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: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
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: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
WBPaper00026952:class_A Raw data from each experiment were downloaded from the Stanford Microarray Database into Excel files and processed as follows: (i) sort by Spot Flag and discard any rows where the Spot Flag value was nonzero, indicating a bad PCR; (ii) sort by Failed and discard any rows where the Failed value was nonzero, indicating abnormal hybridization; (iii) import into a common file for each type of experiment (i.e., lin-14 or lin-4) the columns from each raw experimental file [RAT2(R/G), which shows a log base 2 transformed ratio of normalized red/green signal for each spot; name of spot (Wormbase designation); chromosome location and description (www.wormbase.org)]; (iv) calculate an average RAT2(R/G) based on the 2 or 3 values (avg; any rows which had only one good experimental value were discarded); (v) calculate a standard deviation (stdev) for the average value; (vi) calculate a t value for each spot by using the formula t = avg*[sqrt(n - 1)]/stdev, where n is the number of experiments for which good data exist, sqrt is square root, and stdev is standard deviation; (vii) sort by absolute t value and discard any rows with a t value below 4.303 (below 95% confidence interval for three experiments) or below 12.706 (below 95% confidence interval for two experiments); (viii) sort by absolute average value and discard any rows with average values below 1.0 (less than twofold change compared to control).
Class A gene expression showed down regulation in lin-14(lf) in L1, no change in lin-4(lf) in L2.
WBPaper00026952:class_B Raw data from each experiment were downloaded from the Stanford Microarray Database into Excel files and processed as follows: (i) sort by Spot Flag and discard any rows where the Spot Flag value was nonzero, indicating a bad PCR; (ii) sort by Failed and discard any rows where the Failed value was nonzero, indicating abnormal hybridization; (iii) import into a common file for each type of experiment (i.e., lin-14 or lin-4) the columns from each raw experimental file [RAT2(R/G), which shows a log base 2 transformed ratio of normalized red/green signal for each spot; name of spot (Wormbase designation); chromosome location and description (www.wormbase.org)]; (iv) calculate an average RAT2(R/G) based on the 2 or 3 values (avg; any rows which had only one good experimental value were discarded); (v) calculate a standard deviation (stdev) for the average value; (vi) calculate a t value for each spot by using the formula t = avg*[sqrt(n - 1)]/stdev, where n is the number of experiments for which good data exist, sqrt is square root, and stdev is standard deviation; (vii) sort by absolute t value and discard any rows with a t value below 4.303 (below 95% confidence interval for three experiments) or below 12.706 (below 95% confidence interval for two experiments); (viii) sort by absolute average value and discard any rows with average values below 1.0 (less than twofold change compared to control).
Class B gene expression showed up regulation in lin-14(lf) in L1, no change in lin-4(lf) in L2.
WBPaper00026952:class_C Raw data from each experiment were downloaded from the Stanford Microarray Database into Excel files and processed as follows: (i) sort by Spot Flag and discard any rows where the Spot Flag value was nonzero, indicating a bad PCR; (ii) sort by Failed and discard any rows where the Failed value was nonzero, indicating abnormal hybridization; (iii) import into a common file for each type of experiment (i.e., lin-14 or lin-4) the columns from each raw experimental file [RAT2(R/G), which shows a log base 2 transformed ratio of normalized red/green signal for each spot; name of spot (Wormbase designation); chromosome location and description (www.wormbase.org)]; (iv) calculate an average RAT2(R/G) based on the 2 or 3 values (avg; any rows which had only one good experimental value were discarded); (v) calculate a standard deviation (stdev) for the average value; (vi) calculate a t value for each spot by using the formula t = avg*[sqrt(n - 1)]/stdev, where n is the number of experiments for which good data exist, sqrt is square root, and stdev is standard deviation; (vii) sort by absolute t value and discard any rows with a t value below 4.303 (below 95% confidence interval for three experiments) or below 12.706 (below 95% confidence interval for two experiments); (viii) sort by absolute average value and discard any rows with average values below 1.0 (less than twofold change compared to control).
Class C gene expression showed down regulation in lin-14(lf) in L1, up regulation in lin-4(lf) in L2.
WBPaper00026952:class_D Raw data from each experiment were downloaded from the Stanford Microarray Database into Excel files and processed as follows: (i) sort by Spot Flag and discard any rows where the Spot Flag value was nonzero, indicating a bad PCR; (ii) sort by Failed and discard any rows where the Failed value was nonzero, indicating abnormal hybridization; (iii) import into a common file for each type of experiment (i.e., lin-14 or lin-4) the columns from each raw experimental file [RAT2(R/G), which shows a log base 2 transformed ratio of normalized red/green signal for each spot; name of spot (Wormbase designation); chromosome location and description (www.wormbase.org)]; (iv) calculate an average RAT2(R/G) based on the 2 or 3 values (avg; any rows which had only one good experimental value were discarded); (v) calculate a standard deviation (stdev) for the average value; (vi) calculate a t value for each spot by using the formula t = avg*[sqrt(n - 1)]/stdev, where n is the number of experiments for which good data exist, sqrt is square root, and stdev is standard deviation; (vii) sort by absolute t value and discard any rows with a t value below 4.303 (below 95% confidence interval for three experiments) or below 12.706 (below 95% confidence interval for two experiments); (viii) sort by absolute average value and discard any rows with average values below 1.0 (less than twofold change compared to control).
Class D gene expression showed up regulation in lin-14(lf) in L1, down regulation in lin-4(lf) in L2.
WBPaper00026952:class_E Raw data from each experiment were downloaded from the Stanford Microarray Database into Excel files and processed as follows: (i) sort by Spot Flag and discard any rows where the Spot Flag value was nonzero, indicating a bad PCR; (ii) sort by Failed and discard any rows where the Failed value was nonzero, indicating abnormal hybridization; (iii) import into a common file for each type of experiment (i.e., lin-14 or lin-4) the columns from each raw experimental file [RAT2(R/G), which shows a log base 2 transformed ratio of normalized red/green signal for each spot; name of spot (Wormbase designation); chromosome location and description (www.wormbase.org)]; (iv) calculate an average RAT2(R/G) based on the 2 or 3 values (avg; any rows which had only one good experimental value were discarded); (v) calculate a standard deviation (stdev) for the average value; (vi) calculate a t value for each spot by using the formula t = avg*[sqrt(n - 1)]/stdev, where n is the number of experiments for which good data exist, sqrt is square root, and stdev is standard deviation; (vii) sort by absolute t value and discard any rows with a t value below 4.303 (below 95% confidence interval for three experiments) or below 12.706 (below 95% confidence interval for two experiments); (viii) sort by absolute average value and discard any rows with average values below 1.0 (less than twofold change compared to control).
Class E gene expression showed no change in lin-14(lf) in L1, up regulation in lin-4(lf) in L2.
load 10 more results