feat: Amrfinderplus

.examples/Lactobacillus_delbrueckii/project_config.yaml

@@ -29,3 +29,4 @@ rules:
   cblaster-genome: TRUE
   cblaster-bgc: FALSE
   gecco: TRUE
+  amrfinderplus: FALSE

.tests/config/test1/project_config.yaml

@@ -20,5 +20,5 @@ rules:
   deeptfactor-roary: FALSE
   cblaster-genome: TRUE
   cblaster-bgc: TRUE
-  ppanggolin: TRUE
   gecco: TRUE
+  amrfinderplus: TRUE

.tests/config/test2/project_config.yaml

@@ -20,4 +20,5 @@ rules:
   deeptfactor-roary: FALSE
   cblaster-genome: TRUE
   cblaster-bgc: TRUE
-  ppanggolin: TRUE
+  gecco: TRUE
+  amrfinderplus: TRUE

.tests/config/test3/project_config.yaml

@@ -20,4 +20,5 @@ rules:
   deeptfactor-roary: FALSE
   cblaster-genome: TRUE
   cblaster-bgc: TRUE
-  ppanggolin: TRUE
+  gecco: TRUE
+  amrfinderplus: TRUE

workflow/Snakefile

@@ -92,6 +92,7 @@ include: "rules/cblaster.smk"
 include: "rules/data_warehouse.smk"
 include: "rules/convert_genbank.smk"
 include: "rules/gecco.smk"
+include: "rules/amrfinderplus.smk"
 
 ##### 4. Generate user-defined local resources
 custom_resource_dir(config["resources_path"], resource_mapping)

workflow/bgcflow/bgcflow/data/gather_amrfinder.py

@@ -0,0 +1,64 @@
+import logging
+import sys
+from pathlib import Path
+
+import pandas as pd
+
+log_format = "%(levelname)-8s %(asctime)s   %(message)s"
+date_format = "%d/%m %H:%M:%S"
+logging.basicConfig(format=log_format, datefmt=date_format, level=logging.DEBUG)
+
+
+def cleanup_amrfinder(input_file, genome_id=None):
+    """
+    Cleans up the AMRFinder output file by filling null values in the 'Protein identifier' column
+    with a combination of 'Contig id', 'Start', and 'Stop' coordinates. Adds a 'genome_id' column.
+
+    Parameters:
+    input_file (str): Path to the input file.
+    genome_id (str, optional): Genome identifier. If not provided, it will be derived from the input file name.
+
+    Returns:
+    pd.DataFrame: Cleaned DataFrame.
+    """
+    input_path = Path(input_file)
+    if genome_id is None:
+        genome_id = input_path.stem
+    df = pd.read_csv(input_path, sep="\t")
+
+    # Fill null values in 'Protein identifier' with a combination of 'Contig id', 'Start', and 'Stop'
+    df["Protein identifier"] = df.apply(
+        lambda row: row["Protein identifier"]
+        if pd.notnull(row["Protein identifier"])
+        else f"{row['Contig id']}_{row['Start']}_{row['Stop']}",
+        axis=1,
+    )
+    df["genome_id"] = genome_id
+
+    return df
+
+
+def gather_amrfinder(input_list, output_file):
+    """
+    Gathers and cleans up multiple AMRFinder output files listed in an input file,
+    concatenates them into a single DataFrame, and writes the result to an output file.
+
+    Parameters:
+    input_list (str): Path to the file containing a list of input file paths.
+    output_file (str): Path to the output file where the concatenated DataFrame will be saved.
+
+    Returns:
+    None
+    """
+    dataframes = []
+
+    with open(input_list, "r") as f:
+        data = f.read()
+
+    dataframes = pd.concat([cleanup_amrfinder(i) for i in data.split()])
+    dataframes.to_csv(output_file, index=False)
+    return
+
+
+if __name__ == "__main__":
+    gather_amrfinder(sys.argv[1], sys.argv[2])

workflow/envs/amrfinderplus.post-deploy.sh

@@ -0,0 +1 @@
+amrfinder -u

workflow/envs/amrfinderplus.yaml

@@ -0,0 +1,7 @@
+name: amrfinder
+channels:
+  - conda-forge
+  - bioconda
+  - defaults
+dependencies:
+  -  ncbi-amrfinderplus

workflow/notebook/amrfinderplus.py.ipynb

@@ -0,0 +1,92 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "aa0f0d95-5e6b-436f-a971-9486d0841329",
+   "metadata": {},
+   "source": [
+    "# AMRFinderPlus\n",
+    "Summary of [AMRFinderPlus](https://github.com/ncbi/amr) results from project: `[{{ project().name }}]` \n",
+    "\n",
+    "## Description\n",
+    "Identify AMR genes and point mutations, and virulence and stress resistance genes in assembled bacterial nucleotide and protein sequence.\n",
+    "\n",
+    "## AMR Hits Overview"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d21448bb-afe9-4fdb-b964-2143a0ccd1e4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from IPython.display import display, Markdown, HTML\n",
+    "from pathlib import Path\n",
+    "import altair as alt\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "from itables import to_html_datatable as DT\n",
+    "import itables.options as opt\n",
+    "opt.css = \"\"\"\n",
+    ".itables table td { font-style: italic; font-size: .8em;}\n",
+    ".itables table th { font-style: oblique; font-size: .8em; }\n",
+    "\"\"\"\n",
+    "opt.classes = [\"display\", \"compact\"]\n",
+    "opt.lengthMenu = [5, 10, 20, 50, 100, 200, 500]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "53fb8b15-379c-4be1-827e-243602f89d95",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "report_dir = Path(\"../\")\n",
+    "amr_table = report_dir / \"tables/df_amrfinderplus.csv\"\n",
+    "df = pd.read_csv(amr_table)\n",
+    "\n",
+    "display(HTML(DT(df, columnDefs=[{\"className\": \"dt-center\", \"targets\": \"_all\"}],)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4d8fe1ca-30f9-472a-9e01-4e9db61825b8",
+   "metadata": {},
+   "source": [
+    "[Download Table]({{ project().file_server() }}/tables/df_amrfinderplus.csv){:target=\"_blank\" .md-button}\n",
+    "\n",
+    "## References\n",
+    "<font size=\"2\">\n",
+    "{% for i in project().rule_used['amrfinderplus']['references'] %}\n",
+    "- *{{ i }}*\n",
+    "{% endfor %}\n",
+    "</font>"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

workflow/rules.yaml

@@ -241,3 +241,11 @@ gecco:
   - "Accurate de novo identification of biosynthetic gene clusters with GECCO. Laura M Carroll,
     Martin Larralde, Jonas Simon Fleck, Ruby Ponnudurai, Alessio Milanese, Elisa Cappio Barazzone,
     Georg Zeller. bioRxiv 2021.05.03.442509; doi:10.1101/2021.05.03.442509"
+amrfinderplus:
+  final_output: "data/processed/{name}/tables/df_amrfinderplus.csv"
+  description: Identify AMR genes and point mutations, and virulence and stress resistance genes in assembled bacterial nucleotide and protein sequence.
+  category: Genome Mining
+  link:
+  - https://github.com/ncbi/amr
+  references:
+  - "Feldgarden M, Brover V, Gonzalez-Escalona N, Frye JG, Haendiges J, Haft DH, Hoffmann M, Pettengill JB, Prasad AB, Tillman GE, Tyson GH, Klimke W. AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence. Sci Rep. 2021 Jun 16;11(1):12728. doi: 10.1038/s41598-021-91456-0. PMID: 34135355; PMCID: PMC8208984."

workflow/rules/amrfinderplus.smk

@@ -0,0 +1,52 @@
+rule amrfinderplus:
+    input:
+        fna="data/interim/fasta/{strains}.fna",
+        faa="data/interim/prokka/{strains}/{strains}.faa",
+        gff="data/interim/prokka/{strains}/{strains}.gff",
+    output:
+        table="data/interim/amrfinderplus/{strains}.tsv",
+    log:
+        "logs/amrfinderplus/amrfinderplus/{strains}.log"
+    conda:
+        "../envs/amrfinderplus.yaml"
+    params:
+        annotation="prokka",
+        ident_min="-1",
+        coverage_min="0.5",
+        translation_table="11",
+    threads: 4
+    shell:
+        """
+        amrfinder -p {input.faa} \
+            -n {input.fna} \
+            -g {input.gff} \
+            -a {params.annotation} \
+            --plus \
+            --ident_min {params.ident_min} \
+            --coverage_min {params.coverage_min} \
+            --translation_table {params.translation_table} \
+            --threads {threads} \
+            --log {log} > {output.table}
+        """
+
+rule amrfinder_gather:
+    input:
+        tables=lambda wildcards: expand(
+            "data/interim/amrfinderplus/{strains}.tsv",
+            strains=[s for s in PEP_PROJECTS[wildcards.name].sample_table.genome_id.unique()],
+        ),
+    output:
+        table="data/processed/{name}/tables/df_amrfinderplus.csv"
+    conda:
+        "../envs/bgc_analytics.yaml"
+    log:
+        "logs/amrfinderplus/gather/amrfinderplus_gather_{name}.log"
+    shell:
+        """
+        TMPDIR="data/interim/tmp/{wildcards.name}"
+        mkdir -p $TMPDIR
+        INPUT_TSV="$TMPDIR/df_amrfinderplus.txt"
+        echo '{input.tables}' > $INPUT_TSV
+        python workflow/bgcflow/bgcflow/data/gather_amrfinder.py $INPUT_TSV {output.table} 2>> {log}
+        rm $INPUT_TSV
+        """