Effects of filtering by Present call on analysis of microarray experiments

Background Affymetrix $ GeneChips^{®} $ are widely used for expression profiling of tens of thousands of genes. The large number of comparisons can lead to false positives. Various methods have been used to reduce false positives, but they have rarely been compared or quantitatively evaluated. Here...
Ausführliche Beschreibung

Background Affymetrix $ GeneChips^{®} $ are widely used for expression profiling of tens of thousands of genes. The large number of comparisons can lead to false positives. Various methods have been used to reduce false positives, but they have rarely been compared or quantitatively evaluated. Here we describe and evaluate a simple method that uses the detection (Present/Absent) call generated by the Affymetrix microarray suite version 5 software (MAS5) to remove data that is not reliably detected before further analysis, and compare this with filtering by expression level. We explore the effects of various thresholds for removing data in experiments of different size (from 3 to 10 arrays per treatment), as well as their relative power to detect significant differences in expression. Results Our approach sets a threshold for the fraction of arrays called Present in at least one treatment group. This method removes a large percentage of probe sets called Absent before carrying out the comparisons, while retaining most of the probe sets called Present. It preferentially retains the more significant probe sets (p ≤ 0.001) and those probe sets that are turned on or off, and improves the false discovery rate. Permutations to estimate false positives indicate that probe sets removed by the filter contribute a disproportionate number of false positives. Filtering by fraction Present is effective when applied to data generated either by the MAS5 algorithm or by other probe-level algorithms, for example RMA (robust multichip average). Experiment size greatly affects the ability to reproducibly detect significant differences, and also impacts the effect of filtering; smaller experiments (3–5 samples per treatment group) benefit from more restrictive filtering (≥50% Present). Conclusion Use of a threshold fraction of Present detection calls (derived by MAS5) provided a simple method that effectively eliminated from analysis probe sets that are unlikely to be reliable while preserving the most significant probe sets and those turned on or off; it thereby increased the ratio of true positives to false positives. Ausführliche Beschreibung

Autor*in:	McClintick, Jeanette N [verfasserIn] Edenberg, Howard J

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2006

Schlagwörter:	False Discovery Rate Detection Call Robust Multichip Average Experiment Size Small Experiment

Anmerkung:	© McClintick and Edenberg; licensee BioMed Central Ltd. 2006. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (

Übergeordnetes Werk:	Enthalten in: BMC bioinformatics - London : BioMed Central, 2000, 7(2006), 1 vom: 31. Jan.
Übergeordnetes Werk:	volume:7 ; year:2006 ; number:1 ; day:31 ; month:01

Links:	Volltext

DOI / URN:	10.1186/1471-2105-7-49

Katalog-ID:	SPR026831449