Merge branch 'dev-test' into dev

.gitignore

 .nextflow*
 work/
 
+metagwgs.code-workspace

.gitlab-ci.yml

-# recipe for building singularity image and deploy it on the registery for bwa version 0.7.17
-image:
-   name: quay.io/singularity/singularity:v3.4.0
-   entrypoint: [""]
-
-stages:
- - build
- - deploy
-
-# Build Singularity container bwa_v0.7.17.sif
-singularity-image:
-   stage: build
-   script:
-       - singularity build metagWGS.sif env/Singularity_recipe_metagWGS
-       - singularity build eggnog_mapper.sif env/Singularity_recipe_eggnog_mapper
-       - singularity build mosdepth.sif env/Singularity_recipe_mosdepth
-   artifacts:
-      paths:
-       - metagWGS.sif
-       - eggnog_mapper.sif
-       - mosdepth.sif
-   only:
-    changes:
-      - .gitlab-ci.yml
-      - env/*
-
-# Push the image template.sif on the registry
-deploy:
-   stage: deploy
-   script:
-       - singularity push --docker-username "${CI_REGISTRY_USER}" --docker-password "${CI_REGISTRY_PASSWORD}" metagWGS.sif oras://"$CI_REGISTRY_IMAGE"/"$CI_PROJECT_NAME":"$CI_COMMIT_TAG"
-       - singularity push --docker-username "${CI_REGISTRY_USER}" --docker-password "${CI_REGISTRY_PASSWORD}" eggnog_mapper.sif oras://"$CI_REGISTRY_IMAGE"/eggnog_mapper:"$CI_COMMIT_TAG"
-       - singularity push --docker-username "${CI_REGISTRY_USER}" --docker-password "${CI_REGISTRY_PASSWORD}" mosdepth.sif oras://"$CI_REGISTRY_IMAGE"/mosdepth:"$CI_COMMIT_TAG"
-   only:
-    changes:
-      - .gitlab-ci.yml
-      - env/*

bin/filter_diamond_hits.py

+#!/usr/bin/env python3
+
+"""----------------------------------------------------------------------------
+  Script Name: filter_diamond_hits.py
+  Description: Keep best diamond hits for each query gene/protein 
+               based on best bitscore and filter out query with low identity and low coverage
+               Adapted from best_bitscore_diamond.py script of Joanna Fourquet
+  Input files: Diamond output file (.m8)
+  Created By:  Jean Mainguy
+  Date:        2021-08-02
+-------------------------------------------------------------------------------
+"""
+
+# Metadata
+__author__ = 'Mainguy Jean - Plateforme bioinformatique Toulouse'
+__copyright__ = 'Copyright (C) 2021 INRAE'
+__license__ = 'GNU General Public License'
+__version__ = '0.1'
+__email__ = 'support.bioinfo.genotoul@inra.fr'
+__status__ = 'dev'
+
+
+from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter, FileType
+import logging
+import sys
+import csv
+
+
+def get_hits_with_highest_bitscore(hits):
+    highest_bitscore = max([float(hit['bitScore']) for hit in hits])
+    return [hit for hit in hits if float(hit['bitScore']) == highest_bitscore]
+
+
+def get_all_hits_per_query(blast_result_file, header_list):
+    # Assertion: Hit are already sorted by query in diamond output.
+    # Both commands should output the same number of line:
+    # cut -f1 blast_result_file | uniq | wc -l
+    # cut -f1 blast_result_file | sort | uniq | wc -l
+
+    with open(blast_result_file) as in_fl:
+
+        result_reader = csv.DictReader(in_fl, delimiter='\t', fieldnames=header_list)
+
+        query_ids_processed = []
+
+        current_query_id = None
+        hits = []
+
+        for hit in result_reader:
+
+            if not current_query_id:
+                current_query_id = hit['queryId']
+
+            if current_query_id and current_query_id != hit['queryId']:
+                yield hits
+                hits = []
+
+                current_query_id = hit['queryId']
+                assert current_query_id not in query_ids_processed, f"Queries are not sorted in blast result. Query {current_query_id} is found in different part of the file."
+
+                query_ids_processed.append(current_query_id)
+
+            hits.append(hit)
+
+        if current_query_id:
+            yield hits
+
+
+def is_identity_and_coverage_ok(hit, min_identity, min_coverage):
+
+    qcovhsp = (int(hit["queryEnd"]) - int(hit["queryStart"]) + 1) / int(hit['queryLength'])
+    if float(hit['percIdentity']) >= min_identity or qcovhsp >= min_coverage:
+        return True
+    return False
+
+
+def parse_arguments():
+    """Parse script arguments."""
+    parser = ArgumentParser(description="...",
+                            formatter_class=ArgumentDefaultsHelpFormatter)
+
+    parser.add_argument('aln_input_file',
+                        help="File with blast/diamond matches expected format m8 \
+    \nqueryId, subjectId, percIdentity, alnLength, mismatchCount, gapOpenCount,\
+    queryStart, queryEnd, subjectStart, subjectEnd, eVal, bitScore")
+
+    parser.add_argument('-o', '--output_file', type=str,
+                        default="best_hit.tsv", help=("string specifying output file path"))
+
+    parser.add_argument('-i', '--min_identity', default=60, type=float,
+                        help="percentage of identity")
+
+    parser.add_argument('-c', '--min_coverage', default=70, type=float,
+                        help="percentage of coverage")
+
+    parser.add_argument("-v", "--verbose", help="increase output verbosity",
+                        action="store_true")
+
+    args = parser.parse_args()
+    return args
+
+
+def main():
+
+    args = parse_arguments()
+
+    if args.verbose:
+        logging.basicConfig(format="%(levelname)s: %(message)s", level=logging.DEBUG)
+        logging.info('Mode verbose ON')
+
+    else:
+        logging.basicConfig(format="%(levelname)s: %(message)s")
+
+    headers = "queryId subjectId percIdentity alnLength mismatchCount gapOpenCount queryStart queryEnd subjectStart subjectEnd eVal bitScore queryLength subjectLength subjectTitle"
+    header_list = headers.split(' ')
+
+    blast_result = args.aln_input_file
+    outfile = args.output_file
+    min_coverage = args.min_coverage
+    min_identity = args.min_identity
+    best_hit_count = 0
+    query_count_with_low_hit = 0
+
+    with open(outfile, 'w') as out_fl:
+        writer = csv.DictWriter(out_fl, fieldnames=header_list, delimiter='\t')
+
+        for query_i, query_hits in enumerate(get_all_hits_per_query(blast_result, header_list)):
+
+            if query_i % 10000 == 0:
+                logging.info(f'{query_i} queries processed... ')
+
+            correct_hits = [hit for hit in query_hits if is_identity_and_coverage_ok(
+                hit, min_identity, min_coverage)]
+
+            if not correct_hits:
+                query_count_with_low_hit += 1
+                continue
+
+            best_hits = get_hits_with_highest_bitscore(correct_hits)
+            for best_hit in best_hits:
+                best_hit_count += 1
+                writer.writerow(best_hit)
+
+    logging.info(f'{query_count_with_low_hit} queries ({100*query_count_with_low_hit/(query_i+1):.2f}%) have low hits that do not pass identity ({min_identity}%) or coverage ({min_coverage}%) thresholds')
+    logging.info(f'{best_hit_count} best hits of {query_i+1 - query_count_with_low_hit } queries have been written in {outfile}.')
+
+
+if __name__ == '__main__':
+    main()

bin/merge_abundance_and_functional_annotations.py

@@ -89,21 +89,21 @@ concat_diamond_files = pd.DataFrame()
 
 # Concatenate diamond files.
 for (diamond_idx,diamond_path) in enumerate(diamond_files):
-    diamond_file = pd.read_csv(diamond_path, delimiter='\t', decimal='.', header=None)
-    diamond_file.loc[:,1] = 'https://www.ncbi.nlm.nih.gov/protein/' + diamond_file.loc[:,1]
-    group_diamond_file = diamond_file.groupby(diamond_file.columns[0])\
-    .agg({diamond_file.columns[14] : ';'.join, diamond_file.columns[1] : ','.join})\
-    .reset_index()\
-    .reindex(columns=diamond_file.columns)
-    res_diamond_file = group_diamond_file.iloc[:,[0,1,14]]
+    diamond_columns = ["qseqid","sseqid","pident","length","mismatch","gapopen","qstart","qend","sstart","send","evalue","bitscore","qlen","slen","stitle"]
+    diamond_file = pd.read_csv(diamond_path, delimiter='\t', decimal='.', header=None, names=diamond_columns)
+    diamond_file.loc[:,"sseqid"] = 'https://www.ncbi.nlm.nih.gov/protein/' + diamond_file.loc[:,"sseqid"]
+    group_diamond_file = diamond_file.groupby("qseqid")\
+        .agg({"stitle" : ';'.join, "sseqid" : ','.join})\
+        .reset_index()\
+        .reindex(columns=diamond_file.columns)
+    res_diamond_file = group_diamond_file.loc[:,["qseqid","sseqid","stitle"]]
     concat_diamond_files = pd.concat([concat_diamond_files, res_diamond_file])
 
 # Merge counts, annotation and diamond results.
 merge_annot = pd.merge(counts_file,concat_eggnog_mapper_files,left_on="seed_cluster",right_on='#query_name', how='left')
-merge = pd.merge(merge_annot,concat_diamond_files,left_on="seed_cluster",right_on=concat_diamond_files.columns[0], how='left')
+merge = pd.merge(merge_annot,concat_diamond_files,left_on="seed_cluster",right_on="qseqid", how='left')
 merge.drop('#query_name', inplace=True, axis=1)
-merge.drop(merge.columns[28], inplace=True, axis=1)
-res_merge = merge.rename(columns = {1: 'diamond_db_id', 14: 'diamond_db_description'})
+merge.drop("qseqid", inplace=True, axis=1)
 
 # Write merge data frame in output file.
-res_merge.to_csv(args.output_file, sep="\t", index=False)
+merge.to_csv(args.output_file, sep="\t", index=False)

bin/merge_contig_quantif_perlineage.py

@@ -71,14 +71,19 @@ percontig = pd.read_csv(args.percontig_file, delimiter='\t', dtype=str)
 # Merge idxstats and .percontig.tsv files.
 merge = pd.merge(idxstats,percontig,left_on='contig',right_on='#contig', how='outer')
 
-#add depth
+# Add depth
 merge = pd.merge(merge,mosdepth,left_on='contig',right_on='contig', how='outer')
 
+# Fill NaN values to keep unmapped contigs.
+merge['consensus_lineage'] = merge['consensus_lineage'].fillna('Unknown')
+merge['tax_id_by_level'] = merge['tax_id_by_level'].fillna(1)
+merge['consensus_tax_id'] = merge['consensus_tax_id'].fillna(1)
+
 # Group by lineage and sum number of reads and contigs.
 res = merge.groupby(['consensus_lineage','consensus_tax_id', 'tax_id_by_level']).agg({'contig' : [';'.join, 'count'], 'mapped': 'sum', 'depth': 'mean'}).reset_index()
 res.columns=['lineage_by_level', 'consensus_tax_id', 'tax_id_by_level', 'name_contigs', 'nb_contigs', 'nb_reads', 'depth']
 
-# Fill the NaN by 0.
+# Fill NaN values with 0.
 res.fillna(0, inplace=True)
 
 # Split by taxonomic level

bin/merge_kaiju_results.py

@@ -57,7 +57,7 @@ with open(args.list_of_kaiju_files) as fkaiju_list:
     kaiju_files = fkaiju_list.read().split()
 
 # Merge kaiju results for all samples.
-for (kaiju_idx,kaiju_path) in enumerate(kaiju_files):
+for (kaiju_idx,kaiju_path) in enumerate(sorted(kaiju_files)):
     print(kaiju_idx)
     if(kaiju_idx==0):
         merge  = pd.read_csv(kaiju_path, delimiter='\t', dtype=str)

bin/quantification_by_contig_lineage.py

@@ -58,8 +58,8 @@ with open(args.list_of_input_files) as finput_list:
     sample_files = finput_list.read().split()
 
 # Merge results for all samples by lineage.
-for (sample_idx,sample_path) in enumerate(sample_files):
-    print("Read " + sample_path)
+for (sample_idx,sample_path) in enumerate(sorted(sample_files)):
+    print(sample_idx)
     if(sample_idx==0):
         merge  = pd.read_csv(sample_path, delimiter='\t', dtype=str)
         sample_name = os.path.splitext(sample_path)[0]
@@ -78,7 +78,7 @@ merge.rename(columns = {'name_contigs': 'name_contigs_' + sample_name, \
 'nb_reads': 'nb_reads_' + sample_name,\
 'depth': 'depth_' + sample_name},inplace=True)
 
-# Fill the NaN by 0.
+# Fill NaN values with 0.
 merge.fillna(0, inplace=True)
 print("Write " + args.output_file)
 # Write merge data frame in output file.

conf/base.config

@@ -44,14 +44,10 @@ process {
         memory = { 50.GB * task.attempt }
         cpus = 25
     }
-    withName: metaspades {
+    withName: assembly {
         memory = { 110.GB * task.attempt }
         cpus = 20
     }
-    withName: megahit {
-        cpus = 20
-        memory = { 100.GB * task.attempt }
-    }
     withName: quast {
         cpus = 4
         memory = { 8.GB * task.attempt }

conf/big_test_genotoul.config

@@ -45,14 +45,10 @@ process {
         memory = { 2.GB * task.attempt }
         cpus = 20
     }
-    withName: metaspades {
+    withName: assembly {
         memory = { 60.GB * task.attempt }
         cpus = 14
     }
-    withName: megahit {
-        cpus = 20
-        memory = { 60.GB * task.attempt }
-    }
     withName: quast {
         cpus = 3
         memory = { 8.GB * task.attempt }

conf/test_genotoul_testq.config

@@ -41,14 +41,10 @@ process {
         memory = { 36.GB * task.attempt }
         cpus = 4
     }
-    withName: metaspades {
+    withName: assembly {
         memory = { 10.GB * task.attempt }
         cpus = 8
     }
-    withName: megahit {
-        cpus = 8
-        memory = { 10.GB * task.attempt }
-    }
     withName: quast {
         cpus = 2
         memory = { 2.GB * task.attempt }

conf/test_genotoul_workq.config

 process.executor = 'slurm'
 includeConfig 'singularity.config'
-singularity.runOptions = "-B /work/bank/ -B /bank -B /work2 -B /work -B /save -B /home -B /work/project -B /usr/local/bioinfo"
+singularity.runOptions = "-B /work/bank/ -B /bank -B /work -B /work2 -B /save -B /home -B /work/project -B /usr/local/bioinfo"
 process.queue = 'workq'
 
 process {
@@ -15,18 +15,18 @@ process {
   maxErrors = '-1'
 
     withName: cutadapt {
-            cpus = 3
-            memory = { 1.GB * task.attempt }
+        cpus = 3
+        memory = { 1.GB * task.attempt }
     }
     withName: sickle {
-            memory = { 1.GB * task.attempt }
+        memory = { 1.GB * task.attempt }
     }
     withLabel: fastqc {
-            cpus = 6
-            memory = { 1.GB * task.attempt }
+        cpus = 6
+        memory = { 1.GB * task.attempt }
     }
     withName: multiqc {
-            memory = { 2.GB * task.attempt }
+        memory = { 2.GB * task.attempt }
     }
     withName: host_filter {
         memory = { 20.GB * task.attempt }
@@ -38,17 +38,13 @@ process {
         cpus = 6
     }
     withName: kaiju {
-        memory = { 100.GB * task.attempt }
+        memory = { 50.GB * task.attempt }
         cpus = 4
     }
-    withName: metaspades {
+    withName: assembly {
         memory = { 10.GB * task.attempt }
         cpus = 8
     }
-    withName: megahit {
-        cpus = 8
-        memory = { 10.GB * task.attempt }
-    }
     withName: quast {
         cpus = 2
         memory = { 2.GB * task.attempt }
@@ -75,8 +71,8 @@ process {
         memory = { 1.GB * task.attempt }
     }
     withName: diamond {
-        cpus = 2
-        memory = { 8.GB * task.attempt }
+        cpus = 8
+        memory = { 10.GB * task.attempt }
     }
     withName: get_software_versions {
         memory = { 1.GB * task.attempt }

conf/test_local.config

@@ -37,14 +37,10 @@ process {
         memory = { 10.GB * task.attempt }
         cpus = 2
     }
-    withName: metaspades {
+    withName: assembly {
         memory = { 2.GB * task.attempt }
         cpus = 3
     }
-    withName: megahit {
-        cpus = 3
-        memory = { 2.GB * task.attempt }
-    }
     withName: quast {
         cpus = 2
         memory = { 2.GB * task.attempt }

docs/README.md

@@ -45,7 +45,7 @@ A report html file is generated at the end of the workflow with [MultiQC](https:
 
 The pipeline is built using [Nextflow,](https://www.nextflow.io/docs/latest/index.html#) a bioinformatics workflow tool to run tasks across multiple compute infrastructures in a very portable manner.
 
-Two [Singularity](https://sylabs.io/docs/) containers are available making installation trivial and results highly reproducible.
+Three [Singularity](https://sylabs.io/docs/) containers are available making installation trivial and results highly reproducible.
 
 ## Documentation
 

docs/installation.md

@@ -32,7 +32,7 @@ A directory called `metagwgs` containing all source files of the pipeline have b
 
 ## III. Install Singularity
 
-metagWGS needs two [Singularity](https://sylabs.io/docs/) containers to run: Singularity version 3 or above must be installed.
+metagWGS needs three [Singularity](https://sylabs.io/docs/) containers to run: Singularity version 3 or above must be installed.
 
 See [here](https://sylabs.io/guides/3.7/user-guide/quick_start.html#quick-installation-steps) how to install Singularity >=v3.
 
@@ -43,9 +43,9 @@ See [here](https://sylabs.io/guides/3.7/user-guide/quick_start.html#quick-instal
 
 ## IV. Download or build Singularity containers
 
-You can directly download the two Singularity containers (`Solution 1`, recommended) or build them (`Solution 2`).
+You can directly download the three Singularity containers (`Solution 1`, recommended) or build them (`Solution 2`).
 
-### Solution 1 (recommended): download the two containers
+### Solution 1 (recommended): download the three containers
 
 **In the directory you want tu run the workflow**, where you have the directory `metagwgs` with metagWGS source files, run these command lines:
 
@@ -53,23 +53,26 @@ You can directly download the two Singularity containers (`Solution 1`, recommen
 cd metagwgs/env/
 singularity pull eggnog_mapper.sif oras://registry.forgemia.inra.fr/genotoul-bioinfo/metagwgs/eggnog_mapper:latest
 singularity pull metagwgs.sif oras://registry.forgemia.inra.fr/genotoul-bioinfo/metagwgs/metagwgs:latest
-singularity pull mosdepth.sif oras://registry.forgemia.inra.fr/genotoul-bioinfo/metagwgs/mosdepth:latest
+singularity pull mosdepth.sif oras://registry.forgemia.inra.fr/genotoul-bioinfo/metagwgs/metagwgs:latest
 ```
 
-Three files (`metagwgs.sif` , `mosdepth.sif` and `eggnog_mapper.sif`) must have been downloaded.
+Three files (`metagwgs.sif`, `eggnog_mapper.sif` and `mosdepth.sif`) must have been downloaded.
 
-### Solution 2: build the two containers.
+### Solution 2: build the three containers.
 
-**In the directory you want tu run the workflow**, where you have downloaded metagWGS source files, go to `metagwgs/env/` directory, and follow [these explanations](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/wikis/Singularity%20container) to build the two containers. You need two files by container to build them. These files are into the `metagwgs/env/` folder and you can read them here:
+**In the directory you want tu run the workflow**, where you have downloaded metagWGS source files, go to `metagwgs/env/` directory, and follow [these explanations](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/wikis/Singularity%20container) to build the three containers. You need three files by container to build them. These files are into the `metagwgs/env/` folder and you can read them here:
 
 * metagwgs.sif container
    * [metagWGS recipe file](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/env/Singularity_recipe_metagWGS)
    * [metagWGS.yml](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/env/metagWGS.yml)
-* eggnog_mapper container
+* eggnog_mapper.sif container
    * [eggnog_mapper recipe file](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/env/Singularity_recipe_eggnog_mapper)
    * [eggnog_mapper.yml](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/env/eggnog_mapper.yml)
+* mosdepth.sif container
+   * [mosdepth recipe file](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/env/Singularity_recipe_mosdepth)
+   * [mosdepth.yml](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/env/mosdepth.yml)
 
-At the end of the build, two files (`metagwgs.sif` and `eggnog_mapper.sif`) must have been generated.
+At the end of the build, three files (`metagwgs.sif`, `eggnog_mapper.sif` and `mosdepth.sif`) must have been generated.
 
 ## V. Use metagWGS
 

docs/usage.md

@@ -2,7 +2,7 @@
 
 ## I. Basic usage
 
-1. See [Installation page](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/docs/installation.md) to install metagWGS. Make sure you are in the directory where you downloaded `metagwgs` source files and added into `metagwgs/dev` the two Singularity images `metagwgs.sif` and `eggnog_mapper.sif`.
+1. See [Installation page](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/docs/installation.md) to install metagWGS. Make sure you are in the directory where you downloaded `metagwgs` source files and added into `metagwgs/env` the two Singularity images `metagwgs.sif` and `eggnog_mapper.sif`.
 
 2. metagWGS is still under development: you need to use the `dev` branch of the metagwgs repository.
 
@@ -108,7 +108,7 @@ It allows you to choose the configuration profile among:
 
 These profiles are associated to different configuration files developped [in this directory](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/tree/dev/conf). The `base.config` file available in this directory is the base configuration load in first which is crushed by indications of the profile you use. See [here](https://genotoul-bioinfo.pages.mia.inra.fr/use-nextflow-nfcore-course/nfcore/profiles.html) for more explanations.
 
-### 2. Usefull options
+### 2. Useful options
 
 #### `-resume`
 
@@ -223,7 +223,7 @@ No parameter available for this substep.
 
 * `--kaiju_db_dir "PATH/directory"`: if you have already downloaded the kaiju database, indicate its directory. **WARNING:** you will not be able to use kaiju database built with `kaiju-makedb` command line. Default: `--kaiju_db_dir false`. See **WARNING 2**.
 
-* `--kaiju_db "http://kaiju.binf.ku.dk/database/CHOOSEN_DATABASE.tgz"`: allows metagWGS to download kaiju database of your choice. The list of kaiju databases is available in [kaiju website](http://kaiju.binf.ku.dk/server), in the blue insert on the left side. Default: `--kaiju_db false`. See **WARNING 2**.
+* `--kaiju_db "http://kaiju.binf.ku.dk/database/CHOOSEN_DATABASE.tgz"`: allows metagWGS to download kaiju database of your choice. The list of kaiju databases is available in [kaiju website](http://kaiju.binf.ku.dk/server), in the blue insert on the left side. Default: `--kaiju_db https://kaiju.binf.ku.dk/database/kaiju_db_refseq_2021-02-26.tgz`. See **WARNING 2**.
 
 * `--skip_kaiju`: allows to skip taxonomic affiliation of reads with kaiju. Krona files will not be generated. Use: `--skip_kaiju`. See **WARNING 2**.
 
@@ -237,7 +237,7 @@ No parameter available for this substep.
 
 **WARNING 4:** the user has choice between `metaspades` or `megahit` for `--assembly` parameter. The choice can be based on CPUs and memory availability: `metaspades` needs more CPUs and memory than `megahit` but our tests showed that assembly metrics are better for `metaspades` than `megahit`.
 
-* `--metaspades_mem [memory_value]`: memory (in G) used by `metaspades` process. Default: `440`.
+* `--metaspades_mem [memory_value]`: memory (in Gb) used by `metaspades` process. Default: `440`.
 
 #### **`03_filtering` step:**
 
@@ -288,6 +288,8 @@ No parameters.
 
 * `--taxdump "FTP_PATH_TO_taxdump.tar.gz"`: indicates the FTP adress of the NCBI file `taxdump.tar.gz`. Default `"ftp://ftp.ncbi.nih.gov/pub/taxonomy/taxdump.tar.gz"`.
 
+* `--taxonomy_dir "PATH/directory": if you have already downloaded the accession2taxid and taxdump databases, indicate their parent directory. Default: `--taxonomy_dir false`.`
+
 #### **`08_binning` step:**
 
 **WARNING 13:** `08_binning` step depends on `01_clean_qc`, `02_assembly`, `03_filtering` (if you use it), `04_structural_annot` and `05_alignment` steps. You need to use mandatory files of these six steps to run `08_binning`. See [II. Input files](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/blob/dev/docs/usage.md#ii-input-files) and WARNINGS from 1 to 9.

functional_tests/README.md

+# Functional tests: Usage
+
+## I. Pre-requisites
+
+1. metagWGS is still under development: you need to use the `dev-test` branch of the metagwgs repository.
+
+    Run:
+    ```bash
+    cd metagwgs
+    git checkout dev-test
+    git pull
+    cd functional_tests
+    ```
+
+2. Make sure you are in the directory where you downloaded `metagwgs` source files and added the three mandatory Singularity images in `metagwgs/env`
+
+3. Make sure you downloaded all the required data files for metagwgs. If not, they will be downloaded by the pipeline each time you run it in a new project.
+
+4. Download the test datasets (expected results + test fastq) from [link-to-test-datasets].
+
+## II. Functional tests
+
+Each step of metagwgs produces a series of files. We want to be able to determine if the modifications we perform on metagwgs have an impact on any of these files (presence, contents, format, ...).
+
+Two datasets are currently available for these functional tests: test (from [metagwgs/test](https://forgemia.inra.fr/genotoul-bioinfo/metagwgs/-/tree/master/test)) and MAG (from [nf-core/test-datasets](https://github.com/nf-core/test-datasets/tree/mag/test_data))
+
+When launching the functional test script, the files contained in *exp_dir* (in ./test_expected_logs) are scanned and, for each possible file extension, a test if performed on an expected file against it's observed version (in ./results).
+
+### Test methods
+
+5 simple test methods are used:
+
+diff: simple bash difference between two files
+`diff exp_path obs_path`
+
+zdiff: simple bash difference between two gzipped files
+`zdiff exp_path obs_path`
+
+no_header_diff: remove the headers of .annotations and .seed_orthologs files
+`diff <(grep -w "^?#" exp_path) <(grep -w "^?#" obs_path)`
+
+cut_diff: exception for cutadapt.log file
+`diff <(tail -n+6 exp_path) <(tail -n+6 obs_path)`
+
+not_empty: in python, check if file is empty
+`test = path.getsize(obs_path) > 0`
+
+## III. Launch test
+
+Nextflow metagwgs can be launched on any cluster manager (sge, slurm, ...). The script for functional tests can use a provided script containing the command to launch Nextflow on a cluster.
+
+Exemples below use the slurm job manager and launche all 7 steps of metagwgs to ensure all parts of main.nf work as intended.
+
+### Launch with script
+
+Create a new directory (project-directory) containing a shell script to be used by functional tests:
+
+```
+#!/bin/bash
+
+sbatch -W -p workq -J metagwgs --mem=6G \
+    --wrap="module load bioinfo/Nextflow-v21.04.1 ; module load system/singularity-3.7.3 ; nextflow run -profile test_genotoul_workq [work_dir]/metaG/metagwgs/main.nf --step '01_clean_qc,02_assembly,03_filtering,04_structural_annot,05_alignment,06_func_annot,07_taxo_affi' --reads '../metagwgs/test/*_{R1,R2}.fastq.gz' --host_fasta '[work_dir]/human_ref/Homo_sapiens.GRCh38_chr21.fa' --host_bwa_index '[work_dir]/human_ref/Homo_sapiens.GRCh38_chr21.fa.{amb,ann,bwt,pac,sa}' --kaiju_db_dir '/bank/kaijudb/kaijudb_refseq_2020-05-25' --taxonomy_dir '[work_dir]/taxonomy' --eggnog_mapper_db_dir '/bank/eggnog-mapper/eggnog-mapper-2.0.4-rf1/data' --assembly metaspades --diamond_bank "[work_dir]/refseq_bacteria_2021-05-20/refseq_bacteria.dmnd" -with-report -with-timeline -with-trace -with-dag -resume"
+```
+
+Then launch this command:
+
+```
+cd project-directory
+python [work_dir]/metaG/metagwgs/functional_tests/main.py -step 07_taxo_affi -exp_dir [work_dir]/test_expected_logs -obs_dir ./results --script launch_07_taxo_affi.sh
+```
+
+### Launch without script
+
+If you already have launched metagwgs [see metagwgs README and usage] on test data:
+
+```
+cd project-directory
+python [work_dir]/metaG/metagwgs/functional_tests/main.py -step 07_taxo_affi -exp_dir [work_dir]/test_expected_logs -obs_dir ./results
+```
+
+## Output
+
+A ft_\[step\].log file is created for each step of metagwgs. It contains information about each test performed on given files.
+
+Exemple with ft_01_clean_qc.log:
+
+```
+Expected directory: /work/pmartin2/metaG/test_expected_logs/01_clean_qc
+vs
+Observed directory: /work/pmartin2/metaG/refac_09_13.2/results/01_clean_qc
+
+------------------------------------------------------------------------------
+