Enable local gene list analysis

[cthoyt]

Right now, there are several gene list analysis available through the INDRA Discovery website (https://discovery.indra.bio/gene/discrete, https://discovery.indra.bio/gene/signed, https://discovery.indra.bio/gene/continuous). Depending on the query, they can be slow, so it would be nice to have a way to run these analyses locally with an indra_cogex.client module that interacts with the REST API to get the underlying data that's necessary, then run the analysis locally.

This shouldn't be a huge lift, since most of the code necessary to run this is modularized already inside the web endpoints (see below), but one change is that it currently uses the client to interact with the database directly, and we'd want to switch that to a different client that interacts with the API, so we don't have to give direct access to the database

indra_cogex/src/indra_cogex/apps/gla/gene_blueprint.py

Lines 175 to 284 in bbede16

	def discretize_analysis():
	"""Render the home page."""
	form = DiscreteForm()
	if form.validate_on_submit():
	method = form.correction.data
	alpha = form.alpha.data
	keep_insignificant = form.keep_insignificant.data
	minimum_evidence_count = form.minimum_evidence.data
	minimum_belief = form.minimum_belief.data
	genes, errors = form.parse_genes()
	gene_set = set(genes)
	go_results = go_ora(
	client,
	gene_set,
	method=method,
	alpha=alpha,
	keep_insignificant=keep_insignificant,
	)
	wikipathways_results = wikipathways_ora(
	client,
	gene_set,
	method=method,
	alpha=alpha,
	keep_insignificant=keep_insignificant,
	)
	reactome_results = reactome_ora(
	client,
	gene_set,
	method=method,
	alpha=alpha,
	keep_insignificant=keep_insignificant,
	)
	phenotype_results = phenotype_ora(
	gene_set,
	client=client,
	method=method,
	alpha=alpha,
	keep_insignificant=keep_insignificant,
	)
	if form.indra_path_analysis.data:
	indra_upstream_results = indra_upstream_ora(
	client,
	gene_set,
	method=method,
	alpha=alpha,
	keep_insignificant=keep_insignificant,
	minimum_evidence_count=minimum_evidence_count,
	minimum_belief=minimum_belief,
	)
	indra_downstream_results = indra_downstream_ora(
	client,
	gene_set,
	method=method,
	alpha=alpha,
	keep_insignificant=keep_insignificant,
	minimum_evidence_count=minimum_evidence_count,
	minimum_belief=minimum_belief,
	)
	else:
	indra_upstream_results = None
	indra_downstream_results = None
	if INDRA_COGEX_WEB_LOCAL and form.local_download.data:
	downloads = Path.home().joinpath("Downloads")
	go_results.to_csv(
	downloads.joinpath("go_results.tsv"), sep="\t", index=False
	)
	wikipathways_results.to_csv(
	downloads.joinpath("wikipathways_results.tsv"), sep="\t", index=False
	)
	reactome_results.to_csv(
	downloads.joinpath("reactome_results.tsv"), sep="\t", index=False
	)
	phenotype_results.to_csv(
	downloads.joinpath("phenotype_results.tsv"), sep="\t", index=False
	)
	if form.indra_path_analysis.data:
	indra_downstream_results.to_csv(
	downloads.joinpath("indra_downstream_results.tsv"),
	sep="\t",
	index=False,
	)
	indra_upstream_results.to_csv(
	downloads.joinpath("indra_upstream_results.tsv"),
	sep="\t",
	index=False,
	)
	flask.flash(f"Downloaded files to {downloads}")
	return flask.redirect(url_for(f".{discretize_analysis.__name__}"))
	return flask.render_template(
	"gene_analysis/discrete_results.html",
	genes=genes,
	errors=errors,
	method=method,
	alpha=alpha,
	go_results=go_results,
	wikipathways_results=wikipathways_results,
	reactome_results=reactome_results,
	phenotype_results=phenotype_results,
	indra_downstream_results=indra_downstream_results,
	indra_upstream_results=indra_upstream_results,
	)
	return flask.render_template(
	"gene_analysis/discrete_form.html",
	form=form,
	example_hgnc_ids=", ".join(EXAMPLE_GENE_IDS),
	)