Family genome browser: visualizing genomes with pedigree information

HaploForge: a comprehensive pedigree drawing and haplotype visualization web application

Motivation

Haplotype reconstruction is an important tool for understanding the aetiology of human disease. Haplotyping infers the most likely phase of observed genotypes conditional on constraints imposed by the genotypes of other pedigree members. The results of haplotype reconstruction, when visualized appropriately, show which alleles are identical by descent despite the presence of untyped individuals. When used in concert with linkage analysis, haplotyping can help delineate a locus of interest and provide a succinct explanation for the transmission of the trait locus. Unfortunately, the design choices made by existing haplotype visualization programs do not scale to large numbers of markers. Indeed, following haplotypes from generation to generation requires excessive scrolling back and forth. In addition, the most widely used program for haplotype visualization produces inconsistent recombination artefacts for the X chromosome.

Results

To resolve these issues, we developed HaploForge, a novel web application for haplotype visualization and pedigree drawing. HaploForge takes advantage of HTML5 to be fast, portable and avoid the need for local installation. It can accurately visualize autosomal and X-linked haplotypes from both outbred and consanguineous pedigrees. Haplotypes are coloured based on identity by descent using a novel A* search algorithm and we provide a flexible viewing mode to aid visual inspection. HaploForge can currently process haplotype reconstruction output from Allegro, GeneHunter, Merlin and Simwalk.

Availability and implementation

HaploForge is licensed under GPLv3 and is hosted and maintained via GitHub. https://github.com/mtekman/haploforge.

Contact

r.kleta@ucl.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

Interactive Exploration, Analysis, and Visualization of Complex Phenome-Genome Datasets with ASPIREdb

Identifying variants causal for complex genetic disorders is challenging. With the advent of whole-exome and whole-genome sequencing, computational tools are needed to explore and analyze the list of variants for further validation. Correlating genetic variants with subject phenotype is crucial for the interpretation of the disease-causing mutations. Often such work is done by teams of researchers who need to share information and coordinate activities. To this end, we have developed a powerful, easy to use Web application, ASPIREdb, which allows researchers to search, organize, analyze, and visualize variants and phenotypes associated with a set of human subjects. Investigators can annotate variants using publicly available reference databases and build powerful queries to identify subjects or variants of interest. Functional information and phenotypic associations of these genes are made accessible as well. Burden analysis and additional reporting tools allow investigation of variant properties and phenotype characteristics. Projects can be shared, allowing researchers to work collaboratively to build queries and annotate the data. We demonstrate ASPIREdb's functionality using publicly available data sets, showing how the software can be used to accomplish goals that might otherwise require specialized bioinformatics expertise. ASPIREdb is available at http://aspiredb.chibi.ubc.ca.

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.