Analyzing Meta Data (HFEvsLFE) using FisherExactTest Programs Mines All Significant Multi-Dimensional Adjusted Results and performs a Fisher Exact Test on the Feed Efficiency Status of the Sampels (HFE vs LFE) for all the Significant ASE samples for a variant.
After implementing the Fisher Exact Test, p-values are adjusted using the Benjamini-Hochberg method. Program then annotates all the results with variant effects based on output from VEP (applied to testable variants and non-testable).
REQUIRED INPUT FILES
-
Testable_VEP_Results.txt
-All the annotated data from VEP -
sig_multi_dim_adj_results.txt
-All the significant multi-dimensional adjusted results for a specific tissue -
Meta Input File
-Meta Data File about the chicken samples (tells which samples are HFE vs LFE)
REQUIRED INPUT SETTINGS
-
Project Name
-Tells program how to parse the meta data file to identify the correct samples -
Tissue
-Tells program how to parse the meta data file to identify the correct samples -
Sample Minimum
-Minimum number of samples to considered when implementing the Fisher Exact Test
OUTPUT FILES
-
fisher_exact_test_results.txt
-Testable variants for Fisher Exact Test with corresponding p-values -
non_testable_sig_ase_results.txt
-Non-testable variants for the Fisher Exact Test -Fail due to minimal sample number required or resulting p-value is NaN -
Final_Annot_Results_Fisher_Exact_Test.txt (FINAL FILE OF INTEREST)
-Final testable variants with corresponding Fisher Exact Test p-values along with adjusted p-values (Benjamini Hochberg) and corresponding variant effect information from VEP -
ANNOT_non_testable_sig_ase_results.txt
-Non-testable variants annotated with corresponding variant effect information