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Factor-Model-FAME:Factor Analysis based Methodology for Expression(FAME) data associates novel miRNAs with Ovarian Cancer

Overview

This repository contains the MATLAB implementation of simulations and real data analysis in our manuscript: Factor Analysis based Methodology for Expression(FAME) data associates novel miRNAs with Ovarian Cancer.

All the simulations are in the folder "factor_one sample" for one-sample test, "factor_two sample(Pairwise Comparision)" and "factor_two sample(Transition to One-Sample Test)" for two-sample test. And we suggest use "factor_two sample(Transition to One-Sample Test)" rather than "factor_two sample(Pairwise Comparision)", it has the higher power.

The real data analysis are in the "real data analysis" folder containing the code, data and results visualization.

Work flow

Here are some descriptions about the MATLAB .m files in the simulation:

  • Example_one_sample_test.m and Example_two_sample_test.m: give examples for one-sample and two-sample test to show how to use the code.
  • m0.m: main function file to get all important variables we need, such as FDR, rejection number and power.
  • solveW.m: estimate factor model.
  • solvet_hat00.m: function file to get FAME statistics and collect critical value which is computed by t_hat.m.
  • pai.m: function file to get the estimation of the proportion of non-nulls. This method is based on Cao, H., Kosorok, M. (2011). Simultaneous critical values for t-tests in very high dimensions. Bernoulli, 17, 347–394.
  • t_hat.m: function file to compute critical value.
  • generate_Y.m: function file to generate data followed factor model.

For real data analysis:

  • real_data_analysis.m: gives an example to run the analysis and print rejection number.
  • plot_reject.m: visualization for the rejection number under varying FDR control level, and compare with CK, Fan, Storey method.
  • poorly_expressed_plot.m: visualization for the miRNAs which are poorly expressed.
  • vocano_plot.m: vocano plot compared with BH method.

And in the file /real data analysis/data/:

  • data.benchmark.csv: gene expression data. The letter at the end is V and E in the first line indicate they are high-grade serous ovarian and endometrioid endometrial cancer samples, respectively. They both have n = 96 samples and p = 3523 markers for each of samples. And these 3523 markers in our data belong to 1347 miRNAs.
  • Ebench.csv: endometrioid endometrial cancer samples
  • Vbench.csv: high-grade serous ovarian cancer samples

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