Update reviewer comments

conf/test_full.config

@@ -22,6 +22,6 @@ params {
     nmpfams_latest_link     = params.pipelines_testdata_base_path + 'proteinannotator/testdata/nmpfams/nmpfamsdb_test.hmm.gz'
     metagroot_latest_link   = params.pipelines_testdata_base_path + 'proteinannotator/testdata/metagroot/metagroot_test.hmm.gz'
     // Functional annotation
-    interproscan_db_url       = params.pipelines_testdata_base_path + 'proteinannotator/testdata/interproscan_test.tar.gz'
+    interproscan_db_url       = params.pipelines_testdata_base_path + 'proteinannotator/testdata/interproscan/interproscan_test.tar.gz'
     interproscan_applications = 'Hamap,TIGRFAM,sfld'
 }

docs/output.md

@@ -102,7 +102,7 @@ If the `skip_*` flags (e.g., `skip_pfam`, `skip_funfam`, `skip_nmpfams`, `skip_m
 
 Each of the `domain_annotation/` subfolders (e.g., `pfam`, `funfam`, `nmpfams`, `metagroot`) contain a `.domtbl.gz` annotation file per input sample, depending on which domain annotation databases were used in the pipeline execution.
 
-[hmmer](https://github.com/EddyRivasLab/hmmer) is a fast and flexible alignment trimming tool that keeps phylogenetically informative sites and removes others.
+[hmmer](https://github.com/EddyRivasLab/hmmer) (HMMER) is a sequence search tool that uses profile hidden Markov models (profile HMMs) to identify homologous sequences against curated databases such as Pfam, FunFam, NMPFams and metagRoot.
 
 ### Functional annotation
 
@@ -114,7 +114,7 @@ Each of the `domain_annotation/` subfolders (e.g., `pfam`, `funfam`, `nmpfams`,
 - `functional_annotation/`
   - `interproscan/`
     - `<samplename>/`
-      - `<samplename>.gff`: general feature format (GFF) file
+      - `<samplename>.gff3`: general feature format (GFF) file
       - `<samplename>.json`: javascript object notation (JSON) file
       - `<samplename>.tsv`: tab-separated variable (TSV) file
       - `<samplename>.xml`: eXtensible markup language (XML) file
@@ -389,18 +389,6 @@ The `s4pred` module is used to predict secondary structures of amino acid sequen
 
 Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see <http://multiqc.info>.
 
-### SeqKit stats
-
-<details markdown="1">
-<summary>Output files</summary>
-
-- `seqkit/`
-  - `{prefix}.tsv`: output of `seqkit stats` command on `{prefix}.fasta` input file, in tab-delimited text format.
-
-</details>
-
-[SeqKit stats](https://bioinf.shenwei.me/seqkit/usage/#stats) generates simple statistics for protein FASTA files, such as number of residues, minimal sequence length, average sequence length, and maximal sequence length.
-
 ### Pipeline information
 
 <details markdown="1">

docs/usage.md

@@ -84,9 +84,8 @@ You can also generate such `YAML`/`JSON` files via [nf-core/launch](https://nf-c
 
 [InterProScan](https://github.com/ebi-pf-team/interproscan) is used to provide more information about the proteins annotated on the contigs. By default, turning on this subworkflow without `--skip_interproscan` will download and unzip the InterPro database. The database will then be saved in the output directory `<output_directory>/downloaded_dbs/interproscan_db/`. We recommend keeping a copy of this directory for future reuse in case the results folder is deleted.
 
-:::note
-The large database download (5.5GB) can take up to 4 hours depending on the bandwidth.
-:::
+> [!NOTE]
+> The large database download (5.5GB) can take up to 4 hours depending on the bandwidth.
 
 A local version of the database can be supplied to the pipeline by passing the InterProScan database directory to `--interproscan_db <path/to/downloaded-untarred-interproscan_db-dir/>`. The directory can be created by running (e.g. for database version 5.72-103.0):
 

modules.json

@@ -12,7 +12,7 @@
                     },
                     "hmmer/hmmsearch": {
                         "branch": "master",
-                        "git_sha": "6d46786420b4d7bc88eba026eb389c0c5535d120",
+                        "git_sha": "a971f6723149313787b278969dcbe0fb4411bb4a",
                         "installed_by": ["modules"]
                     },
                     "interproscan": {
@@ -50,11 +50,6 @@
                         "git_sha": "6d46786420b4d7bc88eba026eb389c0c5535d120",
                         "installed_by": ["faa_seqfu_seqkit"]
                     },
-                    "seqkit/stats": {
-                        "branch": "master",
-                        "git_sha": "6d46786420b4d7bc88eba026eb389c0c5535d120",
-                        "installed_by": ["modules"]
-                    },
                     "untar": {
                         "branch": "master",
                         "git_sha": "6d46786420b4d7bc88eba026eb389c0c5535d120",
@@ -71,7 +66,7 @@
                     },
                     "utils_nextflow_pipeline": {
                         "branch": "master",
-                        "git_sha": "05954dab2ff481bcb999f24455da29a5828af08d",
+                        "git_sha": "1a545fcbd762911c21a64ced3dbef99b2b51ac75",
                         "installed_by": ["subworkflows"]
                     },
                     "utils_nfcore_pipeline": {
@@ -81,7 +76,7 @@
                     },
                     "utils_nfschema_plugin": {
                         "branch": "master",
-                        "git_sha": "fdc08b8b1ae74f56686ce21f7ea11ad11990ce57",
+                        "git_sha": "ce3424257de288c0ca25f097a68d3a289da23f12",
                         "installed_by": ["subworkflows"]
                     }
                 }