WBPaper00005432:xbp-1(zc12)_upregulated

A t-test was used to determine the probability that differences in treatment-induced levels of mRNA between the wild type and xbp-1 mutant were due to chance. A 95% confidence limit was applied. Genes whose activation by tunicamycin treatment is enhanced in xbp-1(zc12)III mutant animals.

WBPaper00005432:xbp-1(zc12)_downregulated

A t-test was used to determine the probability that differences in treatment-induced levels of mRNA between the wild type and xbp-1 mutant were due to chance. A 95% confidence limit was applied. Genes whose activation by tunicamycin treatment is attenuated in xbp-1(zc12)III mutant animals.

WBPaper00039851:Live_C_albicans_vs_HK_OP50

Data were analyzed using Resolver Gene Expression Data Analysis System, version 5.1 (Rosetta Inpharmatics). Three biologic replicates per condition were normalized using the Resolver intensity error model for single color chips. Conditions were compared using Resolver to determine the fold change between conditions for each probe set and to generate a P value using a modified t-test. Probe sets were considered differentially expressed if the fold change was 2-fold or greater (P < 0.01). When comparing datasets, the overlap expected by chance alone was determined in 50 groups of randomly selected C. elegans genes using Regulatory Sequence Analysis Tools (http://rsat.ulb.ac.be/rsat/), a technique that has been used for similar analyses. P values were determined using chi-square tests. Differentially expressed genes in the following exposure comparison:live C. albicans versus heat-killed E. coli.

WBPaper00039851:Live_C_albicans_vs_HK_C_albicans

Data were analyzed using Resolver Gene Expression Data Analysis System, version 5.1 (Rosetta Inpharmatics). Three biologic replicates per condition were normalized using the Resolver intensity error model for single color chips. Conditions were compared using Resolver to determine the fold change between conditions for each probe set and to generate a P value using a modified t-test. Probe sets were considered differentially expressed if the fold change was 2-fold or greater (P < 0.01). When comparing datasets, the overlap expected by chance alone was determined in 50 groups of randomly selected C. elegans genes using Regulatory Sequence Analysis Tools (http://rsat.ulb.ac.be/rsat/), a technique that has been used for similar analyses. P values were determined using chi-square tests. Differentially expressed genes in the following exposure comparison:live C. albicans versus heat-killed C. albicans.

WBPaper00039851:HK_C_albicans_vs_HK_OP50

Data were analyzed using Resolver Gene Expression Data Analysis System, version 5.1 (Rosetta Inpharmatics). Three biologic replicates per condition were normalized using the Resolver intensity error model for single color chips. Conditions were compared using Resolver to determine the fold change between conditions for each probe set and to generate a P value using a modified t-test. Probe sets were considered differentially expressed if the fold change was 2-fold or greater (P < 0.01). When comparing datasets, the overlap expected by chance alone was determined in 50 groups of randomly selected C. elegans genes using Regulatory Sequence Analysis Tools (http://rsat.ulb.ac.be/rsat/), a technique that has been used for similar analyses. P values were determined using chi-square tests. Differentially expressed genes in the following exposure comparison :heat-killed C. albicans versus heat-killed E. coli.

WBPaper00037113:CPF_16C_up-regulated

The Rank Product package was used to identify the differentially expressed genes between controls and treatment in each experiment. Briefly, genes were ranked based on up- or downregulation by the treatment in each experiment. Then, for each gene a combined probability was calculated as a rank product (RP). The RP values were used to rank the genes based on how likely it was to observe them by chance at that particular position on the list of differentially expressed genes. The RP can be interpreted as a p-value. To determine significance levels, the RP method uses a permutation-based estimation procedure to transform the p-value into an e-value that addresses the multiple testing problem derived from testing many genes simultaneously. Genes with a percentage of false-positives (PFP) < 0.05 were considered differentially expressed between treatments and control in each experiment. This method has the advantage to identify genes with a response to the toxicants even when the absolute effect of the response was low. Because authors used sub-lethal concentrations of the toxicants, methods that use thresholds based on absolute fold change would not identify small changes in gene expression. Moreover, RP has proved to be a robust method for comparing microarray data from different sources and experiments. Up-regulated genes under 0.5mg/l CPF treatment at 16 centigrade.

WBPaper00037113:CPF_DZN_16C_down-regulated

The Rank Product package was used to identify the differentially expressed genes between controls and treatment in each experiment. Briefly, genes were ranked based on up- or downregulation by the treatment in each experiment. Then, for each gene a combined probability was calculated as a rank product (RP). The RP values were used to rank the genes based on how likely it was to observe them by chance at that particular position on the list of differentially expressed genes. The RP can be interpreted as a p-value. To determine significance levels, the RP method uses a permutation-based estimation procedure to transform the p-value into an e-value that addresses the multiple testing problem derived from testing many genes simultaneously. Genes with a percentage of false-positives (PFP) < 0.05 were considered differentially expressed between treatments and control in each experiment. This method has the advantage to identify genes with a response to the toxicants even when the absolute effect of the response was low. Because authors used sub-lethal concentrations of the toxicants, methods that use thresholds based on absolute fold change would not identify small changes in gene expression. Moreover, RP has proved to be a robust method for comparing microarray data from different sources and experiments. Down-Regulated genes under 0.5mg/l CPF+ 1 mg/l DZN treatment at 16 centigrade.

WBPaper00037113:DZN_16C_down-regulated

The Rank Product package was used to identify the differentially expressed genes between controls and treatment in each experiment. Briefly, genes were ranked based on up- or downregulation by the treatment in each experiment. Then, for each gene a combined probability was calculated as a rank product (RP). The RP values were used to rank the genes based on how likely it was to observe them by chance at that particular position on the list of differentially expressed genes. The RP can be interpreted as a p-value. To determine significance levels, the RP method uses a permutation-based estimation procedure to transform the p-value into an e-value that addresses the multiple testing problem derived from testing many genes simultaneously. Genes with a percentage of false-positives (PFP) < 0.05 were considered differentially expressed between treatments and control in each experiment. This method has the advantage to identify genes with a response to the toxicants even when the absolute effect of the response was low. Because authors used sub-lethal concentrations of the toxicants, methods that use thresholds based on absolute fold change would not identify small changes in gene expression. Moreover, RP has proved to be a robust method for comparing microarray data from different sources and experiments. Down-regulated genes under 1 mg/l DZN treatment at 16 centigrade.

WBPaper00037113:DZN_16C_up-regulated

The Rank Product package was used to identify the differentially expressed genes between controls and treatment in each experiment. Briefly, genes were ranked based on up- or downregulation by the treatment in each experiment. Then, for each gene a combined probability was calculated as a rank product (RP). The RP values were used to rank the genes based on how likely it was to observe them by chance at that particular position on the list of differentially expressed genes. The RP can be interpreted as a p-value. To determine significance levels, the RP method uses a permutation-based estimation procedure to transform the p-value into an e-value that addresses the multiple testing problem derived from testing many genes simultaneously. Genes with a percentage of false-positives (PFP) < 0.05 were considered differentially expressed between treatments and control in each experiment. This method has the advantage to identify genes with a response to the toxicants even when the absolute effect of the response was low. Because authors used sub-lethal concentrations of the toxicants, methods that use thresholds based on absolute fold change would not identify small changes in gene expression. Moreover, RP has proved to be a robust method for comparing microarray data from different sources and experiments. Up-regulated genes under 1 mg/l DZN treatment at 16 centigrade

WBPaper00037113:CPF_DZN_16C_up-regulated

The Rank Product package was used to identify the differentially expressed genes between controls and treatment in each experiment. Briefly, genes were ranked based on up- or downregulation by the treatment in each experiment. Then, for each gene a combined probability was calculated as a rank product (RP). The RP values were used to rank the genes based on how likely it was to observe them by chance at that particular position on the list of differentially expressed genes. The RP can be interpreted as a p-value. To determine significance levels, the RP method uses a permutation-based estimation procedure to transform the p-value into an e-value that addresses the multiple testing problem derived from testing many genes simultaneously. Genes with a percentage of false-positives (PFP) < 0.05 were considered differentially expressed between treatments and control in each experiment. This method has the advantage to identify genes with a response to the toxicants even when the absolute effect of the response was low. Because authors used sub-lethal concentrations of the toxicants, methods that use thresholds based on absolute fold change would not identify small changes in gene expression. Moreover, RP has proved to be a robust method for comparing microarray data from different sources and experiments. Up-Regulated genes under 0.5mg/l CPF+ 1 mg/l DZN treatment at 16 centigrade.