MOTIVATION: Cross-platform microarray analysis is an increasingly important research tool, but researchers still lack open source tools for storing, integrating and analyzing large amounts of microarray data obtained from different array platforms. RESULTS: An open source integrated microarray database and analysis suite, WebArrayDB (http://www.webarraydb.org), has been developed that features convenient uploading of data for storage in a MIAME (Minimal Information about a Microarray Experiment) compliant fashion, and allows data to be mined with a large variety of R-based tools, including data analysis across multiple platforms. Different methods for probe alignment, normalization and statistical analysis are included to account for systematic bias. Student's t-test, moderated t-tests, non-parametric tests and analysis of variance or covariance (ANOVA/ANCOVA) are among the choices of algorithms for differential analysis of data. Users also have the flexibility to define new factors and create new analysis models to fit complex experimental designs. All data can be queried or browsed through a web browser. The computations can be performed in parallel on symmetric multiprocessing (SMP) systems or Linux clusters. AVAILABILITY: The software package is available for the use on a public web server (http://www.webarraydb.org) or can be downloaded. are available at Bioinformatics online.
MOTIVATION: Cross-platform microarray analysis is an increasingly important research tool, but researchers still lack open source tools for storing, integrating and analyzing large amounts of microarray data obtained from different array platforms. RESULTS: An open source integrated microarray database and analysis suite, WebArrayDB (http://www.webarraydb.org), has been developed that features convenient uploading of data for storage in a MIAME (Minimal Information about a Microarray Experiment) compliant fashion, and allows data to be mined with a large variety of R-based tools, including data analysis across multiple platforms. Different methods for probe alignment, normalization and statistical analysis are included to account for systematic bias. Student's t-test, moderated t-tests, non-parametric tests and analysis of variance or covariance (ANOVA/ANCOVA) are among the choices of algorithms for differential analysis of data. Users also have the flexibility to define new factors and create new analysis models to fit complex experimental designs. All data can be queried or browsed through a web browser. The computations can be performed in parallel on symmetric multiprocessing (SMP) systems or Linux clusters. AVAILABILITY: The software package is available for the use on a public web server (http://www.webarraydb.org) or can be downloaded. are available at Bioinformatics online.
Authors: A Brazma; P Hingamp; J Quackenbush; G Sherlock; P Spellman; C Stoeckert; J Aach; W Ansorge; C A Ball; H C Causton; T Gaasterland; P Glenisson; F C Holstege; I F Kim; V Markowitz; J C Matese; H Parkinson; A Robinson; U Sarkans; S Schulze-Kremer; J Stewart; R Taylor; J Vilo; M Vingron Journal: Nat Genet Date: 2001-12 Impact factor: 38.330
Authors: Qing-Rong Chen; Young K Song; Jun S Wei; Sven Bilke; Shahab Asgharzadeh; Robert C Seeger; Javed Khan Journal: Genomics Date: 2008-07-30 Impact factor: 5.736
Authors: Robert C Gentleman; Vincent J Carey; Douglas M Bates; Ben Bolstad; Marcel Dettling; Sandrine Dudoit; Byron Ellis; Laurent Gautier; Yongchao Ge; Jeff Gentry; Kurt Hornik; Torsten Hothorn; Wolfgang Huber; Stefano Iacus; Rafael Irizarry; Friedrich Leisch; Cheng Li; Martin Maechler; Anthony J Rossini; Gunther Sawitzki; Colin Smith; Gordon Smyth; Luke Tierney; Jean Y H Yang; Jianhua Zhang Journal: Genome Biol Date: 2004-09-15 Impact factor: 13.583
Authors: Jing Guo; Mårten Hammar; Lisa Oberg; Shanmukha S Padmanabhuni; Marcus Bjäreland; Daniel Dalevi Journal: PLoS One Date: 2013-08-12 Impact factor: 3.240
Authors: Lucas B Pontel; Nadia L Scampoli; Steffen Porwollik; Susana K Checa; Michael McClelland; Fernando C Soncini Journal: Microbiology (Reading) Date: 2014-05-23 Impact factor: 2.777
Authors: Cecilia A Silva; Carlos J Blondel; Carolina P Quezada; Steffen Porwollik; Helene L Andrews-Polymenis; Cecilia S Toro; Mercedes Zaldívar; Inés Contreras; Michael McClelland; Carlos A Santiviago Journal: Infect Immun Date: 2011-11-14 Impact factor: 3.441
Authors: Ashley C Bono; Christine E Hartman; Sina Solaimanpour; Hao Tong; Steffen Porwollik; Michael McClelland; Jonathan G Frye; Jan Mrázek; Anna C Karls Journal: J Bacteriol Date: 2017-05-25 Impact factor: 3.490
Authors: Eva Kucerova; Sandra W Clifton; Xiao-Qin Xia; Fred Long; Steffen Porwollik; Lucinda Fulton; Catrina Fronick; Patrick Minx; Kim Kyung; Wesley Warren; Robert Fulton; Dongyan Feng; Aye Wollam; Neha Shah; Veena Bhonagiri; William E Nash; Kymberlie Hallsworth-Pepin; Richard K Wilson; Michael McClelland; Stephen J Forsythe Journal: PLoS One Date: 2010-03-08 Impact factor: 3.240