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Bioinformatics. 2015 Jul 15;31(14):2310-7. doi: 10.1093/bioinformatics/btv154. Epub 2015 Mar 18.

Two-group comparisons of zero-inflated intensity values: the choice of test statistic matters.

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Center for Medical Statistics, Informatics and Intelligent Systems, Medical University Vienna, Austria, Vienna, Austria and.
Mosaiques Diagnostics and Therapeutics AG, Hannover, Germany.



A special characteristic of data from molecular biology is the frequent occurrence of zero intensity values which can arise either by true absence of a compound or by a signal that is below a technical limit of detection.


While so-called two-part tests compare mixture distributions between groups, one-part tests treat the zero-inflated distributions as left-censored. The left-inflated mixture model combines these two approaches. Both types of distributional assumptions and combinations of both are considered in a simulation study to compare power and estimation of log fold change. We discuss issues of application using an example from peptidomics.The considered tests generally perform best in scenarios satisfying their respective distributional assumptions. In the absence of distributional assumptions, the two-part Wilcoxon test or the empirical likelihood ratio test is recommended. Assuming a log-normal subdistribution the left-inflated mixture model provides estimates for the proportions of the two considered types of zero intensities.


R code is available at

[Indexed for MEDLINE]

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