For each transcript represented on the microarray, authors first used all 18 data points from all of the 18 microarrays to calculate its average in-stage standard deviation as SD=SQRT((i=1-K (ni-1)SDi2)/(N-K)), degree of freedom (df)=N-K, where K is the number of developmental stages in which the given transcript had at least one non-missing log2(IP/Total) value; ni is the number of non-missing values in stage i among the K stages; SDi is the standard deviation of the log2(IP/Total) values from all the replicates of stage i; N is the total number of non-missing values for this transcript at all stages. A transcript must have at least one stage with at least two non-missing values to be testable. All of the non-missing values of a transcript at each stage were averaged to generate the stage-average values (Mi for stage i). The standard error of Mi was calculated as SEi=SD/SQRT(ni) (df=N-K), where SD is the average in-stage standard deviation calculated above and ni is the number of non-missing values at stage i, as explained above. Based on the SEi, a one-tailed Students t-test was used to calculate the P-value of enrichment in stage i (Test if Mi>0). The T statistic was constructed as T=Mi/SEi (df=N-K). Mi>0 and enrichment P<0.001 were used as the threshold of enrichment for each stage.
miRNA targets that are significantly enriched at L1 larva stage. To generate a global view of the dynamics of miRNA-mediated regulation of gene expression during C. elegans development, authors analyzed the mRNAs in the AIN-2-GFP IP results from five developmental stages. The magnitude of the combined interaction of miRNAs with a given target mRNA was assessed by measuring the fold enrichment of that mRNA in AIN-2 IP samples, relative to the abundance of the mRNA in the corresponding total lysate. Because this enrichment in the IP sample versus total lysate directly reflects the miRISC-associated fraction of a given mRNA, high enrichment indicates the likelihood of strong miRNA-mediated regulation of the mRNA, whereas low or negative enrichment indicates the likelihood of weak or absent miRNA regulation of the mRNA. It is also possible that poor enrichment could reflect interactions that occur only in a rare subset of cells at any given stage of development. Transcripts that were significantly enriched (0
WBPaper00035084:L3_enriched_AIN-2_IP For each transcript represented on the microarray, authors first used all 18 data points from all of the 18 microarrays to calculate its average in-stage standard deviation as SD=SQRT((i=1-K (ni-1)SDi2)/(N-K)), degree of freedom (df)=N-K, where K is the number of developmental stages in which the given transcript had at least one non-missing log2(IP/Total) value; ni is the number of non-missing values in stage i among the K stages; SDi is the standard deviation of the log2(IP/Total) values from all the replicates of stage i; N is the total number of non-missing values for this transcript at all stages. A transcript must have at least one stage with at least two non-missing values to be testable. All of the non-missing values of a transcript at each stage were averaged to generate the stage-average values (Mi for stage i). The standard error of Mi was calculated as SEi=SD/SQRT(ni) (df=N-K), where SD is the average in-stage standard deviation calculated above and ni is the number of non-missing values at stage i, as explained above. Based on the SEi, a one-tailed Students t-test was used to calculate the P-value of enrichment in stage i (Test if Mi>0). The T statistic was constructed as T=Mi/SEi (df=N-K). Mi>0 and enrichment P<0.001 were used as the threshold of enrichment for each stage.
miRNA targets that are significantly enriched at L3 larva stage. To generate a global view of the dynamics of miRNA-mediated regulation of gene expression during C. elegans development, authors analyzed the mRNAs in the AIN-2-GFP IP results from five developmental stages. The magnitude of the combined interaction of miRNAs with a given target mRNA was assessed by measuring the fold enrichment of that mRNA in AIN-2 IP samples, relative to the abundance of the mRNA in the corresponding total lysate. Because this enrichment in the IP sample versus total lysate directly reflects the miRISC-associated fraction of a given mRNA, high enrichment indicates the likelihood of strong miRNA-mediated regulation of the mRNA, whereas low or negative enrichment indicates the likelihood of weak or absent miRNA regulation of the mRNA. It is also possible that poor enrichment could reflect interactions that occur only in a rare subset of cells at any given stage of development. Transcripts that were significantly enriched (0
WBPaper00035084:L4_enriched_AIN-2_IP For each transcript represented on the microarray, authors first used all 18 data points from all of the 18 microarrays to calculate its average in-stage standard deviation as SD=SQRT((i=1-K (ni-1)SDi2)/(N-K)), degree of freedom (df)=N-K, where K is the number of developmental stages in which the given transcript had at least one non-missing log2(IP/Total) value; ni is the number of non-missing values in stage i among the K stages; SDi is the standard deviation of the log2(IP/Total) values from all the replicates of stage i; N is the total number of non-missing values for this transcript at all stages. A transcript must have at least one stage with at least two non-missing values to be testable. All of the non-missing values of a transcript at each stage were averaged to generate the stage-average values (Mi for stage i). The standard error of Mi was calculated as SEi=SD/SQRT(ni) (df=N-K), where SD is the average in-stage standard deviation calculated above and ni is the number of non-missing values at stage i, as explained above. Based on the SEi, a one-tailed Students t-test was used to calculate the P-value of enrichment in stage i (Test if Mi>0). The T statistic was constructed as T=Mi/SEi (df=N-K). Mi>0 and enrichment P<0.001 were used as the threshold of enrichment for each stage.
miRNA targets that are significantly enriched at L4 larva stage. To generate a global view of the dynamics of miRNA-mediated regulation of gene expression during C. elegans development, authors analyzed the mRNAs in the AIN-2-GFP IP results from five developmental stages. The magnitude of the combined interaction of miRNAs with a given target mRNA was assessed by measuring the fold enrichment of that mRNA in AIN-2 IP samples, relative to the abundance of the mRNA in the corresponding total lysate. Because this enrichment in the IP sample versus total lysate directly reflects the miRISC-associated fraction of a given mRNA, high enrichment indicates the likelihood of strong miRNA-mediated regulation of the mRNA, whereas low or negative enrichment indicates the likelihood of weak or absent miRNA regulation of the mRNA. It is also possible that poor enrichment could reflect interactions that occur only in a rare subset of cells at any given stage of development. Transcripts that were significantly enriched (0
WBPaper00035084:embryo_enriched_AIN-2_IP For each transcript represented on the microarray, authors first used all 18 data points from all of the 18 microarrays to calculate its average in-stage standard deviation as SD=SQRT((i=1-K (ni-1)SDi2)/(N-K)), degree of freedom (df)=N-K, where K is the number of developmental stages in which the given transcript had at least one non-missing log2(IP/Total) value; ni is the number of non-missing values in stage i among the K stages; SDi is the standard deviation of the log2(IP/Total) values from all the replicates of stage i; N is the total number of non-missing values for this transcript at all stages. A transcript must have at least one stage with at least two non-missing values to be testable. All of the non-missing values of a transcript at each stage were averaged to generate the stage-average values (Mi for stage i). The standard error of Mi was calculated as SEi=SD/SQRT(ni) (df=N-K), where SD is the average in-stage standard deviation calculated above and ni is the number of non-missing values at stage i, as explained above. Based on the SEi, a one-tailed Students t-test was used to calculate the P-value of enrichment in stage i (Test if Mi>0). The T statistic was constructed as T=Mi/SEi (df=N-K). Mi>0 and enrichment P<0.001 were used as the threshold of enrichment for each stage.
miRNA targets that are significantly enriched at embryo stage. To generate a global view of the dynamics of miRNA-mediated regulation of gene expression during C. elegans development, authors analyzed the mRNAs in the AIN-2-GFP IP results from five developmental stages. The magnitude of the combined interaction of miRNAs with a given target mRNA was assessed by measuring the fold enrichment of that mRNA in AIN-2 IP samples, relative to the abundance of the mRNA in the corresponding total lysate. Because this enrichment in the IP sample versus total lysate directly reflects the miRISC-associated fraction of a given mRNA, high enrichment indicates the likelihood of strong miRNA-mediated regulation of the mRNA, whereas low or negative enrichment indicates the likelihood of weak or absent miRNA regulation of the mRNA. It is also possible that poor enrichment could reflect interactions that occur only in a rare subset of cells at any given stage of development. Transcripts that were significantly enriched (0
WBPaper00035084:L2_enriched_AIN-2_IP For each transcript represented on the microarray, authors first used all 18 data points from all of the 18 microarrays to calculate its average in-stage standard deviation as SD=SQRT((i=1-K (ni-1)SDi2)/(N-K)), degree of freedom (df)=N-K, where K is the number of developmental stages in which the given transcript had at least one non-missing log2(IP/Total) value; ni is the number of non-missing values in stage i among the K stages; SDi is the standard deviation of the log2(IP/Total) values from all the replicates of stage i; N is the total number of non-missing values for this transcript at all stages. A transcript must have at least one stage with at least two non-missing values to be testable. All of the non-missing values of a transcript at each stage were averaged to generate the stage-average values (Mi for stage i). The standard error of Mi was calculated as SEi=SD/SQRT(ni) (df=N-K), where SD is the average in-stage standard deviation calculated above and ni is the number of non-missing values at stage i, as explained above. Based on the SEi, a one-tailed Students t-test was used to calculate the P-value of enrichment in stage i (Test if Mi>0). The T statistic was constructed as T=Mi/SEi (df=N-K). Mi>0 and enrichment P<0.001 were used as the threshold of enrichment for each stage.
miRNA targets that are significantly enriched at L2 larva stage. To generate a global view of the dynamics of miRNA-mediated regulation of gene expression during C. elegans development, authors analyzed the mRNAs in the AIN-2-GFP IP results from five developmental stages. The magnitude of the combined interaction of miRNAs with a given target mRNA was assessed by measuring the fold enrichment of that mRNA in AIN-2 IP samples, relative to the abundance of the mRNA in the corresponding total lysate. Because this enrichment in the IP sample versus total lysate directly reflects the miRISC-associated fraction of a given mRNA, high enrichment indicates the likelihood of strong miRNA-mediated regulation of the mRNA, whereas low or negative enrichment indicates the likelihood of weak or absent miRNA regulation of the mRNA. It is also possible that poor enrichment could reflect interactions that occur only in a rare subset of cells at any given stage of development. Transcripts that were significantly enriched (0
WBPaper00049311:AgNO3_regulated Data were screened for differences of each treatment (Ag-MNP, sAg-MNP, and AgNO3) from control using one-way ANOVA with contrasts. The false discovery rate (FDR) threshold was set at 0.2 and the fold change was required to be greater than 1.5, and a P-value <= 0.05. The FDR of 0.2 was selected to balance the protection against false positives while minimizing the rate of false negatives. Using Partek, genes that were significantly different from control in at least one treatment were then analyzed using agglomerative hierarchical cluster analysis (HCA). HCA is a 2-Pass clustering method; the first pass is a K-means clustering and in the second pass the K-means clusters are joined by agglomerative clustering.
Transcripts that showed significantly altered expression after 48 hour exposure to AgNO3.
WBPaper00049311:sAg-MNP_regulated Data were screened for differences of each treatment (Ag-MNP, sAg-MNP, and AgNO3) from control using one-way ANOVA with contrasts. The false discovery rate (FDR) threshold was set at 0.2 and the fold change was required to be greater than 1.5, and a P-value <= 0.05. The FDR of 0.2 was selected to balance the protection against false positives while minimizing the rate of false negatives. Using Partek, genes that were significantly different from control in at least one treatment were then analyzed using agglomerative hierarchical cluster analysis (HCA). HCA is a 2-Pass clustering method; the first pass is a K-means clustering and in the second pass the K-means clusters are joined by agglomerative clustering.
Transcripts that showed significantly altered expression after 48 hour exposure to sAg-MNP.