computational tools are often difficult to understand or use, thereby limiting their application by scientists who do not have a strong computational background. Hence, it is of great importance to build user-friendly interfaces that allow both computational scientists and life scientists without a computational background to gain greater biological and medical insights. To that end, this survey was designed to systematically present available Web-based tools and facilitate the use TCGA data for cancer research.

VAReporter: variant reporter for cancer research of massive parallel sequencing

Background

High throughput sequencing technologies have been an increasingly critical aspect of precision medicine owing to a better identification of disease targets, which contributes to improved health care cost and clinical outcomes. In particular, disease-oriented targeted enrichment sequencing is becoming a widely-accepted application for diagnostic purposes, which can interrogate known diagnostic variants as well as identify novel biomarkers from panels of entire human coding exome or disease-associated genes.

Results

We introduce a workflow named VAReporter to facilitate the management of variant assessment in disease-targeted sequencing, the identification of pathogenic variants, the interpretation of biological effects and the prioritization of clinically actionable targets. State-of-art algorithms that account for mutation phenotypes are used to rank the importance of mutated genes through visual analytic strategies. We established an extensive annotation source by integrating a wide variety of biomedical databases and followed the American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation and reporting of sequence variations.

Conclusions

In summary, VAReporter is the first web server designed to provide a “one-stop” resource for individual’s diagnosis and large-scale cohort studies, and is freely available at http://rnd.cgu.edu.tw/vareporter.

Nonsynonymous variants in MYH9 and ABCA4 are the most frequent risk loci associated with nonsyndromic orofacial cleft in Taiwanese population

BACKGROUND

Nonsyndromic orofacial cleft is a common birth defect with a complex etiology, including multiple genetic and environmental risk factors. Recent whole genome analyses suggested associations between nonsyndromic orofacial cleft and up to 18 genetic risk loci (ABCA4, BMP4, CRISPLD2, GSTT1, FGF8, FGFR2, FOXE1, IRF6, MAFB, MSX1, MTHFR, MYH9, PDGFC, PVRL1, SUMO1, TGFA, TGFB3, and VAX1), each of which confers a different relative risk in different populations. We evaluate the nonsynonymous variants in these 18 genetic risk loci in nonsyndromic orofacial clefts and normal controls to clarify the specific variants in Taiwanese population.

METHODS

We evaluated these 18 genetic risk loci in 103 cases of nonsyndromic orofacial clefts and 100 normal controls using a next-generation sequencing (NGS) customized panel and manipulated a whole-exon targeted-sequencing study based on the NGS system of an Ion Torrent Personal Genome Machine (IT-PGM). IT-PGM data processing, including alignment with the human genome build 19 reference genome (hg19), base calling, trimming of barcoded adapter sequences, and filtering of poor signal reads, was performed using the IT platform-specific pipeline software Torrent Suite, version 4.2, with the plug-in "variant caller" program. Further advanced annotation was facilitated by uploading the exported VCF file from Variant Caller to the commercial software package Ion Reporter; the free online annotation software Vanno and Mutation Taster. Benign or tolerated amino acid changes were excluded after analysis using sorting intolerant from tolerant and polymorphism phenotyping. Sanger sequencing was used to validate the significant variants identified by NGS. Furthermore, each variant was confirmed in asymptomatic controls using the Sequenom MassARRAY (San Diego, CA, USA).

RESULTS

We identified totally 22 types of nonsynonymous variants specific in nonsyndromic orofacial clefts, including 19 single nucleotide variants, 2 deletions, and 1 duplication in 10 studied genes(ABCA4, MYH9, MTHFR, CRISPLD2, FGF8, PVRL1, FOXE1, VAX1, FGFR2, and IRF6). Nonsynonymous variants in MYH9 and ABCA4, which were detected in 6 and 5 individuals, respectively, were identified to be the most frequent risk loci in nonsyndromic orofacial clefts in the Taiwanese population.

CONCLUSIONS

Nonsynonymous variants in MYH9 and ABCA4 were identified to be the most frequent risk loci in nonsyndromic orofacial clefts in the Taiwanese population. These findings in our study have provided additional information regarding specific variants associated with nonsyndromic orofacial clefts in different population and demonstrate the power of our customized NGS panel, which is clinically useful for the simultaneous detection of multiple genes associated with nonsyndromic orofacial clefts.

Visualizing genome and systems biology: technologies, tools, implementation techniques and trends, past, present and future

"Α picture is worth a thousand words." This widely used adage sums up in a few words the notion that a successful visual representation of a concept should enable easy and rapid absorption of large amounts of information. Although, in general, the notion of capturing complex ideas using images is very appealing, would 1000 words be enough to describe the unknown in a research field such as the life sciences? Life sciences is one of the biggest generators of enormous datasets, mainly as a result of recent and rapid technological advances; their complexity can make these datasets incomprehensible without effective visualization methods. Here we discuss the past, present and future of genomic and systems biology visualization. We briefly comment on many visualization and analysis tools and the purposes that they serve. We focus on the latest libraries and programming languages that enable more effective, efficient and faster approaches for visualizing biological concepts, and also comment on the future human-computer interaction trends that would enable for enhancing visualization further.