ExprMixtureModel1.4Provides a mixture model fit of two normal distributions for the
given genes. Each gene is processed individually.
Output columns:

gene

identifier of the expression profile

normality

P-value of associated with the Shapiro-Wilk normality test

loglik

log likelihood of the mixture model

m1mean

mean of the first Gaussian component

m2mean

mean of the second Gaussian component

m1sd

standard deviation of the first Gaussian component

m2sd

standard deviation of the second Gaussian component

m1prop

proportion of samples captured by the first Gaussian component

m2prop

proportion of samples captured by the second Gaussian component

selected

expression profile satisfies the given thresholds and is plotted

mi

normalized mutual information score

Marko LaaksoMikko KivelĂ¤DEGQuality ControlRmixtoolsExpression matrixGene names and other related annotationsSample groupsThe smaller distribution component should cover at least this proportion of the samples.The difference of the distribution component means is at least this many times
the standard deviation of the less variatiating distribution.Minimum for the normalized mutual information score when groups 1 and 2 are defined.Maximum of the log likelihood for the mixture modelMaximum overlap between the distribution componentsID of the first sample group or an empty string for the first group within the groups inputID of the second sample group or an empty string for the second group within the groups inputA comma separated list of gene annotation column names to be shownCut-off points are visualized at (+,-)sdPoint*mean.If non-empty, a declaration of a new section with the given name is inserted to the
beginning of the combined document.Type of LaTeX section: usually one of section, subsection or subsubsection.
No section statement is written if sectionTitle is empty.Show distributions where the model fit algorithm has failed