Name
Abstract | ||
|---|---|---|
With the abundance of information and analysis results being collected for genetic loci, user-friendly and flexible data visualization approaches can inform and improve the analysis and dissemination of these data. A chromosomal ideogram is an idealized graphic representation of chromosomes. Ideograms can be combined with overlaid points, lines, and/or shapes, to provide summary information from studies of various kinds, such as genome-wide association studies or phenome-wide association studies, coupled with genomic location information. To facilitate visualizing varied data in multiple ways using ideograms, we have developed a flexible software tool called PhenoGram which exists as a web-based tool and also a command-line program.With PhenoGram researchers can create chomosomal ideograms annotated with lines in color at specific base-pair locations, or colored base-pair to base-pair regions, with or without other annotation. PhenoGram allows for annotation of chromosomal locations and/or regions with shapes in different colors, gene identifiers, or other text. PhenoGram also allows for creation of plots showing expanded chromosomal locations, providing a way to show results for specific chromosomal regions in greater detail. We have now used PhenoGram to produce a variety of different plots, and provide these as examples herein. These plots include visualization of the genomic coverage of SNPs from a genotyping array, highlighting the chromosomal coverage of imputed SNPs, copy-number variation region coverage, as well as plots similar to the NHGRI GWA Catalog of genome-wide association results.PhenoGram is a versatile, user-friendly software tool fostering the exploration and sharing of genomic information. Through visualization of data, researchers can both explore and share complex results, facilitating a greater understanding of these data. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1186/1756-0381-6-18 | BioData mining |
Keywords | Field | DocType |
bioinformatics,biomedical research,algorithms | Software tool,Data mining,Data visualization,Chromosome,Copy-number variation,Computer science,Genome-wide association study,Genetic association,Bioinformatics,Ideogram,Locus (genetics) | Journal |
Volume | Issue | ISSN |
6 | 1 | 1756-0381 |
Citations | PageRank | References |
3 | 0.82 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Wolfe | 1 | 3 | 0.82 |
| Scott M. Dudek | 2 | 206 | 26.27 |
| Marylyn D. Ritchie | 3 | 692 | 86.79 |
| Sarah A. Pendergrass | 4 | 42 | 9.20 |