Sentence examples for between batches of samples from inspiring English sources
In SNP based studies differential bias can lead to differences in allele frequency estimates between batches of samples.
These solvents are to be used at the end of the experiment or in between batches of samples to clean the column.
We simulated two chains starting at different initial values up to one million parameter sets and assessed convergence by visually inspecting differences between batches of samples.
Particle-free 0- and 4-hr antioxidant controls, as well as 4-hr positive (residual oil fly ash) and negative (carbon black) particle controls, were run in parallel to quantify autooxidative losses and permit standardization between batches of samples.
Batch effects correspond to non-biological variations existing between batches of samples that, for instance, have not been processed the same day, on the same scanner, or by the same experimenter.
More importantly, the relationship between cell type and EOC status was highly consistent between both batches of samples within our study population and also with the results reported in a prior publication [ 13], which consisted of the application of the cell mixture methodology to an independent study population of n = 131 pretreatment EOC cases and n = 274 controls [ 12].
At increasing dilution we observed that differences in fibrillization kinetics and PELDOR/DEER modulation depths between parallel batches of samples were systematically attenuated.
All data were analyzed as raw values, except for HPLC results, where the data were analyzed as percentage of the average value for the SAL-VEH group, due to large inter-assay variability between two different batches of samples assayed.
The combination of many gene expression profile datasets from different sources poses the problem of the batch effect, i.e. the systematic differences between batches (groups) of samples in microarray experiments due to purely technical reasons.
The batch effects are the systematic differences between batches (groups) of samples in microarray experiments due to technical reasons, such as variability in materials, protocols or operators, possibly introducing a bias able to confound true biological differences (recently reviewed by Luo and coll. [ 30]).
