Sentence examples for the data we removed from inspiring English sources

Because the final correlations used to assess gene coordination were bootstrapped, to detrend the data we removed any linear relationship with age in each of the 20,000 bootstrap instances and used these detrended resamples to generate a histogram of amygdala-cingulate expression profiles as before (see Figure 2A).

Before plotting the data, we removed the outliers detected using the Grubb's test.

To clean the data, we removed the records that do not have the information about gene name, sample ID, primary site, or mutation description.

In order to improve the quality of the data, we removed adapter sequences, trimmed low quality bases (Q < 20) from both ends of reads and discarded reads less than 50 bases in length.

An example is shown in Figure 3. First, to reduce noise in the data, we removed fragments that had less than a median of 40 counts across all samples for one viewpoint.

By using the mean distance as calculated from the data, we remove this nuisance parameter from the algorithm.

By assuming the same model as that used to generate the data, we remove the effect of model misspecification as a source of error in our simulation study.

When we finished using all of the metagenomics data, we removed these sequences because they were not useful for the remaining analyses.

To simulate the linkage approach required for the national surveillance data, we removed unique identifiers from all files.

For the processing of SNP genotype data, we removed such SNPs satisfying minimum allele frequency <0.01 and Hardy-Weinberg equilibrium test statistic value lower than ~7.

In order to eliminate edge effects from our data, we removed the terminal and sub-terminal intervals from all linear regression analyses on the HapMap-derived data sets (for fixed AluY in the YRI and CEU samples, and for polymorphic AluY in the YRI sample).