scholarly journals Physical-Chemistry-Based Analysis of Affymetrix Microarray Data

2006 ◽  
Vol 110 (45) ◽  
pp. 22786-22795 ◽  
Author(s):  
T. Heim ◽  
L.-C. Tranchevent ◽  
E. Carlon ◽  
G. T. Barkema
Keyword(s):  
Physical Chemistry ◽  
Microarray Data ◽  
Affymetrix Microarray ◽  
Affymetrix Microarray Data

scholarly journals Analysis of probe level patterns in Affymetrix microarray data

2007 ◽  
Vol 8 (1) ◽  
pp. 146 ◽  
Author(s):  
Alexander C Cambon ◽  
Abdelnaby Khalyfa ◽  
Nigel GF Cooper ◽  
Caryn M Thompson
Keyword(s):  
Microarray Data ◽  
Affymetrix Microarray ◽  
Affymetrix Microarray Data

Combining Hadoop and GPU to preprocess large Affymetrix microarray data

2014 ◽  
Author(s):  
Sufeng Niu ◽  
Guangyu Yang ◽  
Nilim Sarma ◽  
Pengfei Xuan ◽  
Melissa C. Smith ◽  
...  
Keyword(s):  
Microarray Data ◽  
Affymetrix Microarray ◽  
Affymetrix Microarray Data

scholarly journals MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

2014 ◽  
Vol 15 (1) ◽  
pp. 69 ◽  
Author(s):  
Zhuohui Gan ◽  
Jianwu Wang ◽  
Nathan Salomonis ◽  
Jennifer C Stowe ◽  
Gabriel G Haddad ◽  
...  
Keyword(s):  
Microarray Data ◽  
Affymetrix Microarray ◽  
Affymetrix Microarray Data ◽  
Meta Analyses

scholarly journals affyPara—a Bioconductor Package for Parallelized Preprocessing Algorithms of Affymetrix Microarray Data

2009 ◽  
Vol 3 ◽  
pp. BBI.S3060 ◽  
Author(s):  
Markus Schmidberger ◽  
Esmeralda Vicedo ◽  
Ulrich Mansmann
Keyword(s):  
Microarray Data ◽  
Main Memory ◽  
Computer Hardware ◽  
Data Partition ◽  
Bioconductor Package ◽  
Data Repositories ◽  
Affymetrix Microarray ◽  
Memory Problems ◽  
Affymetrix Microarray Data ◽  
Bioconductor Project

Microarray data repositories as well as large clinical applications of gene expression allow to analyse several hundreds of microarrays at one time. The preprocessing of large amounts of microarrays is still a challenge. The algorithms are limited by the available computer hardware. For example, building classification or prognostic rules from large microarray sets will be very time consuming. Here, preprocessing has to be a part of the cross-validation and resampling strategy which is necessary to estimate the rule's prediction quality honestly. This paper proposes the new Bioconductor package affyPara for parallelized preprocessing of Affymetrix microarray data. Partition of data can be applied on arrays and parallelization of algorithms is a straightforward consequence. The partition of data and distribution to several nodes solves the main memory problems and accelerates preprocessing by up to the factor 20 for 200 or more arrays. affyPara is a free and open source package, under GPL license, available form the Bioconductor project at www.bioconductor.org . A user guide and examples are provided with the package.

scholarly journals Celsius: a community resource for Affymetrix microarray data

2007 ◽  
Vol 8 (6) ◽  
pp. R112 ◽  
Author(s):  
Allen Day ◽  
Marc RJ Carlson ◽  
Jun Dong ◽  
Brian D O'Connor ◽  
Stanley F Nelson
Keyword(s):  
Microarray Data ◽  
Community Resource ◽  
Affymetrix Microarray ◽  
Affymetrix Microarray Data

scholarly journals Comparison of Nanostring nCounter® Data on FFPE Colon Cancer Samples and Affymetrix Microarray Data on Matched Frozen Tissues

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0153784 ◽  
Author(s):  
Xi Chen ◽  
Natasha G. Deane ◽  
Keeli B. Lewis ◽  
Jiang Li ◽  
Jing Zhu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Microarray Data ◽  
Affymetrix Microarray ◽  
Affymetrix Microarray Data

scholarly journals GIANT: galaxy-based tool for interactive analysis of transcriptomic data

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jimmy Vandel ◽  
Céline Gheeraert ◽  
Bart Staels ◽  
Jérôme Eeckhoute ◽  
Philippe Lefebvre ◽  
...  
Keyword(s):  
Data Mining ◽  
Biomedical Research ◽  
Microarray Data ◽  
Rna Seq ◽  
Affymetrix Microarray ◽  
Transcriptomic Data ◽  
Interactive Analysis ◽  
Affymetrix Microarray Data

AbstractTranscriptomic analyses are broadly used in biomedical research calling for tools allowing biologists to be directly involved in data mining and interpretation. We present here GIANT, a Galaxy-based tool for Interactive ANalysis of Transcriptomic data, which consists of biologist-friendly tools dedicated to analyses of transcriptomic data from microarray or RNA-seq analyses. GIANT is organized into modules allowing researchers to tailor their analyses by choosing the specific set of tool(s) to analyse any type of preprocessed transcriptomic data. It also includes a series of tools dedicated to the handling of raw Affymetrix microarray data. GIANT brings easy-to-use solutions to biologists for transcriptomic data mining and interpretation.

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