A dynamic, web-accessible resource to process raw microarray scan data into consolidated gene expression values: importance of replication
Author(s) -
Nolwenn Le Meur
Publication year - 2004
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkh870
Subject(s) - replicate , dna microarray , biology , raw data , replication (statistics) , pipeline (software) , microarray databases , microarray , computational biology , microarray analysis techniques , gene expression profiling , gene chip analysis , data mining , expression (computer science) , gene expression , computer science , gene , bioinformatics , genetics , statistics , mathematics , virology , programming language
We propose a freely accessible web-based pipeline, which processes raw microarray scan data to obtain experimentally consolidated gene expression values. The tool MADSCAN, which stands for MicroArray Data Suites of Computed ANalysis, makes a practical choice among the numerous methods available for filtering, normalizing and scaling of raw microarray expression data in a dynamic and automatic way. Different statistical methods have been adapted to extract reliable information from replicate gene spots as well as from replicate microarrays for each biological situation under study. A carefully constructed experimental design thus allows to detect outlying expression values and to identify statistically significant expression values, together with a list of quality controls with proposed threshold values. The integrated processing procedure described here, based on multiple measurements per gene, is decisive for reliably monitoring subtle gene expression changes typical for most biological events.
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