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Although both SAM (Significance Analysis of Microarray, [ 8]) and LIMMA (Linear Models for Microarray Data, [ 9]) utilize moderated t-statistic and do not need the assumption of rigorous normality, their sensitivity is generally affected by a non-normal distribution.
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Similarly, while SAM [ 8] and LIMMA [ 9] do not require a rigorous normal distribution and -especially the latter- shows good performance when the sample size is small, we observed that they are not robust enough for cases showing dramatic deviation from normality, a fact also mentioned in LIMMA's manual.
Moreover PCA does not need rigorous distributional assumptions such as normality when it is used as a descriptive tool [ 20].
These results mostly agreed with the original GWAS (Sabatti et al., 2009) although we used genotype models (instead of allelic models) and the more rigorous rank transform of the data to normality (instead of the log-transform).
Particularly normality.
Normality resumes ■.
Training: Rigorous.
This is millennial normality.
Children want normality.
Dysfunction as normality.
Normality could resume.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com