Merge pull request #37 from genenetwork/heatmap_generation

Heatmap generation

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"
+]