Sentence examples for treated dataset from inspiring English sources

After we excluded non-reliable probes based on Δβ-values in control (mock treated) dataset, we normalized the DNA methylation data by comparing the mock-treated cells with the 5-aza-dC or IR-treated cells (Additional file 1: Figure S1).

The average signal intensity values of all the spike-in probes for two experiments with a reference and a treated dataset are shown in Figures 4 and 5.

A total number of ~1,000 and ~12,047 peaks were called by using W-ChIPeaks [ 14] in control and an E2 treated dataset, respectively.

These results also show that comparison of K a / K s values between treated and untreated datasets is effective at distinguishing primary and accessory drug-resistance mutations (only observed in the treated dataset) from viral fitness mutations (observed in the untreated dataset).

To assess whether drug treatment acts as the consistent amino acid selection in these two datasets, we compared the (A,A) covariation in the Treated dataset with that in the Untreated one.

None of the codon pairs with positive conditional selection in the Specialty dataset showed negative selection in the Treated dataset.

Could the surplus of the (A,A) covariation compared with that of (A,S) and (S,S) in the treated datasets (Specialty and Stanford-Treated) be an artifact of differences in the intrinsic mutation rates between silent and amino acid mutations (e.g. silent mutations are more likely to be transitions than transversions, thus evolving faster)?

AtWRKY6, AtWRKY18, AtWRKY45, and AtWRKY53 were differentially expressed in three jasmonate treated datasets.

Of the 39 jasmonate responsive AtWRKY genes, 22 were differentially expressed in at least two jasmonate treated datasets.

After discarding low quality, filtering 5' contaminant and trimming 3' adaptor reads, a total of 8,500,978, 9,357,545, 9,003,582 and 9,223,744 clean reads were obtained from mock, drought, salinity and alkalinity treated datasets, respectively (see Additional file 1).

Differences between control and MeJA treated datasets were then adjusted using the Catharanthus reference gene EF1α (Cra3894) as an internal control [ 13], as this gene was used as the internal control for qRT-PCR expression measurements.