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diff --git a/gn3/computations/partial_correlations.py b/gn3/computations/partial_correlations.py
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+"""
+This module deals with partial correlations.
+
+It is an attempt to migrate over the partial correlations feature from
+GeneNetwork1.
+"""
+
+from functools import reduce
+from typing import Any, Tuple, Sequence
+
+def control_samples(controls: Sequence[dict], sampleslist: Sequence[str]):
+    """
+    Fetches data for the control traits.
+
+    This migrates `web/webqtl/correlation/correlationFunction.controlStrain` in
+    GN1, with a few modifications to the arguments passed in.
+
+    PARAMETERS:
+    controls: A map of sample names to trait data. Equivalent to the `cvals`
+        value in the corresponding source function in GN1.
+    sampleslist: A list of samples. Equivalent to `strainlst` in the
+        corresponding source function in GN1
+    """
+    def __process_control__(trait_data):
+        def __process_sample__(acc, sample):
+            if sample in trait_data["data"].keys():
+                sample_item = trait_data["data"][sample]
+                val = sample_item["value"]
+                if val is not None:
+                    return (
+                        acc[0] + (sample,),
+                        acc[1] + (val,),
+                        acc[2] + (sample_item["variance"],))
+            return acc
+        return reduce(
+            __process_sample__, sampleslist, (tuple(), tuple(), tuple()))
+
+    return reduce(
+        lambda acc, item: (
+            acc[0] + (item[0],),
+            acc[1] + (item[1],),
+            acc[2] + (item[2],),
+            acc[3] + (len(item[0]),),
+        ),
+        [__process_control__(trait_data) for trait_data in controls],
+        (tuple(), tuple(), tuple(), tuple()))
+
+def dictify_by_samples(samples_vals_vars: Sequence[Sequence]) -> Sequence[dict]:
+    """
+    Build a sequence of dictionaries from a sequence of separate sequences of
+    samples, values and variances.
+
+    This is a partial migration of
+    `web.webqtl.correlation.correlationFunction.fixStrains` function in GN1.
+    This implementation extracts code that will find common use, and that will
+    find use in more than one place.
+    """
+    return tuple(
+        {
+            sample: {"sample_name": sample, "value": val, "variance": var}
+            for sample, val, var in zip(*trait_line)
+        } for trait_line in zip(*(samples_vals_vars[0:3])))
+
+def fix_samples(primary_trait: dict, control_traits: Sequence[dict]) -> Sequence[Sequence[Any]]:
+    """
+    Corrects sample_names, values and variance such that they all contain only
+    those samples that are common to the reference trait and all control traits.
+
+    This is a partial migration of the
+    `web.webqtl.correlation.correlationFunction.fixStrain` function in GN1.
+    """
+    primary_samples = tuple(
+        present[0] for present in
+        ((sample, all(sample in control.keys() for control in control_traits))
+         for sample in primary_trait.keys())
+        if present[1])
+    control_vals_vars: tuple = reduce(
+        lambda acc, x: (acc[0] + (x[0],), acc[1] + (x[1],)),
+        ((item["value"], item["variance"])
+         for sublist in [tuple(control.values()) for control in control_traits]
+         for item in sublist),
+        (tuple(), tuple()))
+    return (
+        primary_samples,
+        tuple(primary_trait[sample]["value"] for sample in primary_samples),
+        control_vals_vars[0],
+        tuple(primary_trait[sample]["variance"] for sample in primary_samples),
+        control_vals_vars[1])
+
+def find_identical_traits(
+        primary_name: str, primary_value: float, control_names: Tuple[str, ...],
+        control_values: Tuple[float, ...]) -> Tuple[str, ...]:
+    """
+    Find traits that have the same value when the values are considered to
+    3 decimal places.
+
+    This is a migration of the
+    `web.webqtl.correlation.correlationFunction.findIdenticalTraits` function in
+    GN1.
+    """
+    def __merge_identicals__(
+            acc: Tuple[str, ...],
+            ident: Tuple[str, Tuple[str, ...]]) -> Tuple[str, ...]:
+        return acc + ident[1]
+
+    def __dictify_controls__(acc, control_item):
+        ckey = "{:.3f}".format(control_item[0])
+        return {**acc, ckey: acc.get(ckey, tuple()) + (control_item[1],)}
+
+    return (reduce(## for identical control traits
+        __merge_identicals__,
+        (item for item in reduce(# type: ignore[var-annotated]
+            __dictify_controls__, zip(control_values, control_names),
+            {}).items() if len(item[1]) > 1),
+        tuple())
+            or
+            reduce(## If no identical control traits, try primary and controls
+                __merge_identicals__,
+                (item for item in reduce(# type: ignore[var-annotated]
+                    __dictify_controls__,
+                    zip((primary_value,) + control_values,
+                        (primary_name,) + control_names), {}).items()
+                 if len(item[1]) > 1),
+                tuple()))