A tool for reconstructing Transfer Entropy-based causal gene NETwork from pseudo-time ordered single cell transcriptomic data
Nucleic Acids Research, gkaa1014, https://doi.org/10.1093/nar/gkaa1014 https://github.com/neocaleb/TENET
./TENET [expression_file_name] [number_of_threads] [trajectory_file_name] [cell_select_file_name] [history_length]
./TENET expression_data.csv 10 trajectory.txt cell_select.txt 1
1-1. Run TENET from TF to target using expression data in a csv file and pseudotime result in a text file
./TENET_TF [expression_file_name] [number_of_threads] [trajectory_file_name] [cell_select_file_name] [history_length] [species]
./TENET_TF expression_data.csv 10 trajectory.txt cell_select.txt 1 human
1-2. Run TENET from selected gene peak to target using expression data in a csv file and pseudotime result in a text file
./TENET_select [expression_file_name] [number_of_threads] [trajectory_file_name] [cell_select_file_name] [history_length] [selcet_list]
./TENET_select expression_data.csv 10 trajectory.txt cell_select.txt 1 select_list.txt
sh getMatrix_rowTF_colGN_AB-matrix.sh [TENET result matrix]
sh getMatrix_rowTF_colPK_C-matrix.sh [TENET result matrix]
sh getMatrix_rowTF_colGN_AB-matrix.sh TE_result_matrix.txt
sh getMatrix_rowTF_colPK_C-matrix.sh TE_result_matrix.txt
python make_GRN_new.py [AB matrix]
python make_GRN_new.py TE_result_matrix_rowTF_colGN.txt
python make_GRN_new.py TE_result_matrix_rowTF_colPK.txt
python countOutdegree.py [name of GRN]
python countOutdegree.py TE_result_matrix_rowTF_colGN.sif
python countOutdegree.py TE_result_matrix_rowTF_colPK.sif
TE_result_matrix_rowTF_colPK.sif.outdegree.txt