def __init__(self, pw, assembly):
self.pw = pw
checkAssembly(assembly)
self.assembly = assembly
pg = PGcommon(self.pw, self.assembly)
self.ctmap = pg.makeCtMap()
self.ctsTable = pg.makeCTStable()
# does does gwas_enrichment_fdr table exist for this assembly?
self.wenrichment = {}
tn = assembly + "_gwas_enrichment_fdr"
hasTable = assembly == "GRCh38"
if hasTable:
cols = self.pw.description(
"PGgwas", """
SELECT * FROM {tn} LIMIT 0""".format(tn=tn), {})
self.wenrichment = {x[0]: True for x in cols}
class PGsearch(object):
def __init__(self, pw, assembly):
self.pw = pw
checkAssembly(assembly)
self.assembly = assembly
self.pgc = PGcommon(self.pw, self.assembly)
self.pgg = PGgwas(self.pw, self.assembly)
self.ctmap = self.pgc.makeCtMap()
self.ctsTable = self.pgc.makeCTStable()
def vista(self, accession):
rows = self.pw.fetchall(
"vista", """
SELECT * from {vtn}
WHERE accession = %(acc)s""".format(vtn=self.assembly + "_vista"),
{"acc": accession})
return [{"vid": x[2]} for x in rows]
def versions(self):
rows = self.pw.fetchall(
"versions", """
SELECT accession, biosample, assay, version
FROM {tn}""".format(tn=self.assembly + "_ground_level_versions"))
return rows
def gwasJson(self, j, json):
self.pgg.gwasPercentActive(j["gwas_study"], j["cellType"], json)
def allCREs(self):
rows = self.pw.fetchall(
"allCREs", """
SELECT {tn}.accession AS accession, chrom, start, stop
FROM {tn}
INNER JOIN {ttn} ON {ttn}.accession = {tn}.accession
""".format(tn=self.assembly + "_cre_all",
ttn=self.assembly + "_ccres_toptier"))
return [{
"accession": e[0],
"chrom": e[1],
"start": e[2],
"end": e[3]
} for e in rows]
def chromCounts(self):
rows = self.pw.fetchall(
"chromCounts", """
SELECT chrom, count from {tn}
""".format(tn=self.assembly + "_cre_all_nums"))
arr = [(e[0], e[1]) for e in rows]
return natsorted(arr, key=lambda y: y[0])
def creHist(self):
rows = self.pw.fetchall(
"creHist", """
SELECT chrom, buckets, numBins, binMax from {tn}
""".format(tn=self.assembly + "_cre_bins"))
return {
e[0]: {
"bins": e[1],
"numBins": e[2],
"binMax": e[3]
}
for e in rows
}
def rfacets_active(self, j):
present = []
ct = j.get("cellType", None)
if ct:
for assay in ["dnase", "promoter", "enhancer", "ctcf"]:
if ct in self.ctmap[assay]:
present.append(assay)
return present
def haveSCT(self, j):
ct = j.get("cellType", None)
ret = []
if ct:
if ct in self.ctsTable:
ret = ["sctv"]
return ret
def creTable(self, j, chrom, start, stop):
pct = PGcreTable(self.pw, self.assembly, self.ctmap, self.ctsTable)
return pct.creTable(j, chrom, start, stop)
def geneTable(self, j, chrom, start, stop):
pct = PGcreTable(self.pw, self.assembly, self.ctmap, self.ctsTable)
return pct.geneTable(j, chrom, start, stop)
def creTableDownloadBed(self, j, fnp):
pct = PGcreTable(self.pw, self.assembly, self.ctmap, self.ctsTable)
return pct.creTableDownloadBed(j, fnp)
def creTableDownloadJson(self, j, fnp):
pct = PGcreTable(self.pw, self.assembly, self.ctmap, self.ctsTable)
return pct.creTableDownloadJson(j, fnp)
def crePos(self, accession):
r = self.pw.fetchone(
"cre_pos", """
SELECT chrom, start, stop
FROM {tn}
WHERE accession = %s
""".format(tn=self.assembly + "_cre_all"), (accession, ))
if not r:
print("ERROR: missing", accession)
return None
return Coord(r[0], r[1], r[2])
def _getGenes(self, accession, chrom, allOrPc):
rows = self.pw.fetchall(
"_getGenes", """
SELECT gi.approved_symbol, g.distance, gi.ensemblid_ver,
gi.chrom, gi.start, gi.stop
FROM
(SELECT UNNEST(gene_{allOrPc}_id) geneid,
UNNEST(gene_{allOrPc}_distance) distance
FROM {tn} WHERE accession = %s) AS g
INNER JOIN {gtn} AS gi
ON g.geneid = gi.geneid
""".format(tn=self.assembly + "_cre_all",
gtn=self.assembly + "_gene_info",
allOrPc=allOrPc), (accession, ))
return rows
def creGenes(self, accession, chrom):
return (self._getGenes(accession, chrom,
"all"), self._getGenes(accession, chrom, "pc"))
def geneInfo(self, gene):
r = self.pw.fetchoneAsNamedTuples(
"pg$geneInfo", """
SELECT *
FROM {gtn}
WHERE approved_symbol = %s
OR ensemblid = %s
OR ensemblid_ver = %s
""".format(gtn=self.assembly + "_gene_info"), (gene, gene, gene))
return r
def intersectingSnps(self, accession, coord, halfWindow):
c = coord.expanded(halfWindow)
rows = self.pw.fetchall(
"intersectingSnps", """
SELECT start, stop, snp
FROM {tn}
WHERE chrom = %s
AND int4range(start, stop) && int4range(%s, %s)
""".format(tn=self.assembly + "_snps"), (c.chrom, c.start, c.end))
ret = []
for snp in rows:
start = snp[0]
end = snp[1]
ret.append({
"chrom":
c.chrom,
"cre_start":
coord.start,
"cre_end":
coord.end,
"accession":
accession,
"snp_start":
start,
"snp_end":
end,
"name":
snp[2],
"distance":
min(abs(coord.end - end), abs(coord.start - start))
})
return ret
def nearbyCREs(self, coord, halfWindow, cols, isProximalOrDistal):
c = coord.expanded(halfWindow)
tableName = self.assembly + "_cre_all"
q = """
SELECT {cols} FROM {tn} INNER JOIN {ttn} ON {tn}.accession = {ttn}.accession
WHERE chrom = %s
AND int4range(start, stop) && int4range(%s, %s)
""".format(cols=','.join(cols),
tn=tableName,
ttn=self.assembly + "_ccres_toptier")
if isProximalOrDistal is not None:
q += """
AND isProximal is {isProx}
""".format(isProx=str(isProximalOrDistal))
rows = self.pw.fetchall("nearbyCREs", q, (c.chrom, c.start, c.end))
return rows
def distToNearbyCREs(self, accession, coord, halfWindow):
cols = [
"start", "stop", self.assembly + "_cre_all.accession AS accession"
]
cres = self.nearbyCREs(coord, halfWindow, cols, None)
ret = []
for c in cres:
acc = c[2]
if acc == accession:
continue
start = c[0]
end = c[1]
ret.append({
"name":
acc,
"distance":
min(abs(coord.end - end), abs(coord.start - start))
})
return ret
def cresInTad(self, accession, chrom, start):
rows = self.pw.fetchall(
"cresInTad", """
SELECT {cre}.accession AS accession, abs(%s - start) AS distance
FROM {cre} INNER JOIN {ttn} ON {cre}.accession = {ttn}.accession
WHERE chrom = %s
AND int4range(start, stop) && int4range(
(SELECT int4range(min(start), max(stop))
FROM {ti} ti
inner join {tads} tads
on ti.tadname = tads.tadname
WHERE accession = %s))
AND abs(%s - start) < 100000
ORDER BY 2
""".format(cre=self.assembly + "_cre_all",
ttn=self.assembly + "_ccres_toptier",
ti=self.assembly + "_tads_info",
tads=self.assembly + "_tads"),
(start, chrom, accession, start))
frows = [x for x in rows if x[0] != accession]
return [{"accession": r[0], "distance": r[1]} for r in frows]
def genesInTad(self, accession, chrom):
rows = self.pw.fetchall(
"genesInTad", """
SELECT geneIDs
FROM {tn}
WHERE accession = %s
""".format(tn=self.assembly + "_tads"), (accession, ))
return rows
def rankMethodToIDxToCellType(self):
pg = PGcommon(self.pw, self.assembly)
return pg.rankMethodToIDxToCellType()
def rankMethodToCellTypes(self):
rows = self.pw.fetchall(
"pg$getRanIdxToCellType", """
SELECT idx, celltype, rankmethod
FROM {assembly}_rankcelltypeindexex
""".format(assembly=self.assembly))
_map = {}
for r in rows:
_map[r[2]] = [
(r[0], r[1])
] if r[2] not in _map else _map[r[2]] + [(r[0], r[1])]
ret = {}
for k, v in _map.items():
ret[k] = [x[1] for x in sorted(v, key=lambda a: a[0])]
#print(k, ret[k])
#print(ret.keys())
# ['Enhancer', 'H3K4me3', 'H3K27ac', 'Promoter', 'DNase', 'Insulator', 'CTCF']
return ret
def _getColsForAccession(self, accession, chrom, cols):
row = self.pw.fetchone(
"_getColsForAccession", """
SELECT {cols}
FROM {tn}
WHERE accession = %s
""".format(cols=','.join(cols), tn=self.assembly + "_cre_all"),
(accession, ))
return row
def creRanksPromoter(self, accession, chrom):
cols = ["promoter_zscores"]
r = self._getColsForAccession(accession, chrom, cols)
return {"zscores": {"Promoter": r[0]}}
def creRanksEnhancer(self, accession, chrom):
cols = ["enhancer_zscores"]
r = self._getColsForAccession(accession, chrom, cols)
return {"zscores": {"Enhancer": r[0]}}
def creRanks(self, accession, chrom):
cols = """dnase_zscores
ctcf_zscores
enhancer_zscores
h3k27ac_zscores
h3k4me3_zscores
insulator_zscores
promoter_zscores
dnase_max
h3k4me3_max
h3k27ac_max
ctcf_max
pct""".split('\n')
cols = [c.strip() for c in cols]
r = self._getColsForAccession(accession, chrom, cols)
group = r[-1]
r = r[:-1]
cols = [c.split('_')[0] if "max" not in c else c for c in cols][:-1]
return (dict(list(zip(cols, r))), group)
def creMostsimilar(self, acc, assay, threshold=20000):
if self.assembly == "hg19":
return []
def whereclause(r):
_assay = assay
if assay != "dnase":
_assay = assay.replace("_dnase", "") + "_only"
return " or ".join([
"%s_rank[%d] < %d" % (_assay, i + 1, threshold)
for i in range(len(r)) if r[i] < threshold
])
r = self.pw.fetchone(
"cre$CRE::mostsimilar", """
SELECT {assay}_rank
FROM {assembly}_cre_all
WHERE accession = %s
""".format(assay=assay, assembly=self.assembly), acc)
if not r:
if 0:
print("cre$CRE::mostsimilar WARNING: no results for accession",
acc, " -- returning empty set")
return []
whereclause = whereclause(r[0])
if len(whereclause.split(" or ")) > 200:
if 0:
print("cre$CRE::mostsimilar", "NOTICE:", acc,
"is active in too many cell types",
len(whereclause.split(" or ")), "returning empty set")
return []
if not whereclause:
if 0:
print("cre$CRE::mostsimilar NOTICE:", acc,
"not active in any cell types; returning empty set")
return []
rows = self.pw.fetchall(
"pg_search", """
SELECT accession,
intarraysimilarity(%(r)s, {assay}_rank, {threshold}) AS similarity,
chrom, start, stop
FROM {assembly}_cre_all
WHERE {whereclause}
ORDER BY similarity DESC LIMIT 10
""".format(assay=assay,
assembly=self.assembly,
threshold=threshold,
whereclause=whereclause), {"r": r})
return [{
"accession": r[0],
"chrom": r[2],
"start": r[3],
"end": r[4]
} for r in rows]
def _intersections_tablename(self, metadata=False, eset=None):
if eset not in [None, "cistrome", "peak"]:
raise Exception(
"pg$PGSearch::_intersections_tablename: invalid dataset %s" %
eset)
if eset is None:
eset = "peak"
return eset + "Intersections" + ("" if not metadata else "Metadata")
def peakIntersectCount(self, accession, chrom, totals, eset=None):
r = self.pw.fetchone(
"peakIntersectCount", """
SELECT tf, histone
FROM {tn}
WHERE accession = %s
""".format(tn=self.assembly + "_" +
self._intersections_tablename(eset=eset)), (accession, ))
if not r:
return {"tfs": [], "histone": []}
tfs = [{
"name": k,
"n": len(set(v)),
"total": totals.get(k, -1)
} for k, v in r[0].items()]
histones = [{
"name": k,
"n": len(set(v)),
"total": totals.get(k, -1)
} for k, v in r[1].items()]
return {"tf": tfs, "histone": histones}
def tfHistoneDnaseList(self, eset=None):
rows = self.pw.fetchall(
"peakIntersectCount", """
SELECT distinct label
FROM {tn}
""".format(tn=self.assembly + "_" +
self._intersections_tablename(metadata=True, eset=eset)))
return sorted([r[0] for r in rows])
def genePos(self, gene):
ensemblid = gene
if gene.startswith("ENS") and '.' in gene:
ensemblid = gene.split('.')[0]
r = self.pw.fetchone(
"cre_pos", """
SELECT chrom, start, stop, approved_symbol, ensemblid_ver FROM {tn}
WHERE chrom != ''
AND (approved_symbol = %s
OR ensemblid = %s
OR ensemblid_ver = %s)
""".format(tn=self.assembly + "_gene_info"), (gene, ensemblid, gene))
if not r:
print("ERROR: missing", gene)
return None, None
return Coord(r[0], r[1], r[2]), (r[3], r[4])
def allDatasets(self):
# TODO: fixme!!
dects = """
C57BL/6_embryonic_facial_prominence_embryo_11.5_days
C57BL/6_embryonic_facial_prominence_embryo_12.5_days
C57BL/6_embryonic_facial_prominence_embryo_13.5_days
C57BL/6_embryonic_facial_prominence_embryo_14.5_days
C57BL/6_embryonic_facial_prominence_embryo_15.5_days
C57BL/6_forebrain_embryo_11.5_days
C57BL/6_forebrain_embryo_12.5_days
C57BL/6_forebrain_embryo_13.5_days
C57BL/6_forebrain_embryo_14.5_days
C57BL/6_forebrain_embryo_15.5_days
C57BL/6_forebrain_embryo_16.5_days
C57BL/6_forebrain_postnatal_0_days
C57BL/6_heart_embryo_11.5_days
C57BL/6_heart_embryo_12.5_days
C57BL/6_heart_embryo_13.5_days
C57BL/6_heart_embryo_14.5_days
C57BL/6_heart_embryo_15.5_days
C57BL/6_heart_embryo_16.5_days
C57BL/6_heart_postnatal_0_days
C57BL/6_hindbrain_embryo_11.5_days
C57BL/6_hindbrain_embryo_12.5_days
C57BL/6_hindbrain_embryo_13.5_days
C57BL/6_hindbrain_embryo_14.5_days
C57BL/6_hindbrain_embryo_15.5_days
C57BL/6_hindbrain_embryo_16.5_days
C57BL/6_hindbrain_postnatal_0_days
C57BL/6_intestine_embryo_14.5_days
C57BL/6_intestine_embryo_15.5_days
C57BL/6_intestine_embryo_16.5_days
C57BL/6_intestine_postnatal_0_days
C57BL/6_kidney_embryo_14.5_days
C57BL/6_kidney_embryo_15.5_days
C57BL/6_kidney_embryo_16.5_days
C57BL/6_kidney_postnatal_0_days
C57BL/6_limb_embryo_11.5_days
C57BL/6_limb_embryo_12.5_days
C57BL/6_limb_embryo_13.5_days
C57BL/6_limb_embryo_14.5_days
C57BL/6_limb_embryo_15.5_days
C57BL/6_liver_embryo_11.5_days
C57BL/6_liver_embryo_12.5_days
C57BL/6_liver_embryo_13.5_days
C57BL/6_liver_embryo_14.5_days
C57BL/6_liver_embryo_15.5_days
C57BL/6_liver_embryo_16.5_days
C57BL/6_liver_postnatal_0_days
C57BL/6_lung_embryo_14.5_days
C57BL/6_lung_embryo_15.5_days
C57BL/6_lung_embryo_16.5_days
C57BL/6_lung_postnatal_0_days
C57BL/6_midbrain_embryo_11.5_days
C57BL/6_midbrain_embryo_12.5_days
C57BL/6_midbrain_embryo_13.5_days
C57BL/6_midbrain_embryo_14.5_days
C57BL/6_midbrain_embryo_15.5_days
C57BL/6_midbrain_embryo_16.5_days
C57BL/6_midbrain_postnatal_0_days
C57BL/6_neural_tube_embryo_11.5_days
C57BL/6_neural_tube_embryo_12.5_days
C57BL/6_neural_tube_embryo_13.5_days
C57BL/6_neural_tube_embryo_14.5_days
C57BL/6_neural_tube_embryo_15.5_days
C57BL/6_stomach_embryo_14.5_days
C57BL/6_stomach_embryo_15.5_days
C57BL/6_stomach_embryo_16.5_days
C57BL/6_stomach_postnatal_0_days""".split('\n')
dects = set(dects)
def makeDataset(r):
return {
"assay": r[0],
"expID": r[1],
"fileID": r[2],
"tissue": r[3],
"biosample_summary": r[4],
"biosample_type": r[5],
"cellTypeName": r[6],
"cellTypeDesc": r[7],
"name": r[7],
"value": r[6], # for datatables
"isde": r[6] in dects,
"synonyms": r[8]
}
cols = [
"assay", "expID", "fileID", "tissue", "biosample_summary",
"biosample_type", "cellTypeName", "cellTypeDesc", "synonyms"
]
rows = self.pw.fetchall(
"datasets", """
SELECT {cols} FROM {tn}
""".format(tn=self.assembly + "_datasets", cols=','.join(cols)))
return [makeDataset(r) for r in rows]
def datasets(self, assay):
return self.pgc.datasets(assay)
def genemap(self):
rows = self.pw.fetchall(
"pg::genemap", """
SELECT ensemblid, approved_symbol, strand
FROM {tn}
WHERE strand != ''
""".format(tn=self.assembly + "_gene_info"))
toSymbol = {r[0]: r[1] for r in rows}
toStrand = {r[0]: r[2] for r in rows}
rows = self.pw.fetchall(
"pg::genemap", """
SELECT ensemblid_ver, approved_symbol, strand
FROM {tn}
WHERE strand != ''
""".format(tn=self.assembly + "_gene_info"))
toSymbol.update({r[0]: r[1] for r in rows})
toStrand.update({r[0]: r[2] for r in rows})
return toSymbol, toStrand
def genesInRegion(self, chrom, start, stop):
fields = ["approved_symbol", "start", "stop", "strand"]
rows = self.pw.fetchall(
"genesinregion", """
SELECT {fields}
FROM {tn}
WHERE chrom = %s
AND int4range(start, stop) && int4range(%s, %s)
ORDER BY start
""".format(fields=','.join(fields), tn=self.assembly + "_gene_info"),
(chrom, start, stop))
fields = ["gene", "start", "stop", "strand"]
return [dict(list(zip(fields, r))) for r in rows]
def histoneTargetExps(self, accession, target, eset=None):
peakTn = self.assembly + "_" + self._intersections_tablename(eset=eset)
peakMetadataTn = self.assembly + "_" + self._intersections_tablename(
metadata=True, eset=eset)
rows = self.pw.fetchall(
"histoneTargetExps", """
SELECT {eid}fileID, biosample_term_name{tissue}
FROM {peakMetadataTn}
WHERE fileID IN (
SELECT distinct(jsonb_array_elements_text(histone->%s))
FROM {peakTn}
WHERE accession = %s
)
ORDER BY biosample_term_name
""".format(eid=("" if eset == "cistrome" else "expID, "),
tissue=(", tissue" if eset == "cistrome" else ""),
peakTn=peakTn,
peakMetadataTn=peakMetadataTn), (target, accession))
return [{
"expID":
r[0] if eset == "cistrome" else (r[0] + ' / ' + r[1]),
"biosample_term_name":
r[1 if (eset == "cistrome" and r[1] != "None") else 2]
} for r in rows]
def tfTargetExps(self, accession, target, eset=None):
peakTn = self.assembly + "_" + self._intersections_tablename(
metadata=False, eset=eset)
peakMetadataTn = self.assembly + "_" + self._intersections_tablename(
metadata=True, eset=eset)
rows = self.pw.fetchall(
"tfTargetExps", """
SELECT {eid}fileID, biosample_term_name
FROM {peakMetadataTn}
WHERE fileID IN (
SELECT distinct(jsonb_array_elements_text(tf->%s))
FROM {peakTn}
WHERE accession = %s
)
ORDER BY biosample_term_name
""".format(eid="" if eset == "cistrome" else "expID, ",
peakTn=peakTn,
peakMetadataTn=peakMetadataTn), (target, accession))
return [{
"expID": r[0] if eset == "cistrome" else (r[0] + ' / ' + r[1]),
"biosample_term_name": r[1 if eset == "cistrome" else 2]
} for r in rows]
def rampageByGene(self, ensemblid_ver):
rows = self.pw.fetchallAsDict(
"rampageByGene", """
SELECT *
FROM {tn}
WHERE ensemblid_ver = %s
""".format(tn=self.assembly + "_rampage"), (ensemblid_ver, ))
ret = []
for r in rows:
nr = {"data": {}}
for k, v in r.items():
if k.startswith("encff"):
nr["data"][k] = v
continue
nr[k] = v
if not nr["data"]:
continue
ret.append(nr)
return ret
def rampage_info(self):
rows = self.pw.fetchallAsDict(
"rampageInfo", """
SELECT *
FROM {tn}
""".format(tn=self.assembly + "_rampage_info"))
ret = {}
for r in rows:
ret[r["fileid"]] = r
return ret
def rampageEnsemblID(self, gene):
r = self.pw.fetchone(
"rampageEnsemblID", """
SELECT ensemblid_ver
FROM {assembly}_gene_info
WHERE approved_symbol = %(gene)s
""".format(assembly=self.assembly), {"gene": gene})
return r[0]
def geBiosampleTypes(self):
rows = self.pw.fetchall(
"geBiosampleTypes", """
SELECT DISTINCT(biosample_type)
FROM {tn}
ORDER BY 1
""".format(tn=self.assembly + "_rnaseq_exps"))
return [r[0] for r in rows]
def geneIDsToApprovedSymbol(self):
rows = self.pw.fetchall(
"geneIDsToApprovedSymbol", """
SELECT geneid, approved_symbol
FROM {gtn}
ORDER BY 1
""".format(gtn=self.assembly + "_gene_info"))
return {r[0]: r[1] for r in rows}
def getHelpKeys(self):
rows = self.pw.fetchall(
"getHelpKeys", """
SELECT key, title, summary
FROM helpkeys
""")
return {r[0]: {"title": r[1], "summary": r[2]} for r in rows}
def tfHistCounts(self, eset=None):
if eset is None:
eset = "peak"
rows = self.pw.fetchall(
"tfHistCounts", """
SELECT COUNT(label), label
FROM {assembly}_{eset}intersectionsmetadata
GROUP BY label
""".format(assembly=self.assembly, eset=eset))
return {r[1]: r[0] for r in rows}
def geneExpressionTissues(self):
rows = self.pw.fetchall(
"geneExpressionTissues", """
SELECT DISTINCT(organ)
FROM {assembly}_rnaseq_exps
""".format(assembly=self.assembly))
return [r[0] for r in rows]
def loadNineStateGenomeBrowser(self):
rows = self.pw.fetchallAsDict(
"loadNineStateGenomeBrowser", """
SELECT cellTypeName, cellTypeDesc, dnase, h3k4me3,
h3k27ac, ctcf, assembly, tissue
FROM {tn}
""".format(tn=self.assembly + "_nine_state"))
ret = {}
for r in rows:
for k in ["dnase", "h3k4me3", "h3k27ac", "ctcf"]:
fileID = r[k]
if "NA" == fileID:
url = ""
else:
fn = fileID + ".bigBed.bed.gz"
url = "http://bib7.umassmed.edu/~purcarom/screen/ver4/v10/9-State/" + fn
r[k + "_url"] = url
ret[r["celltypename"]] = r
return ret
def loadMoreTracks(self):
rows = self.pw.fetchall(
"loadMoreTracks", """
SELECT cellTypeName, tracks
FROM {tn}
""".format(tn=self.assembly + "_more_tracks"))
ret = {}
for r in rows:
ret[r[0]] = r[1]
return ret
def linkedGenes(self, accession):
rows = self.pw.fetchallAsDict(
"linkedGenes", """
SELECT gene, celltype, method, dccaccession
FROM {tn}
WHERE cre = %s
""".format(tn=self.assembly + "_linked_genes"), (accession, ))
return rows
def creBigBeds(self):
rows = self.pw.fetchall(
"creBigBeds", """
SELECT celltype, dcc_accession, typ
FROM {tn}
""".format(tn=self.assembly + "_dcc_cres"))
ret = {}
for ct, acc, typ in rows:
if ct not in ret:
ret[ct] = {}
ret[ct][typ] = acc
return ret
def creBeds(self):
rows = self.pw.fetchall(
"creBeds", """
SELECT celltype, dcc_accession, typ
FROM {tn}
""".format(tn=self.assembly + "_dcc_cres_beds"))
ret = {}
for ct, acc, typ in rows:
if ct not in ret:
ret[ct] = {}
ret[ct][typ] = acc
return ret