def run_ne_workflow(global_variables, biotype):
print "-" * len(list(biotype))
print biotype
print "-" * len(list(biotype))
print
# gets the config for the workflow
config = global_variables["config"]["NE"]
# gets the outpath for the workflow - as we use this a lot
out_path = os.path.join(global_variables["out_path"], biotype,
"ne_workflow")
for element in config:
element_name, element_active, element_type, element_subtype, element_path = element
if check_element_prerequisites(element_active, element_type,
element_subtype, element_path,
global_variables):
# methods for the core workflow
if element_name == "ne_sub_directories_core" and element_type == "core":
core_sub_directories(global_variables, out_path)
elif element_name == "ne_file_matrix_annotated" and element_type == "core":
ne_matrix_annotated(global_variables, out_path, biotype)
elif element_name == "ne_file_matrix_IDs" and element_type == "core":
ne_matrix_IDs(global_variables, out_path, biotype)
elif element_name == "ne_file_matrix_symbols" and element_type == "core":
ne_matrix_symbols(global_variables, out_path, biotype)
elif element_name == "ne_file_gene_IDs" and element_type == "core":
ne_gene_IDs(global_variables, out_path, biotype)
elif element_name == "ne_file_gene_symbols" and element_type == "core":
ne_gene_symbols(global_variables, out_path, biotype)
# methods for statistical analysis
# methods for the plots
elif element_name == "ne_start_plots" and element_type == "plot_core":
pr_dictionary = start_plots(global_variables, out_path, "ne",
None)
elif element_type == "plot":
add_plot(element_path, pr_dictionary)
elif element_name == "ne_end_plots" and element_type == "plot_core":
end_plots(pr_dictionary)
elif element_name == "ne_run_r" and element_type == "plot_core":
run_r(pr_dictionary)
# methods for the report
elif element_name == "ne_start_report" and element_type == "report_core":
start_report(global_variables, pr_dictionary, element_path)
elif element_type == "report_title":
add_header_section_to_report(element_path, pr_dictionary)
elif element_type == "report_text":
add_text_section_to_report(element_path, pr_dictionary,
global_variables)
elif element_type == "report_plot":
add_plot_section_to_report(element_path, pr_dictionary,
global_variables)
elif element_name == "ne_end_report" and element_type == "report_core":
end_report(pr_dictionary)
print "done with: " + element_name.replace("_", " ")
print
def run_mde_workflow(global_variables, biotype):
print "-" * len(list(biotype))
print biotype
print "-" * len(list(biotype))
print
# gets the config for the workflow
config = global_variables["config"]["MDE"]
# iterates through the des
parsed_mde_parameters = global_variables["mde_parameters"]
for mde_dict in parsed_mde_parameters:
mde_ID = mde_dict["mde_ID"]
de_IDs = mde_dict["de_IDs"]
print mde_ID
# gets the outpath for the workflow - as we use this a lot
out_path = os.path.join(global_variables["out_path"], biotype,
"mde_workflows", mde_ID)
for element in config:
element_name, element_active, element_type, element_subtype, element_path = element
# checks prerequisites have been met:
if check_element_prerequisites(element_active, element_type,
element_subtype, element_path,
global_variables):
# methods for the core workflow
if element_name == "mde_sub_directories_core" and element_type == "core":
core_sub_directories(global_variables, out_path)
elif element_name == "mde_file_all_genes_IDs" and element_type == "core":
Mde_IDs(global_variables, out_path, biotype, de_IDs)
elif element_name == "mde_file_genes_significant_in_any_comparison_IDs" and element_type == "core":
Mde_any_significant_IDs(global_variables, out_path,
biotype, de_IDs)
elif element_name == "mde_file_genes_significant_in_all_comparisons_IDs" and element_type == "core":
Mde_all_significant_IDs(global_variables, out_path,
biotype, de_IDs)
elif element_name == "mde_file_all_genes_symbols" and element_type == "core":
Mde_symbols(global_variables, out_path, biotype, de_IDs)
elif element_name == "mde_file_genes_significant_in_any_comparison_symbols" and element_type == "core":
Mde_any_significant_symbols(global_variables, out_path,
biotype, de_IDs)
elif element_name == "mde_file_genes_significant_in_all_comparisons_symbols" and element_type == "core":
Mde_all_significant_symbols(global_variables, out_path,
biotype, de_IDs)
elif element_name == "mde_file_all_genes_annotated" and element_type == "core":
Mde_annotated(global_variables, out_path, biotype, de_IDs)
elif element_name == "mde_file_genes_significant_in_any_comparison_annotated" and element_type == "core":
Mde_any_significant_annotated(global_variables, out_path,
biotype, de_IDs)
elif element_name == "mde_file_genes_significant_in_all_comparisons_annotated" and element_type == "core":
Mde_all_significant_annotated(global_variables, out_path,
biotype, de_IDs)
# methods for statistical analysis
elif element_name == "mde_analysis_pairwise_overlap" and element_type == "statistical":
pairwise_overlap_helper(out_path, de_IDs)
elif element_name == "mde_differential_expression_signature" and element_type == "statistical":
mde_dict = differential_expression_signature_helper(
global_variables, out_path, de_IDs, mde_dict)
# methods for the plots
elif element_name == "mde_start_plots" and element_type == "plot_core":
pr_dictionary = start_plots(global_variables, out_path,
"Mde", mde_dict)
elif element_type == "plot":
add_plot(element_path, pr_dictionary)
elif element_name == "mde_end_plots" and element_type == "plot_core":
end_plots(pr_dictionary)
elif element_name == "mde_run_r" and element_type == "plot_core":
run_r(pr_dictionary)
# methods for the report
elif element_name == "mde_start_report" and element_type == "report_core":
start_report(global_variables, pr_dictionary, element_path)
elif element_type == "report_title":
add_header_section_to_report(element_path, pr_dictionary)
elif element_type == "report_text":
add_text_section_to_report(element_path, pr_dictionary,
global_variables)
elif element_type == "report_plot":
add_plot_section_to_report(element_path, pr_dictionary,
global_variables)
elif element_name == "mde_end_report" and element_type == "report_core":
end_report(pr_dictionary)
print "done with: " + element_name.replace("_", " ")
print
def run_pde_workflow(global_variables, biotype):
print "-" * len(list(biotype))
print biotype
print "-" * len(list(biotype))
print
# gets the config for the workflow
config = global_variables["config"]["PDE"]
# iterates through the PDEs
parsed_pde_parameters = global_variables["pde_parameters"]
for pde_parameter_dict in parsed_pde_parameters:
pde_ID = pde_parameter_dict["pde_ID"]
print pde_ID
pde_ID_no_spaces = pde_ID.replace(" ", "_")
# gets the outpath for the workflow - as we use this a lot
out_path = os.path.join(global_variables["out_path"], biotype,
"pde_workflows", pde_ID_no_spaces)
# iterates through the elements in the config
for element in config:
element_name, element_active, element_type, element_subtype, element_path = element
# checks prerequisites have been met:
if check_element_prerequisites(element_active, element_type,
element_subtype, element_path,
global_variables):
# methods for the core workflow
if element_name == "pde_sub_directories_core" and element_type == "core":
core_sub_directories(global_variables, out_path)
elif element_name == "pde_file_gene_IDs" and element_type == "core":
gene_IDs(global_variables, out_path, biotype, pde_ID)
elif element_name == "pde_file_gene_IDs_upregulated" and element_type == "core":
gene_IDs_upregulated(global_variables, out_path, biotype,
pde_ID)
elif element_name == "pde_file_gene_IDs_downregulated" and element_type == "core":
gene_IDs_downregulated(global_variables, out_path, biotype,
pde_ID)
elif element_name == "pde_file_gene_IDs_significant" and element_type == "core":
gene_IDs_significant(global_variables, out_path, biotype,
pde_ID)
elif element_name == "pde_file_gene_IDs_significant_upregulated" and element_type == "core":
gene_IDs_significant_upregulated(global_variables,
out_path, biotype, pde_ID)
elif element_name == "pde_file_gene_IDs_significant_downregulated" and element_type == "core":
gene_IDs_significant_downregulated(global_variables,
out_path, biotype,
pde_ID)
elif element_name == "pde_file_gene_symbols" and element_type == "core":
gene_symbols(global_variables, out_path, biotype, pde_ID)
elif element_name == "pde_file_gene_symbols_upregulated" and element_type == "core":
gene_symbols_upregulated(global_variables, out_path,
biotype, pde_ID)
elif element_name == "pde_file_gene_symbols_downregulated" and element_type == "core":
gene_symbols_downregulated(global_variables, out_path,
biotype, pde_ID)
elif element_name == "pde_file_gene_symbols_significant" and element_type == "core":
gene_symbols_significant(global_variables, out_path,
biotype, pde_ID)
elif element_name == "pde_file_gene_symbols_significant_upregulated" and element_type == "core":
gene_symbols_significant_upregulated(
global_variables, out_path, biotype, pde_ID)
elif element_name == "pde_file_gene_symbols_significant_downregulated" and element_type == "core":
gene_symbols_significant_downregulated(
global_variables, out_path, biotype, pde_ID)
elif element_name == "pde_file_annotated" and element_type == "core":
PDE_annotated(global_variables, out_path, biotype, pde_ID)
elif element_name == "pde_file_annotated_upregulated" and element_type == "core":
PDE_annotated_upregulated(global_variables, out_path,
biotype, pde_ID)
elif element_name == "pde_file_annotated_downregulated" and element_type == "core":
PDE_annotated_downregulated(global_variables, out_path,
biotype, pde_ID)
elif element_name == "pde_file_annotated_significant" and element_type == "core":
PDE_annotated_significant(global_variables, out_path,
biotype, pde_ID)
elif element_name == "pde_file_annotated_significant_upregulated" and element_type == "core":
PDE_annotated_significant_upregulated(
global_variables, out_path, biotype, pde_ID)
elif element_name == "pde_file_annotated_significant_downregulated" and element_type == "core":
PDE_annotated_significant_downregulated(
global_variables, out_path, biotype, pde_ID)
# methods for statistical analysis
elif element_name == "pde_analysis_spatial" and element_type == "statistical":
spatial_enrichment_helper(global_variables, out_path,
pde_parameter_dict)
elif element_name == "pde_analysis_hypergeometric_gene_sets" and element_type == "statistical":
hypergeometric_gene_set_helper(out_path, global_variables)
elif element_name == "pde_analysis_ipa_upstream_regulators" and element_type == "statistical":
ipa_ureg_helper(out_path, global_variables)
# methods for the plots
elif element_name == "pde_start_plots" and element_type == "plot_core":
pr_dictionary = start_plots(global_variables, out_path,
"PDE", pde_parameter_dict)
elif element_type == "plot":
add_plot(element_path, pr_dictionary)
elif element_name == "pde_end_plots" and element_type == "plot_core":
end_plots(pr_dictionary)
elif element_name == "pde_run_r" and element_type == "plot_core":
run_r(pr_dictionary)
# methods for the report
elif element_name == "pde_start_report" and element_type == "report_core":
start_report(global_variables, pr_dictionary, element_path)
elif element_type == "report_title":
add_header_section_to_report(element_path, pr_dictionary)
elif element_type == "report_text":
add_text_section_to_report(element_path, pr_dictionary,
global_variables)
elif element_type == "report_plot":
add_plot_section_to_report(element_path, pr_dictionary,
global_variables)
elif element_name == "pde_end_report" and element_type == "report_core":
end_report(pr_dictionary)
print "done with: " + element_name.replace("_", " ")
print