inst/helpfiles/tabPanel_MA_missingValue_FALSE.md

In tnaake/MatrixQCvis: Shiny-based interactive data-quality exploration for omics data

MA plot and Hoeffding's D statistic

In the first part of the panel the A vs. M plots per sample are depicted.

The values are defined as follows - $A = 1/2 \cdot (I_i + I_j)$ and - $M = I_i- I_j$, where $I_i$ and $I_j$ are transformed values. In the case of raw or normalized the values are log2-transformed prior to calculating A and M. In case of transformed or batch corrected the values are taken as they are (N.B. when the transformation method is set to none the values are not log2-transformed).

The values for $I_i$ are taken from the sample $i$. For $I_j$, the feature-wise means are calculated from the values of the group $j$ of samples specified by the drop-down menu group. The sample for calculating $I_i$ is excluded from the group $j$. The group can be set to "all" (i.e. all samples except sample $i$ are used to calculate $I_j$) or any other column in colData(se). For any group except "all" the group is taken to which the sample $i$ belongs to and the sample $i$ is excluded from the feature-wise calculation.

The MA values for all samples are by default displayed facet-wise. The MA plot can be set to specific samples by changing the selected value in the input menu plot.

The underlying data set can be selected by the drop-down menu (Data set for the MA plot).

In the second part of the tab, the Hoeffding's D statistic values are visualized for the different data sets raw, normalized, transformed, and batch corrected.

D is a measure of the distance between F(A, M) and G(A)H(M), where F(A, M) is the joint cumulative distribution function (CDF) of A and M, and G and H are marginal CDFs. The higher the value of D, the more dependent are A and M.

tnaake/MatrixQCvis documentation built on Nov. 4, 2024, 7:42 a.m.