TY - JOUR
T1 - SegAnnDB
T2 - Interactive Web-based genomic segmentation
AU - Hocking, Toby D.
AU - Boeva, Valentina
AU - Rigaill, Guillem
AU - Schleiermacher, Gudrun
AU - Janoueix-Lerosey, Isabelle
AU - Delattre, Olivier
AU - Richer, Wilfrid
AU - Bourdeaut, Franck
AU - Suguro, Miyuki
AU - Seto, Masao
AU - Bach, Francis
AU - Vert, Jean Philippe
N1 - Funding Information:
V.B. is member of the team ‘Computational Systems Biology of Cancer’, équipe labellisée par la Ligue Nationale Contre le Cancer. G.S. is supported by the Annenberg Foundation. The authors thank Eve Lapouble for help in collecting data.
Funding Information:
Funding: This work was supported by the European Research Council (SIERRA-ERC-239993 to F.B.; SMAC-ERC-280032 to J-P.V.). This work was supported by Digiteo [DIGITEO-BIOVIZ-2009-25D to T.D.H.]; the Annenberg Foundation [to G.S.]; the French Programme Hospitalier de Recherche Clinique [PHRC IC2007-09 to G.S.]; the French National Cancer Institute [INCA-2007-1-RT-4-IC to G.S.]; and the French Anti-Cancer League. This work was supported in part by a grant-in-Aid from the Ministry of Health, Labor and Welfare of Japan, the Ministry of Education, Culture, Sports, Science and Technology of the Japan, the Japan Society for the Promotion of Science (M.Seto), and a Grant-in-Aid for Cancer Research from the Ministry of Health, Labor and Welfare of Japan (M. Seto), a Grant from Takeda Science Foundation (M. Seto). The authors thank the associations ‘‘Les Torocinelles’’, ‘‘Adam’’, and ‘‘Franck, un rayon de Soleil’’ for their financial support.
PY - 2014/6/1
Y1 - 2014/6/1
N2 - Motivation: DNA copy number profiles characterize regions of chromosome gains, losses and breakpoints in tumor genomes. Although many models have been proposed to detect these alterations, it is not clear which model is appropriate before visual inspection the signal, noise and models for a particular profile. Results: We propose SegAnnDB, a Web-based computer vision system for genomic segmentation: first, visually inspect the profiles and manually annotate altered regions, then SegAnnDB determines the precise alteration locations using a mathematical model of the data and annotations. SegAnnDB facilitates collaboration between biologists and bioinformaticians, and uses the University of California, Santa Cruz genome browser to visualize copy number alterations alongside known genes.
AB - Motivation: DNA copy number profiles characterize regions of chromosome gains, losses and breakpoints in tumor genomes. Although many models have been proposed to detect these alterations, it is not clear which model is appropriate before visual inspection the signal, noise and models for a particular profile. Results: We propose SegAnnDB, a Web-based computer vision system for genomic segmentation: first, visually inspect the profiles and manually annotate altered regions, then SegAnnDB determines the precise alteration locations using a mathematical model of the data and annotations. SegAnnDB facilitates collaboration between biologists and bioinformaticians, and uses the University of California, Santa Cruz genome browser to visualize copy number alterations alongside known genes.
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U2 - 10.1093/bioinformatics/btu072
DO - 10.1093/bioinformatics/btu072
M3 - Article
C2 - 24493034
AN - SCOPUS:84901362035
SN - 1367-4803
VL - 30
SP - 1539
EP - 1546
JO - Bioinformatics
JF - Bioinformatics
IS - 11
ER -