Initial import

scripts/lpls/rpy_go.py

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+""" Module for Gene ontology related functions called in R"""
+import scipy
+
+import rpy
+silent_eval = rpy.with_mode(rpy.NO_CONVERSION, rpy.r)
+
+def get_term_sim(termlist, method = "JiangConrath", verbose=False):
+    """Returns the similariy matrix between go-terms.
+
+    Arguments:
+        termlist: character vector of GO terms
+        method: one of
+        ("JiangConrath","Resnik","Lin","CoutoEnriched","CoutoJiangConrath","CoutoResnik","CoutoLin")
+        verbose: print out various information or not
+    """
+    _methods = ("JiangConrath","Resnik","Lin","CoutoEnriched","CoutoJiangConrath","CoutoResnik","CoutoLin")
+    assert(method in _methods)
+    assert(termlist[0][:2]=='GO')
+    rpy.r.library("GOSim")
+    return rpy.r.getTermSim(termlist, method = method, verbose = verbose)
+
+def get_gene_sim(genelist, similarity='OA',
+                 distance="Resnick"):
+    rpy.r.library("GOSim")
+    rpy.r.assign("ids", genelist)
+    silent_eval('a<-getGeneSim(ids)', verbose=FALSE)
+
+def goterms_from_gene(genelist, ontology=['BP'], garbage = ['IEA', 'ISS', 'ND']):
+    """ Returns the go-terms from a specified genelist (Entrez id).
+    
+    """
+    rpy.r.library("GO")
+    _CODES = {"IMP" : "inferred from mutant phenotype",
+              "IGI" : "inferred from genetic interaction",
+              "IPI" :"inferred from physical interaction",
+              "ISS" : "inferred from sequence similarity",
+              "IDA" : "inferred from direct assay",
+              "IEP" : "inferred from expression pattern",
+              "IEA" : "inferred from electronic annotation",
+              "TAS" : "traceable author statement",
+              "NAS" : "non-traceable author statement",
+              "ND" : "no biological data available",
+              "IC" : "inferred by curator"
+              }
+    _ONTOLOGIES = ['BP', 'CC', 'MF']
+    assert(scipy.all([(code in _CODES) for code in garbage]))
+    assert(scipy.all([(ont in _ONTOLOGIES) for ont in ontology]))
+    
+    goterms = {}
+    for gene in genelist:
+        goterms[gene] = []
+        info = rpy.r('GOENTREZID2GO[["' + str(gene) + '"]]')
+        #print info
+        if info:
+            for term, desc in info.items():
+                if desc['Ontology'] in ontology and desc['Evidence'] not in garbage:
+                        goterms[gene].append(term)
+    return goterms
+
+def genego_matrix(goterms, tmat, gene_ids, term_ids, func=min):
+    ngenes = len(gene_ids)
+    nterms = len(term_ids)
+    gene2indx = {}
+    for i,id in enumerate(gene_ids):
+        gene2indx[id]=i
+    term2indx = {}
+    for i,id in enumerate(term_ids):
+        term2indx[id]=i
+    #G = scipy.empty((nterms, ngenes),'d')
+    G = []
+    newindex = []
+    for gene, terms in goterms.items():
+        g_ind = gene2indx[gene]
+        if len(terms)>0:
+            t_ind = []
+            newindex.append(g_ind)
+            for term in terms:
+                if term2indx.has_key(term): t_ind.append(term2indx[term])
+            print t_ind
+            subsim = tmat[t_ind, :]
+            gene_vec = scipy.apply_along_axis(func, 0, subsim)
+            G.append(gene_vec)
+
+    return scipy.asarray(G), newindex
+
+def goterm2desc(gotermlist):
+    """Returns the go-terms description keyed by go-term
+    """
+    rpy.r.library("GO")
+    term2desc = {}
+    for term in gotermlist:
+        try:
+            desc = rpy.r('Term(GOTERM[["' +str(term)+ '"]])')
+            term2desc[str(term)] = desc
+        except:
+            raise Warning("Description not found for %s\n Mapping incomplete" %term)
+    return term2desc
+
+def parents_dag(go_terms, ontology=['BP']):
+    """ Returns a list of lists representation of a GO DAG parents of goterms."""
+    try:
+        rpy.r.library("GOstats")
+    except:
+        raise ImportError, "Gostats"
+    assert(go_terms[0][:3]=='GO:')
+
+    # go valid namespace
+    go_env = {'BP':rpy.r.BPPARENTS, 'MF':rpy.r.MFPARENTS, 'CC': rpy.r.CCPARENTS}
+    
+