WBPaper00045622:DR1345_vs_SR708_regulated Transcript levels ascertained on microarrays were considered to display differential expression if their genome-wide false discovery rate q (the expected frequency of false positives for the entire microarray) was less than 5%; in order to further restrict the gene list, a lower threshold (e.g., q < 1% or q = 0) was sometimes used. A separate cohort was expanded and its RNA extracted for each microarray, so that the biological N was equal to the number of assays.
Genes with highly differential expression dependent on the lsq4 QTL when comparing gene expression profile between DR1345 and SR708.
WBPaper00035424:ASER_down Intensities of spot features annotated as Bad or Not Found in the .gpr files were set to 1 to be removed from further analysis, and all of the six processed .gpr data were converted to .mev file with TIGR ExpressConverter ver. 1.7. The .mev files were processed with TIGR MIDAS ver. 2.19 with parameters set as follows: one bad channel tolerance policy as generous, with both of channel flag checked and background unchecked. The data were normalized by lowess normalization with default settings and with block and slide SD regularization. Authors then calculated log2(ASER/ASEL) ratios for each gene on the microarray. For the two pairs of dye-swapped repeats, authors calculated the mean log2(ASER/ASEL) of each repeat, so that up to four log2(ASER/ASEL) values per spot were obtained. Authors then calculated the percentile rank for each gene. Each gene spot detected more than once (18 847 spots) were subjected to MannWhitneys U test to assess whether its percentile rank values are significantly higher compared to the rest of the genes detected in the same experiments. Resulting significance levels are shown by P-values. From the P-values, false discovery rate (FDR) was further calculated by the Benjamini and Hochberg method. Statistical analyses were done by using R software version 2.9.
Genes that showed lower expression level in ASER than in ASEL neuron by mRNA tagging.
WBPaper00035424:ASER_up Intensities of spot features annotated as Bad or Not Found in the .gpr files were set to 1 to be removed from further analysis, and all of the six processed .gpr data were converted to .mev file with TIGR ExpressConverter ver. 1.7. The .mev files were processed with TIGR MIDAS ver. 2.19 with parameters set as follows: one bad channel tolerance policy as generous, with both of channel flag checked and background unchecked. The data were normalized by lowess normalization with default settings and with block and slide SD regularization. Authors then calculated log2(ASER/ASEL) ratios for each gene on the microarray. For the two pairs of dye-swapped repeats, authors calculated the mean log2(ASER/ASEL) of each repeat, so that up to four log2(ASER/ASEL) values per spot were obtained. Authors then calculated the percentile rank for each gene. Each gene spot detected more than once (18 847 spots) were subjected to MannWhitneys U test to assess whether its percentile rank values are significantly higher compared to the rest of the genes detected in the same experiments. Resulting significance levels are shown by P-values. From the P-values, false discovery rate (FDR) was further calculated by the Benjamini and Hochberg method. Statistical analyses were done by using R software version 2.9.
Genes that showed higher expression level in ASER than in ASEL neuron by mRNA tagging.