- WBPaper00041075:hcf-1(-)_skn-1(+)_downregulated
N.A. Reanalyzing previously published data.Authors compared the genes differentially expressed in hcf-1(pk924) mutant worms relative to N2 wild-type worms (referred to as hcf-1(-) profile) (Rizki et al., 2011) to those changed in wild-type worms treated with control RNAi relative to skn-1 RNAi (referred to as skn-1 (+) profile) (Oliveira et al., 2009).
Genes that were down regulated in the absence of hcf-1 and the presence of skn-1.
- WBPaper00041075:hcf-1(-)_skn-1(+)_upregulated
N.A. Reanalyzing previously published data.Authors compared the genes differentially expressed in hcf-1(pk924) mutant worms relative to N2 wild-type worms (referred to as hcf-1(-) profile) (Rizki et al., 2011) to those changed in wild-type worms treated with control RNAi relative to skn-1 RNAi (referred to as skn-1 (+) profile) (Oliveira et al., 2009).
Genes that were up regulated in the absence of hcf-1 and the presence of skn-1.
- WBPaper00056443:DietaryRestriction_downregulated
Bioconductor package edgeR, p < 0.05.
Transcripts that showed significantly decreased expression after N2 animals were under dietary restriction (DR, OP50 OD = 0.1) from 3-day post L4 till 6-day post L4 adult hermaphrodite stage, comparing to under ad libtum (AL, OP50 OD = 3) condition.
- WBPaper00056443:DietaryRestriction_upregulated
Bioconductor package edgeR, p < 0.05.
Transcripts that showed significantly increased expression after N2 animals were under dietary restriction (DR, OP50 OD = 0.1) from 3-day post L4 till 6-day post L4 adult hermaphrodite stage, comparing to under ad libtum (AL, OP50 OD = 3) condition.
- WBPaper00056443:sek-1(km4)_downregulated
Bioconductor package edgeR, p < 0.05.
Transcripts that showed significantly decreased expression in sek-1(km4) animals comparing to in N2 animals under both dietary (DR, OP50 OD = 0.1) and ad libtum (AL, OP50 OD = 3) conditions from 3-day post L4 till 6-day post L4 adult hermaphrodite stage.
- WBPaper00044005:DAF-16_downregulated
Authors reanalyzed raw genome-wide expression data from five studies (McElwee et al., 2003; McElwee et al., 2004; Murphy et al., 2003; Shaw et al., 2007; Troemeletal.,2006) encompassing 75 genome-wide expression profiles, which authors used to construct 46 explicit contrasts between conditions with differing levels of DAF-16 activity. After complete reprocessing of the raw data (array-specific standardization, normalization, and remapping of probes), a log-fold-change and corresponding standard error were calculated for each transcript on each array (or array pair for single-channel technologies). Together, these were converted into a vote value between 1 (highly likely to be downregulated) and +1 (highly likely to be upregulated). The total voting score for each gene was computed as the sum of voting scores for individual experiments, which is robust in the sense that the influence of any individual experiment is limited to a single full vote. An empirical null distribution based on random permutation was created, and all genes were ranked from consistently upregulated (class I) to consistently downregulated (class II). The area under the null distribution (p value) for each gene that served as the basis for assigning genes to class I or class II at a 5% false discovery rate.
Top 50 down regulated genes by DAF-16 based on reanalysis 75 previously published experiments.
- WBPaper00044005:DAF-16_upregulated
Authors reanalyzed raw genome-wide expression data from five studies (McElwee et al., 2003; McElwee et al., 2004; Murphy et al., 2003; Shaw et al., 2007; Troemeletal.,2006) encompassing 75 genome-wide expression profiles, which authors used to construct 46 explicit contrasts between conditions with differing levels of DAF-16 activity. After complete reprocessing of the raw data (array-specific standardization, normalization, and remapping of probes), a log-fold-change and corresponding standard error were calculated for each transcript on each array (or array pair for single-channel technologies). Together, these were converted into a vote value between 1 (highly likely to be downregulated) and +1 (highly likely to be upregulated). The total voting score for each gene was computed as the sum of voting scores for individual experiments, which is robust in the sense that the influence of any individual experiment is limited to a single full vote. An empirical null distribution based on random permutation was created, and all genes were ranked from consistently upregulated (class I) to consistently downregulated (class II). The area under the null distribution (p value) for each gene that served as the basis for assigning genes to class I or class II at a 5% false discovery rate.
Top 50 up regulated genes by DAF-16 based on reanalysis 75 previously published experiments.
- WBPaper00056443:sek-1(km4)_upregulated
Bioconductor package edgeR, p < 0.05.
Transcripts that showed significantly increased expression in sek-1(km4) animals comparing to in N2 animals under both dietary (DR, OP50 OD = 0.1) and ad libtum (AL, OP50 OD = 3) conditions from 3-day post L4 till 6-day post L4 adult hermaphrodite stage.
- WBPaper00031486:daf-16_downregulated
Raw microarray data (cel files) were normalized, fold-changes between genotypes were determined, and global statistical analysis was performed, using a slightly modified version of the recently described Goldenspike methodology implemented in R (version 2.0.1) (Choe et al. 2005). Briefly, this procedure performs eight different normalization routines, which are then used to produce an average fold-change difference and false-discovery rate (q-value) between different genotypes that takes into consideration the variance of probe set intensity across the different normalizations. The Goldenspike methodology has been shown to out-perform most commonly used normalization methods (Choe et al. 2005). The Goldenspike protocol was altered slightly to exclude absent probe sets (those probe sets called absent in all hybridizations by MAS5) prior to the final probe-set-level Loess normalization. This alteration was found to reduce the number of false positives associated with the absent probe sets (Schuster et al. 2007).
Genes showing significantly decreased expression in daf-16(mgDf50);daf-2(e1370) comparing to daf-2(e1370), but not in daf-2(m577).
- WBPaper00031486:daf-16_upregulated
Raw microarray data (cel files) were normalized, fold-changes between genotypes were determined, and global statistical analysis was performed, using a slightly modified version of the recently described Goldenspike methodology implemented in R (version 2.0.1) (Choe et al. 2005). Briefly, this procedure performs eight different normalization routines, which are then used to produce an average fold-change difference and false-discovery rate (q-value) between different genotypes that takes into consideration the variance of probe set intensity across the different normalizations. The Goldenspike methodology has been shown to out-perform most commonly used normalization methods (Choe et al. 2005). The Goldenspike protocol was altered slightly to exclude absent probe sets (those probe sets called absent in all hybridizations by MAS5) prior to the final probe-set-level Loess normalization. This alteration was found to reduce the number of false positives associated with the absent probe sets (Schuster et al. 2007).
Genes showing significantly decreased expression in daf-16(mgDf50);daf-2(e1370) comparing to daf-2(e1370), but not in daf-2(m577).