17 June 2015
Genewise expression level523 with fdr<=0.01 1032 with fdr<=0.05 | Raw data format: WT-tpre; WT-t0m; WT-t15m; WT-t30m; WT-t45m; WT-t60m; WT-t75m; WT-t90m; WT-t105m; WT-t120m; DeltaSet1-tpre; DeltaSet1-t0m; DeltaSet1-t15m; DeltaSet1-t30m; DeltaSet1-t45m; DeltaSet1-t60m; DeltaSet1-t75m; DeltaSet1-t90m; DeltaSet1-t105m; DeltaSet1-t120m 5512 of 6532 features kept after filtering (required at least one sample with 10 reads) df = 7.595675 sd = 0.933036 noise combined p-value = 1.000000 noise fit score = 0.732097 bits |
Genewise tail length9 with fdr<=0.01 97 with fdr<=0.05 | Raw data format: WT-tpre; WT-t0m; WT-t15m; WT-t30m; WT-t45m; WT-t60m; WT-t75m; WT-t90m; WT-t105m; WT-t120m; DeltaSet1-tpre; DeltaSet1-t0m; DeltaSet1-t15m; DeltaSet1-t30m; DeltaSet1-t45m; DeltaSet1-t60m; DeltaSet1-t75m; DeltaSet1-t90m; DeltaSet1-t105m; DeltaSet1-t120m 4499 of 6532 features kept after filtering (required sufficient samples with 10 poly(A) reads to fit linear model) df = 22.655004 variance = 20.732851^2 / reads + (0.034642 * avgtail)^2 noise combined p-value = 0.270730 noise fit score = 3.639192 bits |
Primary-peakwise expression level312 with fdr<=0.01 703 with fdr<=0.05 | Raw data format: WT-tpre; WT-t0m; WT-t15m; WT-t30m; WT-t45m; WT-t60m; WT-t75m; WT-t90m; WT-t105m; WT-t120m; DeltaSet1-tpre; DeltaSet1-t0m; DeltaSet1-t15m; DeltaSet1-t30m; DeltaSet1-t45m; DeltaSet1-t60m; DeltaSet1-t75m; DeltaSet1-t90m; DeltaSet1-t105m; DeltaSet1-t120m 3401 of 3401 features kept after filtering (required at least one sample with 10 reads) df = 5.739301 sd = 0.930964 noise combined p-value = 1.000000 noise fit score = 0.606147 bits |
Primary-peakwise tail length1 with fdr<=0.01 53 with fdr<=0.05 | Raw data format: WT-tpre; WT-t0m; WT-t15m; WT-t30m; WT-t45m; WT-t60m; WT-t75m; WT-t90m; WT-t105m; WT-t120m; DeltaSet1-tpre; DeltaSet1-t0m; DeltaSet1-t15m; DeltaSet1-t30m; DeltaSet1-t45m; DeltaSet1-t60m; DeltaSet1-t75m; DeltaSet1-t90m; DeltaSet1-t105m; DeltaSet1-t120m 3340 of 3401 features kept after filtering (required sufficient samples with 10 poly(A) reads to fit linear model) df = 20.719230 variance = 20.395192^2 / reads + (0.034580 * avgtail)^2 noise combined p-value = 0.294344 noise fit score = 3.564138 bits |
Peakwise expression level887 with fdr<=0.01 1511 with fdr<=0.05 | Raw data format: WT-tpre; WT-t0m; WT-t15m; WT-t30m; WT-t45m; WT-t60m; WT-t75m; WT-t90m; WT-t105m; WT-t120m; DeltaSet1-tpre; DeltaSet1-t0m; DeltaSet1-t15m; DeltaSet1-t30m; DeltaSet1-t45m; DeltaSet1-t60m; DeltaSet1-t75m; DeltaSet1-t90m; DeltaSet1-t105m; DeltaSet1-t120m 5562 of 5562 features kept after filtering (required at least one sample with 10 reads) df = 5.762323 sd = 0.910154 noise combined p-value = 1.000000 noise fit score = 0.678190 bits |
Peakwise tail length11 with fdr<=0.01 90 with fdr<=0.05 | Raw data format: WT-tpre; WT-t0m; WT-t15m; WT-t30m; WT-t45m; WT-t60m; WT-t75m; WT-t90m; WT-t105m; WT-t120m; DeltaSet1-tpre; DeltaSet1-t0m; DeltaSet1-t15m; DeltaSet1-t30m; DeltaSet1-t45m; DeltaSet1-t60m; DeltaSet1-t75m; DeltaSet1-t90m; DeltaSet1-t105m; DeltaSet1-t120m 5347 of 5562 features kept after filtering (required sufficient samples with 10 poly(A) reads to fit linear model) df = 10.217743 variance = 17.929878^2 / reads + (0.038204 * avgtail)^2 noise combined p-value = 1.000000 noise fit score = 3.582857 bits |
Peak-pair expression shift3 with fdr<=0.01 11 with fdr<=0.05 | Raw data format: WT-tpre-peak1; WT-t0m-peak1; WT-t15m-peak1; WT-t30m-peak1; WT-t45m-peak1; WT-t60m-peak1; WT-t75m-peak1; WT-t90m-peak1; WT-t105m-peak1; WT-t120m-peak1; DeltaSet1-tpre-peak1; DeltaSet1-t0m-peak1; DeltaSet1-t15m-peak1; DeltaSet1-t30m-peak1; DeltaSet1-t45m-peak1; DeltaSet1-t60m-peak1; DeltaSet1-t75m-peak1; DeltaSet1-t90m-peak1; DeltaSet1-t105m-peak1; DeltaSet1-t120m-peak1; WT-tpre-peak2; WT-t0m-peak2; WT-t15m-peak2; WT-t30m-peak2; WT-t45m-peak2; WT-t60m-peak2; WT-t75m-peak2; WT-t90m-peak2; WT-t105m-peak2; WT-t120m-peak2; DeltaSet1-tpre-peak2; DeltaSet1-t0m-peak2; DeltaSet1-t15m-peak2; DeltaSet1-t30m-peak2; DeltaSet1-t45m-peak2; DeltaSet1-t60m-peak2; DeltaSet1-t75m-peak2; DeltaSet1-t90m-peak2; DeltaSet1-t105m-peak2; DeltaSet1-t120m-peak2 508 of 508 features kept after filtering (required at least one sample with 10 reads) df = 7.486456 sd = 0.918405 noise combined p-value = 0.626132 noise fit score = 0.737797 bits |
Peak-pair tail length shift0 with fdr<=0.01 0 with fdr<=0.05 | Raw data format: WT-tpre-peak1; WT-t0m-peak1; WT-t15m-peak1; WT-t30m-peak1; WT-t45m-peak1; WT-t60m-peak1; WT-t75m-peak1; WT-t90m-peak1; WT-t105m-peak1; WT-t120m-peak1; DeltaSet1-tpre-peak1; DeltaSet1-t0m-peak1; DeltaSet1-t15m-peak1; DeltaSet1-t30m-peak1; DeltaSet1-t45m-peak1; DeltaSet1-t60m-peak1; DeltaSet1-t75m-peak1; DeltaSet1-t90m-peak1; DeltaSet1-t105m-peak1; DeltaSet1-t120m-peak1; WT-tpre-peak2; WT-t0m-peak2; WT-t15m-peak2; WT-t30m-peak2; WT-t45m-peak2; WT-t60m-peak2; WT-t75m-peak2; WT-t90m-peak2; WT-t105m-peak2; WT-t120m-peak2; DeltaSet1-tpre-peak2; DeltaSet1-t0m-peak2; DeltaSet1-t15m-peak2; DeltaSet1-t30m-peak2; DeltaSet1-t45m-peak2; DeltaSet1-t60m-peak2; DeltaSet1-t75m-peak2; DeltaSet1-t90m-peak2; DeltaSet1-t105m-peak2; DeltaSet1-t120m-peak2 506 of 508 features kept after filtering (required sufficient samples with 10 poly(A) reads to fit linear model) df = 20.245944 variance = 19.527444^2 / reads + (0.040105 * avgtail)^2 noise combined p-value = 0.239558 noise fit score = 3.588102 bits |
