Sentence examples for multiple sample groups from inspiring English sources

Examples include comparing compound intensities between multiple sample groups and unbiasedly tracking the fate of specific isotopic labels.

Data involving the analysis of multiple sample groups were analyzed by one-way ANOVA followed by Bonferroni's test for multiple comparisons.

One-way ANOVA followed by Bonferroni's test for multiple comparisons was used to analyze data involving the analysis of multiple sample groups.

One proteomics method is isobaric tag for relative and absolute quantification (iTRAQ), a liquid chromatography and tandem mass spectrometry technique that allows for simultaneous identification and quantification of peptides between multiple sample groups.

Our main approach to reducing the influence of bias was to look for consistency in findings across multiple sample groups.

For our future research, it will be useful to extend our proposed method for an integrative analysis of data with multiple sample groups.

To test differences among multiple samples (groups, i.e., Sm level in different stages), a Kruskal Wallis ANOVA test was used.

In the literature, the cut-off for splitting patients undergoing lymphadenectomy into a limited sampling and a multiple sampling group is around 10 to 12 lymph nodes.

In this chapter, we describe SCR models for situations when we have multiple distinct sample groups, strata or "sessions" (the term used in secr), and our interest is in modeling variation in population size or density among the different strata.

With multiple samples per group, methylkit will preferentially use logistic regression, enabling also the inclusion of potential confounders (Akalin et al, 2012); to get stable estimates of the regression coefficients in logistic regression about 10 events per variable are necessary (Peduzzi et al, 1996).

To assess how the different software packages and pipelines can control false positive rates, we utilized the multiple replicates within the sample groups by constructing artificial two-group comparisons.