Project description:Microarrays have been widely used for the analysis of gene expression and several commercial platforms are available. The combined use of multiple platforms can overcome the inherent biases of each approach, and may represent an alternative that is complementary to RT-PCR for identification of the more robust changes in gene expression profiles. In this paper, we combined statistical and functional analysis for the cross platform validation of two oligonucleotide-based technologies, Affymetrix (AFFX) and Applied Biosystems (ABI), and for the identification of differentially expressed genes. In this study, we analysed differentially expressed genes after treatment of an ovarian carcinoma cell line with a cell cycle inhibitor. Treated versus control RNA was analysed for expression of 16425 genes represented on both platforms. We assessed reproducibility between replicates for each platform using CAT plots, and we found it high for both, with better scores for AFFX. We then applied integrative correlation analysis to assess reproducibility of gene expression patterns across studies, bypassing the need for normalizing expression measurements across platforms. We identified 930 genes as differentially expressed on AFFX and 908 on ABI, with ~80% common to both platforms. Despite the different absolute values, the range of intensities of the differentially expressed genes detected by each platform was similar. ABI showed a slightly higher dynamic range in FC values, which might be associated with its detection system. 62/66 genes identified as differentially expressed by Microarray were confirmed by RT-PCR. In this study we present a cross-platform validation of two oligonucleotide-based technologies, AFFX and ABI. We found good reproducibility between replicates, and showed that both platforms can be used to select differentially expressed genes with substantial agreement. Pathway analysis of the affected functions identified themes well in agreement with those expected for a cell cycle inhibitor, suggesting that this procedure is appropriate to facilitate the identification of biologically relevant signatures associated with compound treatment. The high rate of confirmation found for both common and platform-specific genes suggests that the combination of platforms may overcome biases related to probe design and technical features, thereby accelerating the identification of trustworthy differentially expressed genes. accepted for publication on BMC Bioinformatics Keywords: platform comparison

Project description:Formalin-fixed, paraffin-embedded (FFPE) archival tissue is an important source of DNA material. The most commonly used technique to identify copy number aberrations from chromosomal DNA in tumorigenesis is array comparative genomic hybridization (aCGH). Although copy number analysis using DNA from FFPE archival tissue is challenging, several research groups have reported high quality and reproducible DNA copy number results using aCGH. Aim of the present study is to compare aCGH platforms suitable for copy number analysis using FFPE derived DNA. Two dual channel aCGH platforms (Agilent and NimbleGen) and a single channel SNP based platform (Affymetrix), were evaluated using seven FFPE colon cancer samples, median absolute deviation (MAD), deflection, signal-to-noise ratio (SNR) and DNA input requirements were used as quality criteria. Large differences were observed in MAD values and deflection between platforms; Agilent and NimbleGen showed better MAD values (0.13 for both) compared to Affymetrix (0.22). Contrary, Affymetrix showed a better deflection of 0.94, followed by 0.71 for Agilent and 0.51 for NimbleGen. Since the deflection compensates for the MAD the Signal to Noise Ratios (SNR) were comparable; Agilent ranks first, Affymetrix second and NimbleGen third with SNRs of 3.9, 3.6 and 3.3 respectively. DNA input amounts of 40ng are sufficient for high quality profiles with Affymetrix. For Agilent DNA input amounts of 50ng are sufficient for high quality profiles. For results of similar quality NimbleGen requires at least 100ng. Copy number analysis using DNA derived from FFPE archival material is feasible and shows reproducible results on high-resolution copy number platforms. Input amounts of DNA from FFPE material lower than recommended still yield high quality profiles without additional amplification steps. Overall study comprises 6 samples analyzed across three platforms with an additional dilution range (5 concentrations) of a seventh sample on two platforms. This Series represents NimbleGen platform-derived data.

Project description:Formalin-fixed, paraffin-embedded (FFPE) archival tissue is an important source of DNA material. The most commonly used technique to identify copy number aberrations from chromosomal DNA in tumorigenesis is array comparative genomic hybridization (aCGH). Although copy number analysis using DNA from FFPE archival tissue is challenging, several research groups have reported high quality and reproducible DNA copy number results using aCGH. Aim of the present study is to compare aCGH platforms suitable for copy number analysis using FFPE derived DNA. Two dual channel aCGH platforms (Agilent and NimbleGen) and a single channel SNP based platform (Affymetrix), were evaluated using seven FFPE colon cancer samples, median absolute deviation (MAD), deflection, signal-to-noise ratio (SNR) and DNA input requirements were used as quality criteria. Large differences were observed in MAD values and deflection between platforms; Agilent and NimbleGen showed better MAD values (0.13 for both) compared to Affymetrix (0.22). Contrary, Affymetrix showed a better deflection of 0.94, followed by 0.71 for Agilent and 0.51 for NimbleGen. Since the deflection compensates for the MAD the Signal to Noise Ratios (SNR) were comparable; Agilent ranks first, Affymetrix second and NimbleGen third with SNRs of 3.9, 3.6 and 3.3 respectively. DNA input amounts of 40ng are sufficient for high quality profiles with Affymetrix. For Agilent DNA input amounts of 50ng are sufficient for high quality profiles. For results of similar quality NimbleGen requires at least 100ng. Copy number analysis using DNA derived from FFPE archival material is feasible and shows reproducible results on high-resolution copy number platforms. Input amounts of DNA from FFPE material lower than recommended still yield high quality profiles without additional amplification steps. Overall study comprises 6 samples analyzed across three platforms with an additional dilution range (5 concentrations) of a seventh sample on two platforms. This Series represents Agilent platform-derived data.

Project description:Microarray expression profiling has become a valuable tool in the evaluation of the genetic consequences of metabolic disease. Although 3’-biased gene expression microarray platforms were the first generation to have widespread availability, newer platforms are gradually emerging that have more up-to-date content and/or higher cost efficiency. Deciphering the relative strengths and weaknesses of these various platforms for metabolic pathway level analyses can be daunting. We sought to determine the practical strengths and weaknesses of four leading commercially-available expression array platforms relative to biologic investigations, as well as assess the feasibility of cross-platform data integration for purposes of biochemical pathway analyses. METHODS: Liver RNA from B6.Alb/cre,Pdss2loxP/loxP mice having primary Coenzyme Q deficiency was extracted either at baseline or following treatment with an antioxidant/antihyperlipidemic agent, probucol. Target RNA samples were prepared and hybridized to Affymetrix 430 2.0, Affymetrix Gene 1.0 ST, Affymetrix Exon 1.0 ST, and Illumina Mouse WG-6 expression arrays. Probes on all platforms were re-mapped to coding sequences in the current version of the mouse genome. Data processing and statistical analysis were performed by R/Bioconductor functions, and pathway analyses were carried out by KEGG Atlas and GSEA. RESULTS: Expression measurements were generally consistent across platforms. However, intensive probe-level comparison suggested that differences in probe locations were a major source of inter-platform variance. In addition, genes expressed at low or intermediate levels had lower inter-platform reproducibility than highly expressed genes. All platforms showed similar patterns of differential expression between sample groups, with ‘steroid biosynthesis’ consistently identified as the most down-regulated metabolic pathway by probucol treatment. CONCLUSIONS: This work offers a timely guide for metabolic disease investigators to enable informed end-user decisions regarding choice of expression microarray platform best-suited to specific research project goals. Successful cross-platform integration of biochemical pathway expression data is also demonstrated, especially for well-annotated and highly-expressed genes. However, integration of gene-level expression data is limited by individual platform probe design and the expression level of target genes. Cross-platform analyses of biochemical pathway data will require additional data processing and novel computational bioinformatics tools to address unique statistical challenges.

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Dillution series comparison of Affymetrix and Illumina Expression Platforms

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