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Visualizing genomic information across chromosomes with PhenoGram

BACKGROUND: 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 chromoso...

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Autores principales: Wolfe, Daniel, Dudek, Scott, Ritchie, Marylyn D, Pendergrass, Sarah A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015356/
https://www.ncbi.nlm.nih.gov/pubmed/24131735
http://dx.doi.org/10.1186/1756-0381-6-18
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author Wolfe, Daniel
Dudek, Scott
Ritchie, Marylyn D
Pendergrass, Sarah A
author_facet Wolfe, Daniel
Dudek, Scott
Ritchie, Marylyn D
Pendergrass, Sarah A
author_sort Wolfe, Daniel
collection PubMed
description BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.
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spelling pubmed-40153562014-05-10 Visualizing genomic information across chromosomes with PhenoGram Wolfe, Daniel Dudek, Scott Ritchie, Marylyn D Pendergrass, Sarah A BioData Min Software Article BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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. BioMed Central 2013-10-16 /pmc/articles/PMC4015356/ /pubmed/24131735 http://dx.doi.org/10.1186/1756-0381-6-18 Text en Copyright © 2013 Wolfe et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Article
Wolfe, Daniel
Dudek, Scott
Ritchie, Marylyn D
Pendergrass, Sarah A
Visualizing genomic information across chromosomes with PhenoGram
title Visualizing genomic information across chromosomes with PhenoGram
title_full Visualizing genomic information across chromosomes with PhenoGram
title_fullStr Visualizing genomic information across chromosomes with PhenoGram
title_full_unstemmed Visualizing genomic information across chromosomes with PhenoGram
title_short Visualizing genomic information across chromosomes with PhenoGram
title_sort visualizing genomic information across chromosomes with phenogram
topic Software Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4015356/
https://www.ncbi.nlm.nih.gov/pubmed/24131735
http://dx.doi.org/10.1186/1756-0381-6-18
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