{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T02:36:00Z","timestamp":1784946960456,"version":"3.55.0"},"reference-count":10,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,10,16]],"date-time":"2013-10-16T00:00:00Z","timestamp":1381881600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BioData Mining"],"published-print":{"date-parts":[[2013,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>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.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>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.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>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.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1756-0381-6-18","type":"journal-article","created":{"date-parts":[[2013,10,16]],"date-time":"2013-10-16T15:01:23Z","timestamp":1381935683000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":226,"title":["Visualizing genomic information across chromosomes with PhenoGram"],"prefix":"10.1186","volume":"6","author":[{"given":"Daniel","family":"Wolfe","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott","family":"Dudek","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marylyn D","family":"Ritchie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah A","family":"Pendergrass","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2013,10,16]]},"reference":[{"key":"95_CR1","doi-asserted-by":"publisher","first-page":"e1002406","DOI":"10.1371\/journal.pgen.1002406","volume":"7","author":"PS Ramos","year":"2011","unstructured":"Ramos PS, Criswell LA, Moser KL, Comeau ME, Williams AH, Pajewski NM, Chung SA, Graham RR, Zidovetzki R, Kelly JA, Kaufman KM, Jacob CO, Vyse TJ, Tsao BP, Kimberly RP, Gaffney PM, Alarc\u00f3n-Riquelme ME, Harley JB, Langefeld CD, International Consortium on the Genetics of Systemic Erythematosus: A comprehensive analysis of shared loci between systemic lupus erythematosus (SLE) and sixteen autoimmune diseases reveals limited genetic overlap. Plos Genet. 2011, 7: e1002406-","journal-title":"Plos Genet"},{"key":"95_CR2","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1016\/j.cell.2013.01.035","volume":"152","author":"SR Grossman","year":"2013","unstructured":"Grossman SR, Andersen KG, Shlyakhter I, Tabrizi S, Winnicki S, Yen A, Park DJ, Griesemer D, Karlsson EK, Wong SH, Cabili M, Adegbola RA, Bamezai RNK, Hill AVS, Vannberg FO, Rinn JL, Lander ES, Schaffner SF, Sabeti PC, 1000 Genomes Project: Identifying recent adaptations in large-scale genomic data. Cell. 2013, 152: 703-713.","journal-title":"Cell"},{"key":"95_CR3","doi-asserted-by":"publisher","first-page":"9362","DOI":"10.1073\/pnas.0903103106","volume":"106","author":"LA Hindorff","year":"2009","unstructured":"Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, Manolio TA: Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. 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Plos Genet. 2013, 9: e1003087-","journal-title":"Plos Genet"},{"key":"95_CR6","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1186\/ar3204","volume":"13","author":"A Cortes","year":"2011","unstructured":"Cortes A, Brown MA: Promise and pitfalls of the Immunochip. Arthritis Res Ther. 2011, 13: 101-","journal-title":"Arthritis Res Ther"},{"key":"95_CR7","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1038\/nature09146","volume":"466","author":"D Pinto","year":"2010","unstructured":"Pinto D, Pagnamenta AT, Klei L, Anney R, Merico D, Regan R, Conroy J, Magalhaes TR, Correia C, Abrahams BS, Almeida J, Bacchelli E, Bader GD, Bailey AJ, Baird G, Battaglia A, Berney T, Bolshakova N, B\u00f6lte S, Bolton PF, Bourgeron T, Brennan S, Brian J, Bryson SE, Carson AR, Casallo G, Casey J, Chung BHY, Cochrane L, Corsello C: Functional impact of global rare copy number variation in autism spectrum disorders. Nature. 2010, 466: 368-372.","journal-title":"Nature"},{"key":"95_CR8","doi-asserted-by":"publisher","first-page":"2870","DOI":"10.1093\/hmg\/ddt136","volume":"22","author":"S Girirajan","year":"2013","unstructured":"Girirajan S, Johnson RL, Tassone F, Balciuniene J, Katiyar N, Fox K, Baker C, Srikanth A, Yeoh KH, Khoo SJ, Nauth TB, Hansen R, Ritchie M, Hertz-Picciotto I, Eichler EE, Pessah IN, Selleck SB: Global increases in both common and rare copy number load associated with autism. Hum Mol Genet. 2013, 22: 2870-2880.","journal-title":"Hum Mol Genet"},{"key":"95_CR9","doi-asserted-by":"publisher","first-page":"1037","DOI":"10.1093\/hmg\/ddg113","volume":"12","author":"TS Furey","year":"2003","unstructured":"Furey TS, Haussler D: Integration of the cytogenetic map with the draft human genome sequence. 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