def samples():
"""
Flask function to show list of all samples in the database.
"""
mgr = sample_manager(db="test",conn=g.conn)
rows = mgr.get_all_samples()
return render_template("samples.html", sample_rows=rows, columns=["sample_id","study_name", "files","attributes"])
def _variants():
query = GaussQuery(db="test", conn=g.conn)
if is_arg("sample_id"):
sample_mgr = sample_manager(db="test", conn=g.conn)
sample_id = sample_mgr.get_sample(request.args["sample_id"])["_id"]
query.add("sample_id", sample_id)
if is_arg("gene"):
query.add("annotations.EFF.g", request.args["gene"])
if is_arg("isoform"):
query.add("annotations.EFF.tx", request.args["isoform"])
if is_arg("chrom") and is_arg("start") and is_arg("end"):
chrom = request.args["chrom"].lower().replace("chr", "")
start = int(request.args["start"])
end = int(request.args["end"])
query.add("chrom", chrom)
query.add("start", {'$gte': start, '$lte': end})
if is_arg("limit"):
query.set_limit(request.args["limit"])
if is_arg("skip"):
query.set_skip(request.args["skip"])
if is_arg("columns"):
for c in request.args["columns"].rstrip(";").split(";"):
query.add_column(c)
if is_arg("exclude_filters"):
for f in request.args["exclude_filters"].split(";"):
query.add_exclude_filter(f)
if is_arg("include_filters"):
for f in request.args["include_filters"].strip(";").split(";"):
query.add_include_filter(f)
if is_arg("group"):
query.set_grouping(request.args["group"])
query.execute()
return query.get_results(format="datatables")
def samples_info(sample_id):
"""
Flask function to return sample info page. Returns a summary of
the number of variants in this sample, as well as the files attached
to this sample and metadata.
"""
mgr = sample_manager(db="test",conn=g.conn)
var_mgr = variant_manager(db="test",conn=g.conn)
data = mgr.get_sample(sample_id = sample_id)
effect_summary = var_mgr.get_sample_variant_summary(data["_id"])
for row in effect_summary:
eff_code = row["_id"]
eff_type = VARIANT_EFFECTS[eff_code]
eff_rank = VARIANT_RANKS[eff_type]
row["effect_str"] = Markup("<span class='label impact-tag %s'>%s</span>" % (eff_type, VARIANT_SHORTNAMES[eff_code]))
row["effect_rank"] = eff_rank
rank_sort = np.argsort(map(operator.itemgetter("effect_rank"), effect_summary))
data["variant_summary"] = [effect_summary[i] for i in rank_sort[::-1]]
return render_template("sample_info.html", sample_id=sample_id, info=data)
