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-rw-r--r--gn3/api/heatmaps.py36
-rw-r--r--gn3/app.py12
-rw-r--r--gn3/computations/heatmap.py177
-rw-r--r--gn3/computations/parsers.py10
-rw-r--r--gn3/computations/qtlreaper.py170
-rw-r--r--gn3/db/datasets.py52
-rw-r--r--gn3/db/genotypes.py184
-rw-r--r--gn3/db/traits.py78
-rw-r--r--gn3/heatmaps.py395
-rw-r--r--gn3/heatmaps/heatmaps.py54
-rw-r--r--gn3/random.py11
-rw-r--r--gn3/settings.py19
12 files changed, 900 insertions, 298 deletions
diff --git a/gn3/api/heatmaps.py b/gn3/api/heatmaps.py
new file mode 100644
index 0000000..62ca2ad
--- /dev/null
+++ b/gn3/api/heatmaps.py
@@ -0,0 +1,36 @@
+"""
+Module to hold the entrypoint functions that generate heatmaps
+"""
+
+import io
+from flask import jsonify
+from flask import request
+from flask import Blueprint
+from gn3.heatmaps import build_heatmap
+from gn3.db_utils import database_connector
+
+heatmaps = Blueprint("heatmaps", __name__)
+
+@heatmaps.route("/clustered", methods=("POST",))
+def clustered_heatmaps():
+ """
+ Parses the incoming data and responds with the JSON-serialized plotly figure
+ representing the clustered heatmap.
+ """
+ traits_names = request.get_json().get("traits_names", tuple())
+ if len(traits_names) < 2:
+ return jsonify({
+ "message": "You need to provide at least two trait names."
+ }), 400
+ conn, _cursor = database_connector()
+ def parse_trait_fullname(trait):
+ name_parts = trait.split(":")
+ return "{dataset_name}::{trait_name}".format(
+ dataset_name=name_parts[1], trait_name=name_parts[0])
+ traits_fullnames = [parse_trait_fullname(trait) for trait in traits_names]
+
+ with io.StringIO() as io_str:
+ _filename, figure = build_heatmap(traits_fullnames, conn)
+ figure.write_json(io_str)
+ fig_json = io_str.getvalue()
+ return fig_json, 200
diff --git a/gn3/app.py b/gn3/app.py
index 046b5de..5e852e1 100644
--- a/gn3/app.py
+++ b/gn3/app.py
@@ -3,20 +3,29 @@ import os
from typing import Dict
from typing import Union
+
from flask import Flask
+from flask_cors import CORS # type: ignore
+
from gn3.api.gemma import gemma
from gn3.api.rqtl import rqtl
from gn3.api.general import general
+from gn3.api.heatmaps import heatmaps
from gn3.api.correlation import correlation
from gn3.api.data_entry import data_entry
-
def create_app(config: Union[Dict, str, None] = None) -> Flask:
"""Create a new flask object"""
app = Flask(__name__)
# Load default configuration
app.config.from_object("gn3.settings")
+ CORS(
+ app,
+ origins=app.config["CORS_ORIGINS"],
+ allow_headers=app.config["CORS_HEADERS"],
+ supports_credentials=True, intercept_exceptions=False)
+
# Load environment configuration
if "GN3_CONF" in os.environ:
app.config.from_envvar('GN3_CONF')
@@ -30,6 +39,7 @@ def create_app(config: Union[Dict, str, None] = None) -> Flask:
app.register_blueprint(general, url_prefix="/api/")
app.register_blueprint(gemma, url_prefix="/api/gemma")
app.register_blueprint(rqtl, url_prefix="/api/rqtl")
+ app.register_blueprint(heatmaps, url_prefix="/api/heatmaps")
app.register_blueprint(correlation, url_prefix="/api/correlation")
app.register_blueprint(data_entry, url_prefix="/api/dataentry")
return app
diff --git a/gn3/computations/heatmap.py b/gn3/computations/heatmap.py
deleted file mode 100644
index 3c35029..0000000
--- a/gn3/computations/heatmap.py
+++ /dev/null
@@ -1,177 +0,0 @@
-"""
-This module will contain functions to be used in computation of the data used to
-generate various kinds of heatmaps.
-"""
-
-from functools import reduce
-from typing import Any, Dict, Sequence
-from gn3.computations.slink import slink
-from gn3.db.traits import retrieve_trait_data, retrieve_trait_info
-from gn3.computations.correlations2 import compute_correlation
-
-def export_trait_data(
- trait_data: dict, strainlist: Sequence[str], dtype: str = "val",
- var_exists: bool = False, n_exists: bool = False):
- """
- Export data according to `strainlist`. Mostly used in calculating
- correlations.
-
- DESCRIPTION:
- Migrated from
- https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L166-L211
-
- PARAMETERS
- trait: (dict)
- The dictionary of key-value pairs representing a trait
- strainlist: (list)
- A list of strain names
- type: (str)
- ... verify what this is ...
- var_exists: (bool)
- A flag indicating existence of variance
- n_exists: (bool)
- A flag indicating existence of ndata
- """
- def __export_all_types(tdata, strain):
- sample_data = []
- if tdata[strain]["value"]:
- sample_data.append(tdata[strain]["value"])
- if var_exists:
- if tdata[strain]["variance"]:
- sample_data.append(tdata[strain]["variance"])
- else:
- sample_data.append(None)
- if n_exists:
- if tdata[strain]["ndata"]:
- sample_data.append(tdata[strain]["ndata"])
- else:
- sample_data.append(None)
- else:
- if var_exists and n_exists:
- sample_data += [None, None, None]
- elif var_exists or n_exists:
- sample_data += [None, None]
- else:
- sample_data.append(None)
-
- return tuple(sample_data)
-
- def __exporter(accumulator, strain):
- # pylint: disable=[R0911]
- if strain in trait_data["data"]:
- if dtype == "val":
- return accumulator + (trait_data["data"][strain]["value"], )
- if dtype == "var":
- return accumulator + (trait_data["data"][strain]["variance"], )
- if dtype == "N":
- return accumulator + (trait_data["data"][strain]["ndata"], )
- if dtype == "all":
- return accumulator + __export_all_types(trait_data["data"], strain)
- raise KeyError("Type `%s` is incorrect" % dtype)
- if var_exists and n_exists:
- return accumulator + (None, None, None)
- if var_exists or n_exists:
- return accumulator + (None, None)
- return accumulator + (None,)
-
- return reduce(__exporter, strainlist, tuple())
-
-def trait_display_name(trait: Dict):
- """
- Given a trait, return a name to use to display the trait on a heatmap.
-
- DESCRIPTION
- Migrated from
- https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L141-L157
- """
- if trait.get("db", None) and trait.get("trait_name", None):
- if trait["db"]["dataset_type"] == "Temp":
- desc = trait["description"]
- if desc.find("PCA") >= 0:
- return "%s::%s" % (
- trait["db"]["displayname"],
- desc[desc.rindex(':')+1:].strip())
- return "%s::%s" % (
- trait["db"]["displayname"],
- desc[:desc.index('entered')].strip())
- prefix = "%s::%s" % (
- trait["db"]["dataset_name"], trait["trait_name"])
- if trait["cellid"]:
- return "%s::%s" % (prefix, trait["cellid"])
- return prefix
- return trait["description"]
-
-def cluster_traits(traits_data_list: Sequence[Dict]):
- """
- Clusters the trait values.
-
- DESCRIPTION
- Attempts to replicate the clustering of the traits, as done at
- https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L138-L162
- """
- def __compute_corr(tdata_i, tdata_j):
- if tdata_i[0] == tdata_j[0]:
- return 0.0
- corr_vals = compute_correlation(tdata_i[1], tdata_j[1])
- corr = corr_vals[0]
- if (1 - corr) < 0:
- return 0.0
- return 1 - corr
-
- def __cluster(tdata_i):
- return tuple(
- __compute_corr(tdata_i, tdata_j)
- for tdata_j in enumerate(traits_data_list))
-
- return tuple(__cluster(tdata_i) for tdata_i in enumerate(traits_data_list))
-
-def heatmap_data(formd, search_result, conn: Any):
- """
- heatmap function
-
- DESCRIPTION
- This function is an attempt to reproduce the initialisation at
- https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L46-L64
- and also the clustering and slink computations at
- https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L138-L165
- with the help of the `gn3.computations.heatmap.cluster_traits` function.
-
- It does not try to actually draw the heatmap image.
-
- PARAMETERS:
- TODO: Elaborate on the parameters here...
- """
- threshold = 0 # webqtlConfig.PUBLICTHRESH
- cluster_checked = formd.formdata.getvalue("clusterCheck", "")
- strainlist = [
- strain for strain in formd.strainlist if strain not in formd.parlist]
- genotype = formd.genotype
-
- def __retrieve_traitlist_and_datalist(threshold, fullname):
- trait = retrieve_trait_info(threshold, fullname, conn)
- return (
- trait,
- export_trait_data(retrieve_trait_data(trait, conn), strainlist))
-
- traits_details = [
- __retrieve_traitlist_and_datalist(threshold, fullname)
- for fullname in search_result]
- traits_list = map(lambda x: x[0], traits_details)
- traits_data_list = map(lambda x: x[1], traits_details)
-
- return {
- "target_description_checked": formd.formdata.getvalue(
- "targetDescriptionCheck", ""),
- "cluster_checked": cluster_checked,
- "slink_data": (
- slink(cluster_traits(traits_data_list))
- if cluster_checked else False),
- "sessionfile": formd.formdata.getvalue("session"),
- "genotype": genotype,
- "nLoci": sum(map(len, genotype)),
- "strainlist": strainlist,
- "ppolar": formd.ppolar,
- "mpolar":formd.mpolar,
- "traits_list": traits_list,
- "traits_data_list": traits_data_list
- }
diff --git a/gn3/computations/parsers.py b/gn3/computations/parsers.py
index 94387ff..1af35d6 100644
--- a/gn3/computations/parsers.py
+++ b/gn3/computations/parsers.py
@@ -14,7 +14,7 @@ def parse_genofile(file_path: str) -> Tuple[List[str],
'h': 0,
'u': None,
}
- genotypes, strains = [], []
+ genotypes, samples = [], []
with open(file_path, "r") as _genofile:
for line in _genofile:
line = line.strip()
@@ -22,8 +22,8 @@ def parse_genofile(file_path: str) -> Tuple[List[str],
continue
cells = line.split()
if line.startswith("Chr"):
- strains = cells[4:]
- strains = [strain.lower() for strain in strains]
+ samples = cells[4:]
+ samples = [sample.lower() for sample in samples]
continue
values = [__map.get(value.lower(), None) for value in cells[4:]]
genotype = {
@@ -32,7 +32,7 @@ def parse_genofile(file_path: str) -> Tuple[List[str],
"cm": cells[2],
"mb": cells[3],
"values": values,
- "dicvalues": dict(zip(strains, values)),
+ "dicvalues": dict(zip(samples, values)),
}
genotypes.append(genotype)
- return strains, genotypes
+ return samples, genotypes
diff --git a/gn3/computations/qtlreaper.py b/gn3/computations/qtlreaper.py
new file mode 100644
index 0000000..d1ff4ac
--- /dev/null
+++ b/gn3/computations/qtlreaper.py
@@ -0,0 +1,170 @@
+"""
+This module contains functions to interact with the `qtlreaper` utility for
+computation of QTLs.
+"""
+import os
+import subprocess
+from typing import Union
+
+from gn3.random import random_string
+from gn3.settings import TMPDIR, REAPER_COMMAND
+
+def generate_traits_file(samples, trait_values, traits_filename):
+ """
+ Generate a traits file for use with `qtlreaper`.
+
+ PARAMETERS:
+ samples: A list of samples to use as the headers for the various columns.
+ trait_values: A list of lists of values for each trait and sample.
+ traits_filename: The tab-separated value to put the values in for
+ computation of QTLs.
+ """
+ header = "Trait\t{}\n".format("\t".join(samples))
+ data = (
+ [header] +
+ ["{}\t{}\n".format(i+1, "\t".join([str(i) for i in t]))
+ for i, t in enumerate(trait_values[:-1])] +
+ ["{}\t{}".format(
+ len(trait_values), "\t".join([str(i) for i in t]))
+ for t in trait_values[-1:]])
+ with open(traits_filename, "w") as outfile:
+ outfile.writelines(data)
+
+def create_output_directory(path: str):
+ """Create the output directory at `path` if it does not exist."""
+ try:
+ os.mkdir(path)
+ except FileExistsError:
+ # If the directory already exists, do nothing.
+ pass
+
+def run_reaper(
+ genotype_filename: str, traits_filename: str,
+ other_options: tuple = ("--n_permutations", "1000"),
+ separate_nperm_output: bool = False,
+ output_dir: str = TMPDIR):
+ """
+ Run the QTLReaper command to compute the QTLs.
+
+ PARAMETERS:
+ genotype_filename: The complete path to a genotype file to use in the QTL
+ computation.
+ traits_filename: A path to a file previously generated with the
+ `generate_traits_file` function in this module, to be used in the QTL
+ computation.
+ other_options: Other options to pass to the `qtlreaper` command to modify
+ the QTL computations.
+ separate_nperm_output: A flag indicating whether or not to provide a
+ separate output for the permutations computation. The default is False,
+ which means by default, no separate output file is created.
+ output_dir: A path to the directory where the outputs are put
+
+ RETURNS:
+ The function returns a tuple of the main output file, and the output file
+ for the permutation computations. If the `separate_nperm_output` is `False`,
+ the second value in the tuple returned is `None`.
+
+ RAISES:
+ The function will raise a `subprocess.CalledProcessError` exception in case
+ of any errors running the `qtlreaper` command.
+ """
+ create_output_directory("{}/qtlreaper".format(output_dir))
+ output_filename = "{}/qtlreaper/main_output_{}.txt".format(
+ output_dir, random_string(10))
+ output_list = ["--main_output", output_filename]
+ if separate_nperm_output:
+ permu_output_filename: Union[None, str] = "{}/qtlreaper/permu_output_{}.txt".format(
+ output_dir, random_string(10))
+ output_list = output_list + [
+ "--permu_output", permu_output_filename] # type: ignore[list-item]
+ else:
+ permu_output_filename = None
+
+ command_list = [
+ REAPER_COMMAND, "--geno", genotype_filename,
+ *other_options, # this splices the `other_options` list here
+ "--traits", traits_filename,
+ *output_list # this splices the `output_list` list here
+ ]
+
+ subprocess.run(command_list, check=True)
+ return (output_filename, permu_output_filename)
+
+def chromosome_sorter_key_fn(val):
+ """
+ Useful for sorting the chromosomes
+ """
+ if isinstance(val, int):
+ return val
+ return ord(val)
+
+def organise_reaper_main_results(parsed_results):
+ """
+ Provide the results of running reaper in a format that is easier to use.
+ """
+ def __organise_by_chromosome(chr_name, items):
+ chr_items = [item for item in items if item["Chr"] == chr_name]
+ return {
+ "Chr": chr_name,
+ "loci": [{
+ "Locus": locus["Locus"],
+ "cM": locus["cM"],
+ "Mb": locus["Mb"],
+ "LRS": locus["LRS"],
+ "Additive": locus["Additive"],
+ "pValue": locus["pValue"]
+ } for locus in chr_items]}
+
+ def __organise_by_id(identifier, items):
+ id_items = [item for item in items if item["ID"] == identifier]
+ unique_chromosomes = {item["Chr"] for item in id_items}
+ return {
+ "ID": identifier,
+ "chromosomes": {
+ _chr["Chr"]: _chr for _chr in [
+ __organise_by_chromosome(chromo, id_items)
+ for chromo in sorted(
+ unique_chromosomes, key=chromosome_sorter_key_fn)]}}
+
+ unique_ids = {res["ID"] for res in parsed_results}
+ return {
+ trait["ID"]: trait for trait in
+ [__organise_by_id(_id, parsed_results) for _id in sorted(unique_ids)]}
+
+def parse_reaper_main_results(results_file):
+ """
+ Parse the results file of running QTLReaper into a list of dicts.
+ """
+ with open(results_file, "r") as infile:
+ lines = infile.readlines()
+
+ def __parse_column_float_value(value):
+ # pylint: disable=W0702
+ try:
+ return float(value)
+ except:
+ return value
+
+ def __parse_column_int_value(value):
+ # pylint: disable=W0702
+ try:
+ return int(value)
+ except:
+ return value
+
+ def __parse_line(line):
+ items = line.strip().split("\t")
+ return items[0:2] + [__parse_column_int_value(items[2])] + [
+ __parse_column_float_value(item) for item in items[3:]]
+
+ header = lines[0].strip().split("\t")
+ return [dict(zip(header, __parse_line(line))) for line in lines[1:]]
+
+def parse_reaper_permutation_results(results_file):
+ """
+ Parse the results QTLReaper permutations into a list of values.
+ """
+ with open(results_file, "r") as infile:
+ lines = infile.readlines()
+
+ return [float(line.strip()) for line in lines]
diff --git a/gn3/db/datasets.py b/gn3/db/datasets.py
index 4a05499..6c328f5 100644
--- a/gn3/db/datasets.py
+++ b/gn3/db/datasets.py
@@ -119,9 +119,9 @@ def retrieve_dataset_name(
return fn_map[trait_type](threshold, dataset_name, conn)
-def retrieve_geno_riset_fields(name, conn):
+def retrieve_geno_group_fields(name, conn):
"""
- Retrieve the RISet, and RISetID values for various Geno trait types.
+ Retrieve the Group, and GroupID values for various Geno trait types.
"""
query = (
"SELECT InbredSet.Name, InbredSet.Id "
@@ -130,12 +130,12 @@ def retrieve_geno_riset_fields(name, conn):
"AND GenoFreeze.Name = %(name)s")
with conn.cursor() as cursor:
cursor.execute(query, {"name": name})
- return dict(zip(["riset", "risetid"], cursor.fetchone()))
+ return dict(zip(["group", "groupid"], cursor.fetchone()))
return {}
-def retrieve_publish_riset_fields(name, conn):
+def retrieve_publish_group_fields(name, conn):
"""
- Retrieve the RISet, and RISetID values for various Publish trait types.
+ Retrieve the Group, and GroupID values for various Publish trait types.
"""
query = (
"SELECT InbredSet.Name, InbredSet.Id "
@@ -144,12 +144,12 @@ def retrieve_publish_riset_fields(name, conn):
"AND PublishFreeze.Name = %(name)s")
with conn.cursor() as cursor:
cursor.execute(query, {"name": name})
- return dict(zip(["riset", "risetid"], cursor.fetchone()))
+ return dict(zip(["group", "groupid"], cursor.fetchone()))
return {}
-def retrieve_probeset_riset_fields(name, conn):
+def retrieve_probeset_group_fields(name, conn):
"""
- Retrieve the RISet, and RISetID values for various ProbeSet trait types.
+ Retrieve the Group, and GroupID values for various ProbeSet trait types.
"""
query = (
"SELECT InbredSet.Name, InbredSet.Id "
@@ -159,12 +159,12 @@ def retrieve_probeset_riset_fields(name, conn):
"AND ProbeSetFreeze.Name = %(name)s")
with conn.cursor() as cursor:
cursor.execute(query, {"name": name})
- return dict(zip(["riset", "risetid"], cursor.fetchone()))
+ return dict(zip(["group", "groupid"], cursor.fetchone()))
return {}
-def retrieve_temp_riset_fields(name, conn):
+def retrieve_temp_group_fields(name, conn):
"""
- Retrieve the RISet, and RISetID values for `Temp` trait types.
+ Retrieve the Group, and GroupID values for `Temp` trait types.
"""
query = (
"SELECT InbredSet.Name, InbredSet.Id "
@@ -173,30 +173,30 @@ def retrieve_temp_riset_fields(name, conn):
"AND Temp.Name = %(name)s")
with conn.cursor() as cursor:
cursor.execute(query, {"name": name})
- return dict(zip(["riset", "risetid"], cursor.fetchone()))
+ return dict(zip(["group", "groupid"], cursor.fetchone()))
return {}
-def retrieve_riset_fields(trait_type, trait_name, dataset_info, conn):
+def retrieve_group_fields(trait_type, trait_name, dataset_info, conn):
"""
- Retrieve the RISet, and RISetID values for various trait types.
+ Retrieve the Group, and GroupID values for various trait types.
"""
- riset_fns_map = {
- "Geno": retrieve_geno_riset_fields,
- "Publish": retrieve_publish_riset_fields,
- "ProbeSet": retrieve_probeset_riset_fields
+ group_fns_map = {
+ "Geno": retrieve_geno_group_fields,
+ "Publish": retrieve_publish_group_fields,
+ "ProbeSet": retrieve_probeset_group_fields
}
if trait_type == "Temp":
- riset_info = retrieve_temp_riset_fields(trait_name, conn)
+ group_info = retrieve_temp_group_fields(trait_name, conn)
else:
- riset_info = riset_fns_map[trait_type](dataset_info["dataset_name"], conn)
+ group_info = group_fns_map[trait_type](dataset_info["dataset_name"], conn)
return {
**dataset_info,
- **riset_info,
- "riset": (
- "BXD" if riset_info.get("riset") == "BXD300"
- else riset_info.get("riset", ""))
+ **group_info,
+ "group": (
+ "BXD" if group_info.get("group") == "BXD300"
+ else group_info.get("group", ""))
}
def retrieve_temp_trait_dataset():
@@ -281,11 +281,11 @@ def retrieve_trait_dataset(trait_type, trait, threshold, conn):
trait_type, threshold, trait["trait_name"],
trait["db"]["dataset_name"], conn)
}
- riset = retrieve_riset_fields(
+ group = retrieve_group_fields(
trait_type, trait["trait_name"], dataset_name_info, conn)
return {
"display_name": dataset_name_info["dataset_name"],
**dataset_name_info,
**dataset_fns[trait_type](),
- **riset
+ **group
}
diff --git a/gn3/db/genotypes.py b/gn3/db/genotypes.py
new file mode 100644
index 0000000..8f18cac
--- /dev/null
+++ b/gn3/db/genotypes.py
@@ -0,0 +1,184 @@
+"""Genotype utilities"""
+
+import os
+import gzip
+from typing import Union, TextIO
+
+from gn3.settings import GENOTYPE_FILES
+
+def build_genotype_file(
+ geno_name: str, base_dir: str = GENOTYPE_FILES,
+ extension: str = "geno"):
+ """Build the absolute path for the genotype file."""
+ return "{}/{}.{}".format(os.path.abspath(base_dir), geno_name, extension)
+
+def load_genotype_samples(genotype_filename: str, file_type: str = "geno"):
+ """
+ Load sample of samples from genotype files.
+
+ DESCRIPTION:
+ Traits can contain a varied number of samples, some of which do not exist in
+ certain genotypes. In order to compute QTLs, GEMMAs, etc, we need to ensure
+ to pick only those samples that exist in the genotype under consideration
+ for the traits used in the computation.
+
+ This function loads a list of samples from the genotype files for use in
+ filtering out unusable samples.
+
+
+ PARAMETERS:
+ genotype_filename: The absolute path to the genotype file to load the
+ samples from.
+ file_type: The type of file. Currently supported values are 'geno' and
+ 'plink'.
+ """
+ file_type_fns = {
+ "geno": __load_genotype_samples_from_geno,
+ "plink": __load_genotype_samples_from_plink
+ }
+ return file_type_fns[file_type](genotype_filename)
+
+def __load_genotype_samples_from_geno(genotype_filename: str):
+ """
+ Helper function for `load_genotype_samples` function.
+
+ Loads samples from '.geno' files.
+ """
+ gzipped_filename = "{}.gz".format(genotype_filename)
+ if os.path.isfile(gzipped_filename):
+ genofile: Union[TextIO, gzip.GzipFile] = gzip.open(gzipped_filename)
+ else:
+ genofile = open(genotype_filename)
+
+ for row in genofile:
+ line = row.strip()
+ if (not line) or (line.startswith(("#", "@"))): # type: ignore[arg-type]
+ continue
+ break
+
+ headers = line.split("\t") # type: ignore[arg-type]
+ if headers[3] == "Mb":
+ return headers[4:]
+ return headers[3:]
+
+def __load_genotype_samples_from_plink(genotype_filename: str):
+ """
+ Helper function for `load_genotype_samples` function.
+
+ Loads samples from '.plink' files.
+ """
+ genofile = open(genotype_filename)
+ return [line.split(" ")[1] for line in genofile]
+
+def parse_genotype_labels(lines: list):
+ """
+ Parse label lines into usable genotype values
+
+ DESCRIPTION:
+ Reworks
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/utility/gen_geno_ob.py#L75-L93
+ """
+ acceptable_labels = ["name", "filler", "type", "mat", "pat", "het", "unk"]
+ def __parse_label(line):
+ label, value = [l.strip() for l in line[1:].split(":")]
+ if label not in acceptable_labels:
+ return None
+ if label == "name":
+ return ("group", value)
+ return (label, value)
+ return tuple(
+ item for item in (__parse_label(line) for line in lines)
+ if item is not None)
+
+def parse_genotype_header(line: str, parlist: tuple = tuple()):
+ """
+ Parse the genotype file header line
+
+ DESCRIPTION:
+ Reworks
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/utility/gen_geno_ob.py#L94-L114
+ """
+ items = [item.strip() for item in line.split("\t")]
+ mbmap = "Mb" in items
+ prgy = ((parlist + tuple(items[4:])) if mbmap
+ else (parlist + tuple(items[3:])))
+ return (
+ ("Mbmap", mbmap),
+ ("cm_column", items.index("cM")),
+ ("mb_column", None if not mbmap else items.index("Mb")),
+ ("prgy", prgy),
+ ("nprgy", len(prgy)))
+
+def parse_genotype_marker(line: str, geno_obj: dict, parlist: tuple):
+ """
+ Parse a data line in a genotype file
+
+ DESCRIPTION:
+ Reworks
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/utility/gen_geno_ob.py#L143-L190
+ """
+ # pylint: disable=W0702
+ marker_row = [item.strip() for item in line.split("\t")]
+ geno_table = {
+ geno_obj["mat"]: -1, geno_obj["pat"]: 1, geno_obj["het"]: 0,
+ geno_obj["unk"]: "U"
+ }
+ start_pos = 4 if geno_obj["Mbmap"] else 3
+ if len(parlist) > 0:
+ start_pos = start_pos + 2
+
+ alleles = marker_row[start_pos:]
+ genotype = tuple(
+ (geno_table[allele] if allele in geno_table.keys() else "U")
+ for allele in alleles)
+ if len(parlist) > 0:
+ genotype = (-1, 1) + genotype
+ try:
+ cm_val = float(geno_obj["cm_column"])
+ except:
+ if geno_obj["Mbmap"]:
+ cm_val = float(geno_obj["mb_column"])
+ else:
+ cm_val = 0
+ return (
+ ("chr", marker_row[0]),
+ ("name", marker_row[1]),
+ ("cM", cm_val),
+ ("Mb", float(geno_obj["mb_column"]) if geno_obj["Mbmap"] else None),
+ ("genotype", genotype))
+
+def build_genotype_chromosomes(geno_obj, markers):
+ """
+ Build up the chromosomes from the given markers and partially built geno
+ object
+ """
+ mrks = [dict(marker) for marker in markers]
+ chr_names = {marker["chr"] for marker in mrks}
+ return tuple((
+ ("name", chr_name), ("mb_exists", geno_obj["Mbmap"]), ("cm_column", 2),
+ ("mb_column", geno_obj["mb_column"]),
+ ("loci", tuple(marker for marker in mrks if marker["chr"] == chr_name)))
+ for chr_name in sorted(chr_names))
+
+def parse_genotype_file(filename: str, parlist: tuple = tuple()):
+ """
+ Parse the provided genotype file into a usable pytho3 data structure.
+ """
+ with open(filename, "r") as infile:
+ contents = infile.readlines()
+
+ lines = tuple(line for line in contents if
+ ((not line.strip().startswith("#")) and
+ (not line.strip() == "")))
+ labels = parse_genotype_labels(
+ [line for line in lines if line.startswith("@")])
+ data_lines = tuple(line for line in lines if not line.startswith("@"))
+ header = parse_genotype_header(data_lines[0], parlist)
+ geno_obj = dict(labels + header)
+ markers = tuple(
+ [parse_genotype_marker(line, geno_obj, parlist)
+ for line in data_lines[1:]])
+ chromosomes = tuple(
+ dict(chromosome) for chromosome in
+ build_genotype_chromosomes(geno_obj, markers))
+ return {**geno_obj, "chromosomes": chromosomes}
diff --git a/gn3/db/traits.py b/gn3/db/traits.py
index 1031e44..f2673c8 100644
--- a/gn3/db/traits.py
+++ b/gn3/db/traits.py
@@ -1,5 +1,8 @@
"""This class contains functions relating to trait data manipulation"""
+import os
from typing import Any, Dict, Union, Sequence
+from gn3.settings import TMPDIR
+from gn3.random import random_string
from gn3.function_helpers import compose
from gn3.db.datasets import retrieve_trait_dataset
@@ -43,7 +46,7 @@ def update_sample_data(conn: Any,
count: Union[int, str]):
"""Given the right parameters, update sample-data from the relevant
table."""
- # pylint: disable=[R0913, R0914]
+ # pylint: disable=[R0913, R0914, C0103]
STRAIN_ID_SQL: str = "UPDATE Strain SET Name = %s WHERE Id = %s"
PUBLISH_DATA_SQL: str = ("UPDATE PublishData SET value = %s "
"WHERE StrainId = %s AND Id = %s")
@@ -60,22 +63,22 @@ def update_sample_data(conn: Any,
with conn.cursor() as cursor:
# Update the Strains table
cursor.execute(STRAIN_ID_SQL, (strain_name, strain_id))
- updated_strains: int = cursor.rowcount
+ updated_strains = cursor.rowcount
# Update the PublishData table
cursor.execute(PUBLISH_DATA_SQL,
(None if value == "x" else value,
strain_id, publish_data_id))
- updated_published_data: int = cursor.rowcount
+ updated_published_data = cursor.rowcount
# Update the PublishSE table
cursor.execute(PUBLISH_SE_SQL,
(None if error == "x" else error,
strain_id, publish_data_id))
- updated_se_data: int = cursor.rowcount
+ updated_se_data = cursor.rowcount
# Update the NStrain table
cursor.execute(N_STRAIN_SQL,
(None if count == "x" else count,
strain_id, publish_data_id))
- updated_n_strains: int = cursor.rowcount
+ updated_n_strains = cursor.rowcount
return (updated_strains, updated_published_data,
updated_se_data, updated_n_strains)
@@ -223,7 +226,7 @@ def set_homologene_id_field_probeset(trait_info, conn):
"""
query = (
"SELECT HomologeneId FROM Homologene, Species, InbredSet"
- " WHERE Homologene.GeneId = %(geneid)s AND InbredSet.Name = %(riset)s"
+ " WHERE Homologene.GeneId = %(geneid)s AND InbredSet.Name = %(group)s"
" AND InbredSet.SpeciesId = Species.Id AND"
" Species.TaxonomyId = Homologene.TaxonomyId")
with conn.cursor() as cursor:
@@ -231,7 +234,7 @@ def set_homologene_id_field_probeset(trait_info, conn):
query,
{
k:v for k, v in trait_info.items()
- if k in ["geneid", "riset"]
+ if k in ["geneid", "group"]
})
res = cursor.fetchone()
if res:
@@ -419,7 +422,7 @@ def retrieve_trait_info(
if trait_info["haveinfo"]:
return {
**trait_post_processing_functions_table[trait_dataset_type](
- {**trait_info, "riset": trait_dataset["riset"]}),
+ {**trait_info, "group": trait_dataset["group"]}),
"db": {**trait["db"], **trait_dataset}
}
return trait_info
@@ -442,18 +445,18 @@ def retrieve_temp_trait_data(trait_info: dict, conn: Any):
query,
{"trait_name": trait_info["trait_name"]})
return [dict(zip(
- ["strain_name", "value", "se_error", "nstrain", "id"], row))
+ ["sample_name", "value", "se_error", "nstrain", "id"], row))
for row in cursor.fetchall()]
return []
-def retrieve_species_id(riset, conn: Any):
+def retrieve_species_id(group, conn: Any):
"""
- Retrieve a species id given the RISet value
+ Retrieve a species id given the Group value
"""
with conn.cursor as cursor:
cursor.execute(
- "SELECT SpeciesId from InbredSet WHERE Name = %(riset)s",
- {"riset": riset})
+ "SELECT SpeciesId from InbredSet WHERE Name = %(group)s",
+ {"group": group})
return cursor.fetchone()[0]
return None
@@ -479,9 +482,9 @@ def retrieve_geno_trait_data(trait_info: Dict, conn: Any):
{"trait_name": trait_info["trait_name"],
"dataset_name": trait_info["db"]["dataset_name"],
"species_id": retrieve_species_id(
- trait_info["db"]["riset"], conn)})
+ trait_info["db"]["group"], conn)})
return [dict(zip(
- ["strain_name", "value", "se_error", "id"], row))
+ ["sample_name", "value", "se_error", "id"], row))
for row in cursor.fetchall()]
return []
@@ -512,7 +515,7 @@ def retrieve_publish_trait_data(trait_info: Dict, conn: Any):
{"trait_name": trait_info["trait_name"],
"dataset_id": trait_info["db"]["dataset_id"]})
return [dict(zip(
- ["strain_name", "value", "se_error", "nstrain", "id"], row))
+ ["sample_name", "value", "se_error", "nstrain", "id"], row))
for row in cursor.fetchall()]
return []
@@ -545,7 +548,7 @@ def retrieve_cellid_trait_data(trait_info: Dict, conn: Any):
"trait_name": trait_info["trait_name"],
"dataset_id": trait_info["db"]["dataset_id"]})
return [dict(zip(
- ["strain_name", "value", "se_error", "id"], row))
+ ["sample_name", "value", "se_error", "id"], row))
for row in cursor.fetchall()]
return []
@@ -574,29 +577,29 @@ def retrieve_probeset_trait_data(trait_info: Dict, conn: Any):
{"trait_name": trait_info["trait_name"],
"dataset_name": trait_info["db"]["dataset_name"]})
return [dict(zip(
- ["strain_name", "value", "se_error", "id"], row))
+ ["sample_name", "value", "se_error", "id"], row))
for row in cursor.fetchall()]
return []
-def with_strainlist_data_setup(strainlist: Sequence[str]):
+def with_samplelist_data_setup(samplelist: Sequence[str]):
"""
- Build function that computes the trait data from provided list of strains.
+ Build function that computes the trait data from provided list of samples.
PARAMETERS
- strainlist: (list)
- A list of strain names
+ samplelist: (list)
+ A list of sample names
RETURNS:
Returns a function that given some data from the database, computes the
- strain's value, variance and ndata values, only if the strain is present
- in the provided `strainlist` variable.
+ sample's value, variance and ndata values, only if the sample is present
+ in the provided `samplelist` variable.
"""
def setup_fn(tdata):
- if tdata["strain_name"] in strainlist:
+ if tdata["sample_name"] in samplelist:
val = tdata["value"]
if val is not None:
return {
- "strain_name": tdata["strain_name"],
+ "sample_name": tdata["sample_name"],
"value": val,
"variance": tdata["se_error"],
"ndata": tdata.get("nstrain", None)
@@ -604,19 +607,19 @@ def with_strainlist_data_setup(strainlist: Sequence[str]):
return None
return setup_fn
-def without_strainlist_data_setup():
+def without_samplelist_data_setup():
"""
Build function that computes the trait data.
RETURNS:
Returns a function that given some data from the database, computes the
- strain's value, variance and ndata values.
+ sample's value, variance and ndata values.
"""
def setup_fn(tdata):
val = tdata["value"]
if val is not None:
return {
- "strain_name": tdata["strain_name"],
+ "sample_name": tdata["sample_name"],
"value": val,
"variance": tdata["se_error"],
"ndata": tdata.get("nstrain", None)
@@ -624,7 +627,7 @@ def without_strainlist_data_setup():
return None
return setup_fn
-def retrieve_trait_data(trait: dict, conn: Any, strainlist: Sequence[str] = tuple()):
+def retrieve_trait_data(trait: dict, conn: Any, samplelist: Sequence[str] = tuple()):
"""
Retrieve trait data
@@ -647,22 +650,27 @@ def retrieve_trait_data(trait: dict, conn: Any, strainlist: Sequence[str] = tupl
if results:
# do something with mysqlid
mysqlid = results[0]["id"]
- if strainlist:
+ if samplelist:
data = [
item for item in
- map(with_strainlist_data_setup(strainlist), results)
+ map(with_samplelist_data_setup(samplelist), results)
if item is not None]
else:
data = [
item for item in
- map(without_strainlist_data_setup(), results)
+ map(without_samplelist_data_setup(), results)
if item is not None]
return {
"mysqlid": mysqlid,
"data": dict(map(
lambda x: (
- x["strain_name"],
- {k:v for k, v in x.items() if x != "strain_name"}),
+ x["sample_name"],
+ {k:v for k, v in x.items() if x != "sample_name"}),
data))}
return {}
+
+def generate_traits_filename(base_path: str = TMPDIR):
+ """Generate a unique filename for use with generated traits files."""
+ return "{}/traits_test_file_{}.txt".format(
+ os.path.abspath(base_path), random_string(10))
diff --git a/gn3/heatmaps.py b/gn3/heatmaps.py
new file mode 100644
index 0000000..a36940d
--- /dev/null
+++ b/gn3/heatmaps.py
@@ -0,0 +1,395 @@
+"""
+This module will contain functions to be used in computation of the data used to
+generate various kinds of heatmaps.
+"""
+
+from functools import reduce
+from typing import Any, Dict, Sequence
+
+import numpy as np
+import plotly.graph_objects as go # type: ignore
+import plotly.figure_factory as ff # type: ignore
+from plotly.subplots import make_subplots # type: ignore
+
+from gn3.settings import TMPDIR
+from gn3.random import random_string
+from gn3.computations.slink import slink
+from gn3.computations.correlations2 import compute_correlation
+from gn3.db.genotypes import (
+ build_genotype_file, load_genotype_samples)
+from gn3.db.traits import (
+ retrieve_trait_data, retrieve_trait_info)
+from gn3.computations.qtlreaper import (
+ run_reaper,
+ generate_traits_file,
+ chromosome_sorter_key_fn,
+ parse_reaper_main_results,
+ organise_reaper_main_results)
+
+def export_trait_data(
+ trait_data: dict, samplelist: Sequence[str], dtype: str = "val",
+ var_exists: bool = False, n_exists: bool = False):
+ """
+ Export data according to `samplelist`. Mostly used in calculating
+ correlations.
+
+ DESCRIPTION:
+ Migrated from
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L166-L211
+
+ PARAMETERS
+ trait: (dict)
+ The dictionary of key-value pairs representing a trait
+ samplelist: (list)
+ A list of sample names
+ dtype: (str)
+ ... verify what this is ...
+ var_exists: (bool)
+ A flag indicating existence of variance
+ n_exists: (bool)
+ A flag indicating existence of ndata
+ """
+ def __export_all_types(tdata, sample):
+ sample_data = []
+ if tdata[sample]["value"]:
+ sample_data.append(tdata[sample]["value"])
+ if var_exists:
+ if tdata[sample]["variance"]:
+ sample_data.append(tdata[sample]["variance"])
+ else:
+ sample_data.append(None)
+ if n_exists:
+ if tdata[sample]["ndata"]:
+ sample_data.append(tdata[sample]["ndata"])
+ else:
+ sample_data.append(None)
+ else:
+ if var_exists and n_exists:
+ sample_data += [None, None, None]
+ elif var_exists or n_exists:
+ sample_data += [None, None]
+ else:
+ sample_data.append(None)
+
+ return tuple(sample_data)
+
+ def __exporter(accumulator, sample):
+ # pylint: disable=[R0911]
+ if sample in trait_data["data"]:
+ if dtype == "val":
+ return accumulator + (trait_data["data"][sample]["value"], )
+ if dtype == "var":
+ return accumulator + (trait_data["data"][sample]["variance"], )
+ if dtype == "N":
+ return accumulator + (trait_data["data"][sample]["ndata"], )
+ if dtype == "all":
+ return accumulator + __export_all_types(trait_data["data"], sample)
+ raise KeyError("Type `%s` is incorrect" % dtype)
+ if var_exists and n_exists:
+ return accumulator + (None, None, None)
+ if var_exists or n_exists:
+ return accumulator + (None, None)
+ return accumulator + (None,)
+
+ return reduce(__exporter, samplelist, tuple())
+
+def trait_display_name(trait: Dict):
+ """
+ Given a trait, return a name to use to display the trait on a heatmap.
+
+ DESCRIPTION
+ Migrated from
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/base/webqtlTrait.py#L141-L157
+ """
+ if trait.get("db", None) and trait.get("trait_name", None):
+ if trait["db"]["dataset_type"] == "Temp":
+ desc = trait["description"]
+ if desc.find("PCA") >= 0:
+ return "%s::%s" % (
+ trait["db"]["displayname"],
+ desc[desc.rindex(':')+1:].strip())
+ return "%s::%s" % (
+ trait["db"]["displayname"],
+ desc[:desc.index('entered')].strip())
+ prefix = "%s::%s" % (
+ trait["db"]["dataset_name"], trait["trait_name"])
+ if trait["cellid"]:
+ return "%s::%s" % (prefix, trait["cellid"])
+ return prefix
+ return trait["description"]
+
+def cluster_traits(traits_data_list: Sequence[Dict]):
+ """
+ Clusters the trait values.
+
+ DESCRIPTION
+ Attempts to replicate the clustering of the traits, as done at
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L138-L162
+ """
+ def __compute_corr(tdata_i, tdata_j):
+ if tdata_i[0] == tdata_j[0]:
+ return 0.0
+ corr_vals = compute_correlation(tdata_i[1], tdata_j[1])
+ corr = corr_vals[0]
+ if (1 - corr) < 0:
+ return 0.0
+ return 1 - corr
+
+ def __cluster(tdata_i):
+ return tuple(
+ __compute_corr(tdata_i, tdata_j)
+ for tdata_j in enumerate(traits_data_list))
+
+ return tuple(__cluster(tdata_i) for tdata_i in enumerate(traits_data_list))
+
+def build_heatmap(traits_names, conn: Any):
+ """
+ heatmap function
+
+ DESCRIPTION
+ This function is an attempt to reproduce the initialisation at
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L46-L64
+ and also the clustering and slink computations at
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L138-L165
+ with the help of the `gn3.computations.heatmap.cluster_traits` function.
+
+ It does not try to actually draw the heatmap image.
+
+ PARAMETERS:
+ TODO: Elaborate on the parameters here...
+ """
+ # pylint: disable=[R0914]
+ threshold = 0 # webqtlConfig.PUBLICTHRESH
+ traits = [
+ retrieve_trait_info(threshold, fullname, conn)
+ for fullname in traits_names]
+ traits_data_list = [retrieve_trait_data(t, conn) for t in traits]
+ genotype_filename = build_genotype_file(traits[0]["group"])
+ samples = load_genotype_samples(genotype_filename)
+ exported_traits_data_list = [
+ export_trait_data(td, samples) for td in traits_data_list]
+ clustered = cluster_traits(exported_traits_data_list)
+ slinked = slink(clustered)
+ traits_order = compute_traits_order(slinked)
+ samples_and_values = retrieve_samples_and_values(
+ traits_order, samples, exported_traits_data_list)
+ traits_filename = "{}/traits_test_file_{}.txt".format(
+ TMPDIR, random_string(10))
+ generate_traits_file(
+ samples_and_values[0][1],
+ [t[2] for t in samples_and_values],
+ traits_filename)
+
+ main_output, _permutations_output = run_reaper(
+ genotype_filename, traits_filename, separate_nperm_output=True)
+
+ qtlresults = parse_reaper_main_results(main_output)
+ organised = organise_reaper_main_results(qtlresults)
+
+ traits_ids = [# sort numerically, but retain the ids as strings
+ str(i) for i in sorted({int(row["ID"]) for row in qtlresults})]
+ chromosome_names = sorted(
+ {row["Chr"] for row in qtlresults}, key=chromosome_sorter_key_fn)
+ ordered_traits_names = dict(
+ zip(traits_ids,
+ [traits[idx]["trait_fullname"] for idx in traits_order]))
+
+ return generate_clustered_heatmap(
+ process_traits_data_for_heatmap(
+ organised, traits_ids, chromosome_names),
+ clustered,
+ "single_heatmap_{}".format(random_string(10)),
+ y_axis=tuple(
+ ordered_traits_names[traits_ids[order]]
+ for order in traits_order),
+ y_label="Traits",
+ x_axis=chromosome_names,
+ x_label="Chromosomes")
+
+def compute_traits_order(slink_data, neworder: tuple = tuple()):
+ """
+ Compute the order of the traits for clustering from `slink_data`.
+
+ This function tries to reproduce the creation and update of the `neworder`
+ variable in
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L120
+ and in the `web.webqtl.heatmap.Heatmap.draw` function in GN1
+ """
+ def __order_maker(norder, slnk_dt):
+ if isinstance(slnk_dt[0], int) and isinstance(slnk_dt[1], int):
+ return norder + (slnk_dt[0], slnk_dt[1])
+
+ if isinstance(slnk_dt[0], int):
+ return __order_maker((norder + (slnk_dt[0], )), slnk_dt[1])
+
+ if isinstance(slnk_dt[1], int):
+ return __order_maker(norder, slnk_dt[0]) + (slnk_dt[1], )
+
+ return __order_maker(__order_maker(norder, slnk_dt[0]), slnk_dt[1])
+
+ return __order_maker(neworder, slink_data)
+
+def retrieve_samples_and_values(orders, samplelist, traits_data_list):
+ """
+ Get the samples and their corresponding values from `samplelist` and
+ `traits_data_list`.
+
+ This migrates the code in
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L215-221
+ """
+ # This feels nasty! There's a lot of mutation of values here, that might
+ # indicate something untoward in the design of this function and its
+ # dependents ==> Review
+ samples = []
+ values = []
+ rets = []
+ for order in orders:
+ temp_val = traits_data_list[order]
+ for i, sample in enumerate(samplelist):
+ if temp_val[i] is not None:
+ samples.append(sample)
+ values.append(temp_val[i])
+ rets.append([order, samples[:], values[:]])
+ samples = []
+ values = []
+
+ return rets
+
+def nearest_marker_finder(genotype):
+ """
+ Returns a function to be used with `genotype` to compute the nearest marker
+ to the trait passed to the returned function.
+
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L425-434
+ """
+ def __compute_distances(chromo, trait):
+ loci = chromo.get("loci", None)
+ if not loci:
+ return None
+ return tuple(
+ {
+ "name": locus["name"],
+ "distance": abs(locus["Mb"] - trait["mb"])
+ } for locus in loci)
+
+ def __finder(trait):
+ _chrs = tuple(
+ _chr for _chr in genotype["chromosomes"]
+ if str(_chr["name"]) == str(trait["chr"]))
+ if len(_chrs) == 0:
+ return None
+ distances = tuple(
+ distance for dists in
+ filter(
+ lambda x: x is not None,
+ (__compute_distances(_chr, trait) for _chr in _chrs))
+ for distance in dists)
+ nearest = min(distances, key=lambda d: d["distance"])
+ return nearest["name"]
+ return __finder
+
+def get_nearest_marker(traits_list, genotype):
+ """
+ Retrieves the nearest marker for each of the traits in the list.
+
+ DESCRIPTION:
+ This migrates the code in
+ https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/Heatmap.py#L419-L438
+ """
+ if not genotype["Mbmap"]:
+ return [None] * len(traits_list)
+
+ marker_finder = nearest_marker_finder(genotype)
+ return [marker_finder(trait) for trait in traits_list]
+
+def get_lrs_from_chr(trait, chr_name):
+ """
+ Retrieve the LRS values for a specific chromosome in the given trait.
+ """
+ chromosome = trait["chromosomes"].get(chr_name)
+ if chromosome:
+ return [
+ locus["LRS"] for locus in
+ sorted(chromosome["loci"], key=lambda loc: loc["Locus"])]
+ return [None]
+
+def process_traits_data_for_heatmap(data, trait_names, chromosome_names):
+ """
+ Process the traits data in a format useful for generating heatmap diagrams.
+ """
+ hdata = [
+ [get_lrs_from_chr(data[trait], chr_name) for trait in trait_names]
+ for chr_name in chromosome_names]
+ return hdata
+
+def generate_clustered_heatmap(
+ data, clustering_data, image_filename_prefix, x_axis=None,
+ x_label: str = "", y_axis=None, y_label: str = "",
+ output_dir: str = TMPDIR,
+ colorscale=(
+ (0.0, '#5D5D5D'), (0.4999999999999999, '#ABABAB'),
+ (0.5, '#F5DE11'), (1.0, '#FF0D00'))):
+ """
+ Generate a dendrogram, and heatmaps for each chromosome, and put them all
+ into one plot.
+ """
+ # pylint: disable=[R0913, R0914]
+ num_cols = 1 + len(x_axis)
+ fig = make_subplots(
+ rows=1,
+ cols=num_cols,
+ shared_yaxes="rows",
+ horizontal_spacing=0.001,
+ subplot_titles=["distance"] + x_axis,
+ figure=ff.create_dendrogram(
+ np.array(clustering_data), orientation="right", labels=y_axis))
+ hms = [go.Heatmap(
+ name=chromo,
+ y=y_axis,
+ z=data_array,
+ showscale=False) for chromo, data_array in zip(x_axis, data)]
+ for i, heatmap in enumerate(hms):
+ fig.add_trace(heatmap, row=1, col=(i + 2))
+
+ fig.update_layout(
+ {
+ "width": 1500,
+ "height": 800,
+ "xaxis": {
+ "mirror": False,
+ "showgrid": True,
+ "title": x_label
+ },
+ "yaxis": {
+ "title": y_label
+ }
+ })
+
+ x_axes_layouts = {
+ "xaxis{}".format(i+1 if i > 0 else ""): {
+ "mirror": False,
+ "showticklabels": i == 0,
+ "ticks": "outside" if i == 0 else ""
+ }
+ for i in range(num_cols)}
+
+ fig.update_layout(
+ {
+ "width": 4000,
+ "height": 800,
+ "yaxis": {
+ "mirror": False,
+ "ticks": ""
+ },
+ **x_axes_layouts})
+ fig.update_traces(
+ showlegend=False,
+ colorscale=colorscale,
+ selector={"type": "heatmap"})
+ fig.update_traces(
+ showlegend=True,
+ showscale=True,
+ selector={"name": x_axis[-1]})
+ image_filename = "{}/{}.html".format(output_dir, image_filename_prefix)
+ fig.write_html(image_filename)
+ return image_filename, fig
diff --git a/gn3/heatmaps/heatmaps.py b/gn3/heatmaps/heatmaps.py
deleted file mode 100644
index 3bf7917..0000000
--- a/gn3/heatmaps/heatmaps.py
+++ /dev/null
@@ -1,54 +0,0 @@
-import random
-import plotly.express as px
-
-#### Remove these ####
-
-heatmap_dir = "heatmap_images"
-
-def generate_random_data(data_stop: float = 2, width: int = 10, height: int = 30):
- """
- This is mostly a utility function to be used to generate random data, useful
- for development of the heatmap generation code, without access to the actual
- database data.
- """
- return [[random.uniform(0,data_stop) for i in range(0, width)]
- for j in range(0, height)]
-
-def heatmap_x_axis_names():
- return [
- "UCLA_BXDBXH_CARTILAGE_V2::ILM103710672",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM2260338",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM3140576",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM5670577",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM2070121",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM103990541",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM1190722",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM6590722",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM4200064",
- "UCLA_BXDBXH_CARTILAGE_V2::ILM3140463"]
-#### END: Remove these ####
-
-# Grey + Blue + Red
-def generate_heatmap():
- rows = 20
- data = generate_random_data(height=rows)
- y = (["%s"%x for x in range(1, rows+1)][:-1] + ["X"]) #replace last item with x for now
- fig = px.imshow(
- data,
- x=heatmap_x_axis_names(),
- y=y,
- width=500)
- fig.update_traces(xtype="array")
- fig.update_traces(ytype="array")
- # fig.update_traces(xgap=10)
- fig.update_xaxes(
- visible=True,
- title_text="Traits",
- title_font_size=16)
- fig.update_layout(
- coloraxis_colorscale=[
- [0.0, '#3B3B3B'], [0.4999999999999999, '#ABABAB'],
- [0.5, '#F5DE11'], [1.0, '#FF0D00']])
-
- fig.write_html("%s/%s"%(heatmap_dir, "test_image.html"))
- return fig
diff --git a/gn3/random.py b/gn3/random.py
new file mode 100644
index 0000000..f0ba574
--- /dev/null
+++ b/gn3/random.py
@@ -0,0 +1,11 @@
+"""
+Functions to generate complex random data.
+"""
+import random
+import string
+
+def random_string(length):
+ """Generate a random string of length `length`."""
+ return "".join(
+ random.choices(
+ string.ascii_letters + string.digits, k=length))
diff --git a/gn3/settings.py b/gn3/settings.py
index f4866d5..9d7bba3 100644
--- a/gn3/settings.py
+++ b/gn3/settings.py
@@ -24,3 +24,22 @@ GN2_BASE_URL = "http://www.genenetwork.org/"
# biweight script
BIWEIGHT_RSCRIPT = "~/genenetwork3/scripts/calculate_biweight.R"
+
+# qtlreaper command
+REAPER_COMMAND = "{}/bin/qtlreaper".format(os.environ.get("GUIX_ENVIRONMENT"))
+
+# genotype files
+GENOTYPE_FILES = os.environ.get(
+ "GENOTYPE_FILES", "{}/genotype_files/genotype".format(os.environ.get("HOME")))
+
+# CROSS-ORIGIN SETUP
+CORS_ORIGINS = [
+ "http://localhost:*",
+ "http://127.0.0.1:*"
+]
+
+CORS_HEADERS = [
+ "Content-Type",
+ "Authorization",
+ "Access-Control-Allow-Credentials"
+]
generated by cgit v1.2.3 (git 2.44.0) at 2024-11-24 13:23:43 +0000