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-rw-r--r--gn3/computations/rqtl.py103
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+"""Procedures related rqtl computations"""
+import os
+from typing import Dict, List, Union
+
+import numpy as np
+
+from flask import current_app
+
+from gn3.commands import compose_rqtl_cmd
+from gn3.computations.gemma import generate_hash_of_string
+from gn3.fs_helpers import get_hash_of_files
+
+def generate_rqtl_cmd(rqtl_wrapper_cmd: str,
+ rqtl_wrapper_kwargs: Dict,
+ rqtl_wrapper_bool_kwargs: list) -> Dict:
+ """Given the base rqtl_wrapper command and
+dict of keyword arguments, return the full rqtl_wrapper command and an
+output filename generated from a hash of the genotype and phenotype files
+
+ """
+
+ # Generate a hash from contents of the genotype and phenotype files
+ _hash = get_hash_of_files(
+ [v for k, v in rqtl_wrapper_kwargs.items() if k in ["g", "p"]])
+
+ # Append to hash a hash of keyword arguments
+ _hash += generate_hash_of_string(
+ ",".join([f"{k}:{v}" for k, v in rqtl_wrapper_kwargs.items() if k not in ["g", "p"]]))
+
+ # Append to hash a hash of boolean keyword arguments
+ _hash += generate_hash_of_string(
+ ",".join(rqtl_wrapper_bool_kwargs))
+
+ # Temporarily substitute forward-slashes in hash with underscores
+ _hash = _hash.replace("/", "_")
+
+ _output_filename = f"{_hash}-output.csv"
+ rqtl_wrapper_kwargs["filename"] = _output_filename
+
+ return {
+ "output_file":
+ _output_filename,
+ "rqtl_cmd":
+ compose_rqtl_cmd(rqtl_wrapper_cmd=rqtl_wrapper_cmd,
+ rqtl_wrapper_kwargs=rqtl_wrapper_kwargs,
+ rqtl_wrapper_bool_kwargs=rqtl_wrapper_bool_kwargs)
+ }
+
+
+def process_rqtl_output(file_name: str) -> List:
+ """Given an output file name, read in R/qtl results and return
+ a List of marker objects
+
+ """
+ marker_obs = []
+ # Later I should probably redo this using csv.read to avoid the
+ # awkwardness with removing quotes with [1:-1]
+ with open(os.path.join(current_app.config.get("TMPDIR", "/tmp"),
+ "output", file_name), "r") as the_file:
+ for line in the_file:
+ line_items = line.split(",")
+ if line_items[1][1:-1] == "chr" or not line_items:
+ # Skip header line
+ continue
+
+ # Convert chr to int if possible
+ the_chr: Union[int, str]
+ try:
+ the_chr = int(line_items[1][1:-1])
+ except ValueError:
+ the_chr = line_items[1][1:-1]
+ this_marker = {
+ "name": line_items[0][1:-1],
+ "chr": the_chr,
+ "cM": float(line_items[2]),
+ "Mb": float(line_items[2]),
+ "lod_score": float(line_items[3])
+ }
+ marker_obs.append(this_marker)
+
+ return marker_obs
+
+
+def process_perm_output(file_name: str):
+ """Given base filename, read in R/qtl permutation output and calculate
+ suggestive and significant thresholds
+
+ """
+ perm_results = []
+ with open(os.path.join(current_app.config.get("TMPDIR", "/tmp"),
+ "output", "PERM_" + file_name), "r") as the_file:
+ for i, line in enumerate(the_file):
+ if i == 0:
+ # Skip header line
+ continue
+
+ line_items = line.split(",")
+ perm_results.append(float(line_items[1]))
+
+ suggestive = np.percentile(np.array(perm_results), 67)
+ significant = np.percentile(np.array(perm_results), 95)
+
+ return perm_results, suggestive, significant