Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells-5

) of two different samples on Affymetrix (a) and Illumina (b) platforms. The blue line on each plot represents a regression line that best fits the plotted set of points. Both array types provide high inter-replicates reproducibility of the relative gene expression intensities.<p><b>Copyright information:</b></p><p>Taken from "Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells"</p><p>http://www.biomedcentral.com/1471-2164/9/302</p><p>BMC Genomics 2008;9():302-302.</p><p>Published online 25 Jun 2008</p><p>PMCID:PMC2464609.</p><p></p

Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells-4

Examined; Genes present in the top-left and bottom right quarters of each plots show changes in opposite direction. These genes are expected to overlap by chance.<p><b>Copyright information:</b></p><p>Taken from "Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells"</p><p>http://www.biomedcentral.com/1471-2164/9/302</p><p>BMC Genomics 2008;9():302-302.</p><p>Published online 25 Jun 2008</p><p>PMCID:PMC2464609.</p><p></p

Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells-0

) of two different samples on Affymetrix (a) and Illumina (b) platforms. The blue line on each plot represents a regression line that best fits the plotted set of points. Both array types provide high inter-replicates reproducibility of the relative gene expression intensities.<p><b>Copyright information:</b></p><p>Taken from "Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells"</p><p>http://www.biomedcentral.com/1471-2164/9/302</p><p>BMC Genomics 2008;9():302-302.</p><p>Published online 25 Jun 2008</p><p>PMCID:PMC2464609.</p><p></p

Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells-3

He list was constituted by selecting DEG (Pc < 0.05), then within this list genes were ranked according to decreasing fold change. The number of overlapping genes between lists was calculated for increasing list size. When the number of probes in the lists was approximately 3800, the number of overlapping genes reached a plateau. The "best 3800" set of probes was defined accordingly.<p><b>Copyright information:</b></p><p>Taken from "Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells"</p><p>http://www.biomedcentral.com/1471-2164/9/302</p><p>BMC Genomics 2008;9():302-302.</p><p>Published online 25 Jun 2008</p><p>PMCID:PMC2464609.</p><p></p

The ability of ASE and GTE analysis to detect significantly associated rSNPs at different MAF.

<p>Fractions of rSNPs are shown for different minor allele frequencies (MAF) with significant association signals according to a Bonferroni-corrected p-value of 0.05. Each data point underlying the curves represents the fraction of significant associations within a 1% MAF bin. Sliding 5% MAF window averages are plotted for different sample sizes analyzed by ASE and GTE. Both methods detect a lower fraction of low frequency rSNPs, compared to the fraction of all the SNPs at the same frequency (black line). The ASE method detects a higher fraction of the SNPs (solid lines) with a MAF <15% than GTE (dashed lines) regardless of sample size except for the largest GTE sample set.</p

Overlap of significantly associated rSNPs identified by ASE and GTE.

<p>The percentage of overlapping rSNPs detected by allele-specific expression (ASE) and genotype expression (GTE) analysis is plotted for varying numbers of samples. The top 9536 SNPs from the GTE analysis are compared with the top 38203 SNPs from the ASE analysis, which corresponds to a Bonferroni threshold of p = 0.05 for a GTE sample size of 395 and an ASE sample size of 188. The p-value cut-offs were adapted so that the same SNP top-list sizes were obtained at all sample sizes for both GTE (p-value of 1.17E-7, 1.06E-4, 1.93E-3, 6.12E-3 for n = 395, n = 188, n = 95, and n = 50 respectively) and ASE (p-value of 8.06E-8, 9.35E-5, 4.90E-3 for n = 188, n = 95, and n = 50 respectively). The vertical axes show the percentage of SNPs in the top-lists detected by both GTE and ASE analysis and the horizontal axes show the number of samples analyzed using GTE and ASE, respectively. The percentage overlap is calculated by dividing the number of overlaps with the number of top SNPs in the GTE analysis. In (A), each line shows the effect on the number of overlapping SNPs detected by ASE analysis of a specific sample size when the sample size in GTE analysis was increased. In (B), each line shows the effect on the number of overlapping rSNPs detected by GTE analysis of a specific sample size when the samples size in ASE analysis is increased.</p