def generate_params_totalRNAfunctions():
for dbname, location in P.asDict("databases").iteritems():
yield [['mappings/unique.rpkm.all', location],
[
"overall_annotations/totalRNA.%s" % dbname,
"overall_annotations/totalRNA_diffs.%s" % dbname
]]
def generate_fuzzy_enrich_params():
'''find enrichments.'''
bad_clusters=getBadClusters()
for min_rpkm, min_diff, cluster_lvl in \
itertools.product( PARAMS["min_rpkm"], PARAMS["min_diff"], PARAMS["cluster_lvl" ] ):
for dbname, location in P.asDict("databases").iteritems():
if "fuzzy_k/all-%s-%s.pcl" % (min_rpkm, min_diff) in bad_clusters: continue
yield [ ["fuzzy_k/background-%s-%s" % (min_rpkm, min_diff),
glob.glob("fuzzy_k/cluster-%s-%s-%s.*" % (min_rpkm, min_diff, cluster_lvl)), location],
["fuzzy_k/%s-summary-cluster-%s-%s-%s.0" % (dbname, min_rpkm, min_diff, cluster_lvl),
"fuzzy_k/%s-expanded-cluster-%s-%s-%s.0" % (dbname, min_rpkm, min_diff, cluster_lvl)] ]
def generate_fuzzy_enrich_params():
'''find enrichments.'''
bad_clusters = getBadClusters()
for min_rpkm, min_diff, cluster_lvl in \
itertools.product( PARAMS["min_rpkm"], PARAMS["min_diff"], PARAMS["cluster_lvl" ] ):
for dbname, location in P.asDict("databases").iteritems():
if "fuzzy_k/all-%s-%s.pcl" % (min_rpkm, min_diff) in bad_clusters:
continue
yield [[
"fuzzy_k/background-%s-%s" % (min_rpkm, min_diff),
glob.glob("fuzzy_k/cluster-%s-%s-%s.*" %
(min_rpkm, min_diff, cluster_lvl)), location
],
[
"fuzzy_k/%s-summary-cluster-%s-%s-%s.0" %
(dbname, min_rpkm, min_diff, cluster_lvl),
"fuzzy_k/%s-expanded-cluster-%s-%s-%s.0" %
(dbname, min_rpkm, min_diff, cluster_lvl)
]]
def generate_params_totalRNAfunctions():
for dbname, location in P.asDict("databases").iteritems():
yield [['mappings/unique.rpkm.all', location],
["overall_annotations/totalRNA.%s" % dbname,
"overall_annotations/totalRNA_diffs.%s" % dbname]]
def generate_params_report():
for dbname, location in P.asDict("databases").iteritems():
yield [glob.glob("fuzzy_k/%s-summary-cluster-*-*-*.*" % dbname),
"best_conditions/clustering_summary_%s.txt" % dbname]
def generate_enrichments_high_expn_params():
for min_rpkm in PARAMS["min_rpkm_tree"]:
for dbname, location in P.asDict("databases").iteritems():
yield [ ['mappings/unique.rpkm.all', location],
"high_expn/high_expn.%s.%s" % (dbname, min_rpkm), min_rpkm ]
def generate_calculate_term_params():
for dbname, location in P.asDict("databases").iteritems():
yield [ "mappings/unique.rpkm.all", "mappings/unique.term_patterns.%s" % dbname, location ]
def generate_params_report():
for dbname, location in P.asDict("databases").iteritems():
yield [
glob.glob("fuzzy_k/%s-summary-cluster-*-*-*.*" % dbname),
"best_conditions/clustering_summary_%s.txt" % dbname
]
def generate_enrichments_high_expn_params():
for min_rpkm in PARAMS["min_rpkm_tree"]:
for dbname, location in P.asDict("databases").iteritems():
yield [['mappings/unique.rpkm.all', location],
"high_expn/high_expn.%s.%s" % (dbname, min_rpkm), min_rpkm]
def generate_calculate_term_params():
for dbname, location in P.asDict("databases").iteritems():
yield [
"mappings/unique.rpkm.all",
"mappings/unique.term_patterns.%s" % dbname, location
]
