Merge branch 'master' of https://github.com/stegmaierj/LiveCellMiner

Author: stegmaierj

README.md

@@ -192,6 +192,18 @@ Always make sure that you use consistent OligoIDs. Any spelling or case error wi
 
 - *Smooth Selected Time Series*: Smooths the selected time series with the method selected in the *LiveCellMiner* settings dialog. See documentation of the MATLAB function *smooth* for details on the available methods. Moreover, the size of the smoothing window can be adjusted in the edit field *Smoothing Window* located in the *LiveCellMiner* settings dialog.
 
+# Statistical Analysis
+*LiveCellMiner* allows to apply several statistical tests to selected single features and time series. Note that there is no checking performed if a statistical test is reasonable to be applied for the selected set of features, *i.e.*, familarize yourself with the methodology and make sure to select the appropriate statistical test for your application.
+
+The following functions are included:
+- *Test for Normal Distribution*: Performs a test for each of the selected output classes if the feature follows a normal distribution (the respective test method to use can be specified in the SciXMiner dropdown menu *Data mining: Statistical options*).
+- *Apply Two-Sample t-Test (parametric, SF)*: Performs a two-sample t-test (*e.g.*, to compare a single feature of two different oligos) on a selected single feature (SF). This also produces result tables in `*.csv` format as output with a matrix of pairwise tests (p-values and boolean test result if hypothesis was rejected or not). The result tables are placed in the same folder as the SciXMiner project resides in.
+- *Apply Wilcoxon Rank Sum Test (non-parametric, SF*: Same as the Two-Sample t-Test but using a Wilcoxon rank sum test instead.
+- *Apply ANOVA (parametric, SF)* and *Apply Kruskal-Wallis (non-parametric, SF)*: Possibility to compute an ANOVA or Kruskal-Wallis on the selected single feature (*e.g.* to compare multiple oligos including a visualization of the confidence intervals and the resulting significances). The multiple testing correction method to use can be specified in the *LiveCellMiner* settings dialog as well and is named *Multiple comparison*. See https://de.mathworks.com/help/stats/multcompare.html for further information.
+- *Compute Median Absolute Deviation (MAD, SF)*: Computes the global median value of the selected feature across all classes and the individual median values of each class. The average deviation of the individual median values to the global median (MAD) is computed and used as a threshold. Hits that exhibit a median value that deviates more than 3xMAD can be considered as strong hits.
+- *Apply Two-Way ANOVA*: Possibility to perform two-way ANOVA with interaction, where the dependent variable is the selected time series feature and the independent variables are the currently selected classes (*e.g.*, oligos, experiments, microscope, ...) *vs.* a set of selected time points (*e.g.*, an interphase time point, the MA-transition time point and a later value a few minutes after MA-transition defined by the user). Note that the time point selection uses absolute frame numbers in this case. To get the absolute frame numbers displayed in the line plots and heat map visualizations, make sure to uncheck the *Relative Frame Numbers?* checkbox located in the general *LiveCellMiner* settings dialog. The multiple testing correction method to use can be specified in the *LiveCellMiner* settings dialog as well and is named *Multiple comparison*. See https://de.mathworks.com/help/stats/multcompare.html for further information.
+
+Note that all above-mentioned statistical tests make use of the general *SciXMiner* selection, *i.e.*, you can use the *Edit -> Select -> Data Points using Classes ...* menu entry to perform the desired selection of cells to be used for the statistical analysis. Moreover, make sure to specify the correct output variable (dropdown menu entitled *Selection of output variable* that you can find in the *Single features* and *Time series: General options* dialog). 
 
 ## References:
 1. Mikut, R., Bartschat, A., Doneit, W., Ordiano, J. Á. G., Schott, B., Stegmaier, J., ... & Reischl, M. (2017). The MATLAB Toolbox SciXMiner: User's Manual and Programmer's Guide. arXiv preprint arXiv:1704.03298.
@@ -204,4 +216,4 @@ Always make sure that you use consistent OligoIDs. Any spelling or case error wi
 
 5. Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., ... & Rabinovich, A. (2015). Going Deeper with Convolutions. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1-9).
 
-6. Zhong, Q., Busetto, A. G., Fededa, J. P., Buhmann, J. M., & Gerlich, D. W. (2012). Unsupervised Modeling of Cell Morphology Dynamics for Time-Lapse Microscopy. Nature Methods, 9(7), 711-713.
+6. Zhong, Q., Busetto, A. G., Fededa, J. P., Buhmann, J. M., & Gerlich, D. W. (2012). Unsupervised Modeling of Cell Morphology Dynamics for Time-Lapse Microscopy. Nature Methods, 9(7), 711-713.