hfp_bettercallsal_awsbatch: 1.0.0/bin/gen_salmon_res

comparison 1.0.0/bin/gen_salmon_res_table.py @ 0:801b85b03a17 draft default tip

planemo upload

author	galaxytrakr
date	Thu, 28 May 2026 20:31:42 +0000
parents
children

comparison

equal deleted inserted replaced

--1:000000000000
+:801b85b03a17
+#!/usr/bin/env python3
+# Kranti Konganti
+import argparse
+import glob
+import inspect
+import json
+import logging
+import os
+import pickle
+import pprint
+import re
+from collections import defaultdict
+import yaml
+# Multiple inheritence for pretty printing of help text.
+class MultiArgFormatClasses(argparse.RawTextHelpFormatter, argparse.ArgumentDefaultsHelpFormatter):
+pass
+# Main
+def main() -> None:
+"""
+The succesful execution of this script requires access to bettercallsal formatted
+db flat files. On raven2, they are at /hpc/db/bettercallsall/PDGXXXXXXXXXX.XXXXX
+It takes the ACC2SERO.pickle file and *.reference_target.cluster_list.tsv file
+for that particular NCBI Pathogens release from the db directory mentioned with
+-db option and a root parent directory of the `salmon quant` results mentioned
+with -sal option and generates a final results table with number of reads
+mapped and a .json file to be used with MultiQC to generate a stacked bar plot.
+Using -url option optionally adds an extra column of NCBI Pathogens Isolates
+Browser, which directly links out to NCBI Pathogens Isolates SNP viewer tool.
+"""
+# Set logging.
+logging.basicConfig(
+format="\n" + "=" * 55 + "\n%(asctime)s - %(levelname)s\n" + "=" * 55 + "\n%(message)s\n\n",
+level=logging.DEBUG,
+)
+# Debug print.
+ppp = pprint.PrettyPrinter(width=55)
+prog_name = inspect.stack()[0].filename
+parser = argparse.ArgumentParser(
+prog=prog_name, description=main.__doc__, formatter_class=MultiArgFormatClasses
+)
+required = parser.add_argument_group("required arguments")
+required.add_argument(
+"-sal",
+dest="salmon_res_dir",
+default=False,
+required=True,
+help="Absolute UNIX path to the parent directory that contains the\n"
++ "`salmon quant` results directory. For example, if path to\n"
++ "`quant.sf` is in /hpc/john_doe/test/salmon_res/quant.sf, then\n"
++ "use this command-line option as:\n"
++ "-sal /hpc/john_doe/test",
+)
+required.add_argument(
+"-snp",
+dest="rtc",
+default=False,
+required=True,
+help="Absolute UNIX Path to the PDG SNP reference target cluster\n"
++ "metadata file. On raven2, these are located at\n"
++ "/hpc/db/bettercallsal/PDGXXXXXXXXXX.XXXXX\n"
++ "Required if -sal is on.",
+)
+required.add_argument(
+"-pickle",
+dest="acc2sero",
+default=False,
+required=True,
+help="Absolute UNIX Path to the *ACC2SERO.pickle\n"
++ "metadata file. On raven2, these are located at\n"
++ "/hpc/db/bettercallsal/PDGXXXXXXXXXX.XXXXX\n"
++ "Required if -sal is on.",
+)
+parser.add_argument(
+"-op",
+dest="out_prefix",
+default="bettercallsal.tblsum",
+required=False,
+help="Set the output file(s) prefix for output(s) generated\n" + "by this program.",
+)
+parser.add_argument(
+"-url",
+dest="show_snp_clust_info",
+default=False,
+required=False,
+action="store_true",
+help="Show SNP cluster participation information of the final genome hit.\n"
++ "This may be useful to see a relative placement of your sample in\n"
++ "NCBI Isolates SNP Tree Viewer based on genome similarity but however\n"
++ "due to rapid nature of the updates at NCBI Pathogen Detection Project,\n"
++ "the placement may be in an outdated cluster.",
+)
+args = parser.parse_args()
+salmon_res_dir = args.salmon_res_dir
+out_prefix = args.out_prefix
+show_snp_clust_col = args.show_snp_clust_info
+rtc = args.rtc
+pickled_sero = args.acc2sero
+no_hit = "No genome hit"
+no_presence = "Salmonella presence not detected"
+bcs_sal_yn_prefix = "bettercallsal_salyn"
+sal_y = "Detected"
+sal_n = "Not detected"
+null_value = "NULL"
+assm_pat = re.compile(r"GC[AF]\_[0-9]+\.*[0-9]*")
+ncbi_pathogens_base_url = "https://www.ncbi.nlm.nih.gov/pathogens/"
+ncbi_pathogens_genome_base = "https://www.ncbi.nlm.nih.gov/datasets/genome/"
+sample2salmon, snp_clusters, multiqc_salmon_counts, seen_sero, sal_yn = (
+defaultdict(defaultdict),
+defaultdict(defaultdict),
+defaultdict(defaultdict),
+defaultdict(int),
+defaultdict(int),
+)
+cell_colors_yml = {
+bcs_sal_yn_prefix: {sal_y: "#c8e6c9 !important;", sal_n: "#ffcdd2 !important;"}
+}
+salmon_comb_res = os.path.join(os.getcwd(), out_prefix + ".txt")
+bcs_sal_yn = re.sub(out_prefix, bcs_sal_yn_prefix + ".tblsum", salmon_comb_res)
+cell_colors_yml_file = re.sub(
+out_prefix + ".txt", bcs_sal_yn_prefix + ".cellcolors.yml", salmon_comb_res
+)
+salmon_comb_res_mqc = os.path.join(os.getcwd(), str(out_prefix).split(".")[0] + "_mqc.json")
+salmon_res_files = glob.glob(os.path.join(salmon_res_dir, "*", "quant.sf"), recursive=True)
+salmon_res_file_failed = glob.glob(os.path.join(salmon_res_dir, "BCS_NO_CALLS.txt"))
+if rtc and (not os.path.exists(rtc) or not os.path.getsize(rtc) > 0):
+logging.error(
+"The reference target cluster metadata file,\n"
++ f"{os.path.basename(rtc)} does not exist or is empty!"
+)
+exit(1)
+if rtc and (not salmon_res_dir or not pickled_sero):
+logging.error("When -rtc is on, -sal and -ps are also required.")
+exit(1)
+if pickled_sero and (not os.path.exists(pickled_sero) or not os.path.getsize(pickled_sero)):
+logging.error(
+"The pickle file,\n" + f"{os.path.basename(pickled_sero)} does not exist or is empty!"
+)
+exit(1)
+if salmon_res_dir:
+if not os.path.isdir(salmon_res_dir):
+logging.error("UNIX path\n" + f"{salmon_res_dir}\n" + "does not exist!")
+exit(1)
+if len(salmon_res_files) <= 0:
+# logging.error(
+#     "Parent directory,\n"
+#     + f"{salmon_res_dir}"
+#     + "\ndoes not seem to have any directories that contain\n"
+#     + "the `quant.sf` file(s)."
+# )
+# exit(1)
+with open(salmon_comb_res, "w") as salmon_comb_res_fh:
+salmon_comb_res_fh.write(f"Sample\n{no_hit}s in any samples\n")
+salmon_comb_res_fh.close()
+with open(bcs_sal_yn, "w") as bcs_sal_yn_fh:
+bcs_sal_yn_fh.write(f"Sample\n{no_presence} in any samples\n")
+bcs_sal_yn_fh.close()
+exit(0)
+if rtc and os.path.exists(rtc) and os.path.getsize(rtc) > 0:
+# pdg_release = re.match(r"(^PDG\d+\.\d+)\..+", os.path.basename(rtc))[1] + "/"
+acc2sero = pickle.load(file=open(pickled_sero, "rb"))
+with open(rtc, "r") as rtc_fh:
+for line in rtc_fh:
+cols = line.strip().split("\t")
+if len(cols) < 4:
+logging.error(
+f"The file {os.path.basename(rtc)} seems to\n"
++ "be malformed. It contains less than required 4 columns."
+)
+exit(1)
+elif cols[3] != null_value:
+snp_clusters[cols[0]].setdefault("assembly_accs", []).append(cols[3])
+snp_clusters[cols[3]].setdefault("snp_clust_id", []).append(cols[0])
+snp_clusters[cols[3]].setdefault("pathdb_acc_id", []).append(cols[1])
+if len(snp_clusters[cols[3]]["snp_clust_id"]) > 1:
+logging.error(
+f"There is a duplicate reference accession [{cols[3]}]"
++ f"in the metadata file{os.path.basename(rtc)}!"
+)
+exit(1)
+rtc_fh.close()
+for salmon_res_file in salmon_res_files:
+sample_name = re.match(
+r"(^.+?)((\_salmon\_res)|(\.salmon))$",
+os.path.basename(os.path.dirname(salmon_res_file)),
+)[1]
+salmon_meta_json = os.path.join(
+os.path.dirname(salmon_res_file), "aux_info", "meta_info.json"
+)
+if not os.path.exists(salmon_meta_json) or not os.path.getsize(salmon_meta_json) > 0:
+logging.error(
+"The file\n"
++ f"{salmon_meta_json}\ndoes not exist or is empty!\n"
++ "Did `salmon quant` fail?"
+)
+exit(1)
+if not os.path.exists(salmon_res_file) or not os.path.getsize(salmon_res_file):
+logging.error(
+"The file\n"
++ f"{salmon_res_file}\ndoes not exist or is empty!\n"
++ "Did `salmon quant` fail?"
+)
+exit(1)
+with open(salmon_res_file, "r") as salmon_res_fh:
+for line in salmon_res_fh.readlines():
+if re.match(r"^Name.+", line):
+continue
+cols = line.strip().split("\t")
+ref_acc = "_".join(cols[0].split("_")[:2])
+if ref_acc not in snp_clusters.keys():
+snp_clusters[ref_acc]["snp_clust_id"] = ref_acc
+snp_clusters[ref_acc]["pathdb_acc_id"] = ref_acc
+(
+sample2salmon[sample_name]
+.setdefault(acc2sero[cols[0]], [])
+.append(int(round(float(cols[4]), 2)))
+)
+(
+sample2salmon[sample_name]
+.setdefault("snp_clust_ids", {})
+.setdefault("".join(snp_clusters[ref_acc]["snp_clust_id"]), [])
+.append("".join(snp_clusters[ref_acc]["pathdb_acc_id"]))
+)
+seen_sero[acc2sero[cols[0]]] = 1
+salmon_meta_json_read = json.load(open(salmon_meta_json, "r"))
+(
+sample2salmon[sample_name]
+.setdefault("tot_reads", [])
+.append(salmon_meta_json_read["num_processed"])
+)
+with open(salmon_comb_res, "w") as salmon_comb_res_fh:
+# snp_clust_col_header = (
+#     "\tSNP Cluster(s) by Genome Hit\n" if show_snp_clust_col else "\n"
+# )
+snp_clust_col_header = (
+"\tNCBI Pathogens Isolate Browser\n" if show_snp_clust_col else "\n"
+)
+serotypes = sorted(seen_sero.keys())
+formatted_serotypes = [
+re.sub(r"\,antigen_formula=", " | ", s)
+for s in [re.sub(r"serotype=", "", s) for s in serotypes]
+]
+salmon_comb_res_fh.write(
+"Sample\t" + "\t".join(formatted_serotypes) + snp_clust_col_header
+)
+# sample_snp_relation = (
+#     ncbi_pathogens_base_url
+#     + pdg_release
+#     + "".join(snp_clusters[ref_acc]["snp_clust_id"])
+#     + "?accessions="
+# )
+if len(salmon_res_file_failed) == 1:
+with (open("".join(salmon_res_file_failed), "r")) as no_calls_fh:
+for line in no_calls_fh.readlines():
+if line in ["\n", "\n\r", "\r"]:
+continue
+salmon_comb_res_fh.write(line.strip())
+sal_yn[line.strip()] += 0
+for serotype in serotypes:
+salmon_comb_res_fh.write("\t-")
+salmon_comb_res_fh.write(
+"\t-\n"
+) if show_snp_clust_col else salmon_comb_res_fh.write("\n")
+no_calls_fh.close()
+for sample, counts in sorted(sample2salmon.items()):
+salmon_comb_res_fh.write(sample)
+snp_cluster_res_col = list()
+for snp_clust_id in sample2salmon[sample]["snp_clust_ids"].keys():
+# print(snp_clust_id)
+# print(",".join(sample2salmon[sample]["snp_clust_ids"][snp_clust_id]))
+# ppp.pprint(sample2salmon[sample]["snp_clust_ids"])
+# ppp.pprint(sample2salmon[sample]["snp_clust_ids"][snp_clust_id])
+# final_url_text = ",".join(
+#     sample2salmon[sample]["snp_clust_ids"][snp_clust_id]
+# )
+# final_url_text_to_show = snp_clust_id
+# snp_cluster_res_col.append(
+#     "".join(
+#         [
+#             f'<a href="',
+#             sample_snp_relation,
+#             ",".join(sample2salmon[sample]["snp_clust_ids"][snp_clust_id]),
+#             f'" target="_blank">{snp_clust_id}</a>',
+#         ]
+#     )
+# )
+# ppp.pprint(sample2salmon[sample])
+for pathdbacc in sample2salmon[sample]["snp_clust_ids"][snp_clust_id]:
+# final_url_text_to_show = " ".join(
+#     sample2salmon[sample]["snp_clust_ids"][snp_clust_id]
+# )
+sample_snp_relation = (
+ncbi_pathogens_genome_base
+if assm_pat.match(pathdbacc)
+else ncbi_pathogens_base_url + "isolates/#"
+)
+snp_cluster_res_col.append(
+"".join(
+[
+f'<a href="',
+sample_snp_relation,
+pathdbacc,
+f'" target="_blank">{pathdbacc}</a>',
+]
+)
+)
+per_serotype_counts = 0
+for serotype in serotypes:
+if serotype in sample2salmon[sample].keys():
+# ppp.pprint(counts)
+sample_perc_mapped = round(
+sum(counts[serotype]) / sum(counts["tot_reads"]) * 100, 2
+)
+salmon_comb_res_fh.write(
+f"\t{sum(counts[serotype])} ({sample_perc_mapped}%)"
+)
+multiqc_salmon_counts[sample].setdefault(
+re.match(r"^serotype=(.+?)\,antigen_formula.*", serotype)[1],
+sum(counts[serotype]),
+)
+per_serotype_counts += sum(counts[serotype])
+sal_yn[sample] += 1
+else:
+salmon_comb_res_fh.write(f"\t-")
+sal_yn[sample] += 0
+multiqc_salmon_counts[sample].setdefault(
+no_hit, sum(counts["tot_reads"]) - per_serotype_counts
+)
+snp_clust_col_val = (
+f'\t{" ".join(snp_cluster_res_col)}\n' if show_snp_clust_col else "\n"
+)
+# ppp.pprint(multiqc_salmon_counts)
+salmon_comb_res_fh.write(snp_clust_col_val)
+with open(bcs_sal_yn, "w") as bcs_sal_yn_fh:
+bcs_sal_yn_fh.write("Sample\tSalmonella Presence\tNo. of Serotypes\n")
+for sample in sal_yn.keys():
+if sal_yn[sample] > 0:
+bcs_sal_yn_fh.write(f"{sample}\tDetected\t{sal_yn[sample]}\n")
+else:
+bcs_sal_yn_fh.write(f"{sample}\tNot detected\t{sal_yn[sample]}\n")
+with open(cell_colors_yml_file, "w") as cell_colors_fh:
+yaml.dump(cell_colors_yml, cell_colors_fh, default_flow_style=False)
+salmon_plot_json(salmon_comb_res_mqc, multiqc_salmon_counts, no_hit)
+salmon_comb_res_fh.close()
+bcs_sal_yn_fh.close()
+cell_colors_fh.close()
+def salmon_plot_json(file: None, sample_salmon_counts: None, no_hit: None) -> None:
+"""
+This method will take a dictionary of salmon counts per sample
+and will dump a JSON that will be used by MultiQC.
+"""
+if file is None or sample_salmon_counts is None:
+logging.error(
+"Neither an output file to dump the JSON for MultiQC or the"
++ "dictionary holding the salmon counts was not passed."
+)
+# Credit: http://phrogz.net/tmp/24colors.html
+# Will cycle through 20 distinct colors.
+distinct_color_palette = [
+"#FF0000",
+"#FFFF00",
+"#00EAFF",
+"#AA00FF",
+"#FF7F00",
+"#BFFF00",
+"#0095FF",
+"#FF00AA",
+"#FFD400",
+"#6AFF00",
+"#0040FF",
+"#EDB9B9",
+"#B9D7ED",
+"#E7E9B9",
+"#DCB9ED",
+"#B9EDE0",
+"#8F2323",
+"#23628F",
+"#8F6A23",
+"#6B238F",
+"#4F8F23",
+]
+# Credit: https://mokole.com/palette.html
+# Will use this palette if we run out ouf
+# 20 serotypes. More than 50 serotypes
+# per run is probably rare but if not,
+# will cycle through about 45.
+distinct_color_palette2 = [
+"#2F4F4F",  # darkslategray
+"#556B2F",  # darkolivegreen
+"#A0522D",  # sienna
+"#2E8B57",  # seagreen
+"#006400",  # darkgreen
+"#8B0000",  # darkred
+"#808000",  # olive
+"#BC8F8F",  # rosybrown
+"#663399",  # rebeccapurple
+"#B8860B",  # darkgoldenrod
+"#4682B4",  # steelblue
+"#000080",  # navy
+"#D2691E",  # chocolate
+"#9ACD32",  # yellowgreen
+"#20B2AA",  # lightseagreen
+"#CD5C5C",  # indianred
+"#8FBC8F",  # darkseagreen
+"#800080",  # purple
+"#B03060",  # maroon3
+"#FF8C00",  # darkorange
+"#FFD700",  # gold
+"#FFFF00",  # yellow
+"#DEB887",  # burlywood
+"#00FF00",  # lime
+"#BA55D3",  # mediumorchid
+"#00FA9A",  # mediumspringgreen
+"#4169E1",  # royalblue
+"#E9967A",  # darksalmon
+"#DC143C",  # crimson
+"#00FFFF",  # aqua
+"#F4A460",  # sandybrown
+"#9370DB",  # mediumpurple
+"#0000FF",  # blue
+"#ADFF2F",  # greenyellow
+"#FF6347",  # tomato
+"#D8BFD8",  # thistle
+"#FF00FF",  # fuchsia
+"#DB7093",  # palevioletred
+"#F0E68C",  # khaki
+"#6495ED",  # cornflower
+"#DDA0DD",  # plum
+"#EE82EE",  # violet
+"#7FFFD4",  # aquamarine
+"#FAFAD2",  # lightgoldenrod
+"#FF69B4",  # hotpink
+"#FFB6C1",  # lightpink
+]
+no_hit_color = "#434348"
+col_count = 0
+serotypes = set()
+salmon_counts = defaultdict(defaultdict)
+salmon_counts["id"] = "BETTERCALLSAL_SALMON_COUNTS"
+salmon_counts["section_name"] = "Salmon read counts"
+salmon_counts["description"] = (
+"This section shows the read counts from running <code>salmon</code> "
++ "in <code>--meta</code> mode using SE, merged PE or concatenated PE reads against "
++ "an on-the-fly <code>salmon</code> index generated from the genome hits "
++ "of <code>kma</code>."
+)
+salmon_counts["plot_type"] = "bargraph"
+salmon_counts["pconfig"]["id"] = "bettercallsal_salmon_counts_plot"
+salmon_counts["pconfig"]["title"] = "Salmon: Read counts"
+salmon_counts["pconfig"]["ylab"] = "Number of reads"
+salmon_counts["pconfig"]["xDecimals"] = "false"
+salmon_counts["pconfig"]["cpswitch_counts_label"] = "Number of reads (Counts)"
+salmon_counts["pconfig"]["cpswitch_percent_label"] = "Number of reads (Percentages)"
+for sample in sorted(sample_salmon_counts.keys()):
+serotypes.update(list(sample_salmon_counts[sample].keys()))
+salmon_counts["data"][sample] = sample_salmon_counts[sample]
+if len(serotypes) > len(distinct_color_palette):
+distinct_color_palette = distinct_color_palette2
+for serotype in sorted(serotypes):
+if serotype == no_hit:
+continue
+if col_count == len(distinct_color_palette) - 1:
+col_count = 0
+col_count += 1
+salmon_counts["categories"][serotype] = {"color": distinct_color_palette[col_count]}
+salmon_counts["categories"][no_hit] = {"color": no_hit_color}
+json.dump(salmon_counts, open(file, "w"))
+if __name__ == "__main__":
+main()

Mercurial > repos > galaxytrakr > hfp_bettercallsal_awsbatch

comparison 1.0.0/bin/gen_salmon_res_table.py @ 0:801b85b03a17 draft default tip