diff --git a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md index c7fad072c0ce73..18647f7df36a8e 100644 --- a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md +++ b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/tutorial.md @@ -825,7 +825,7 @@ To identifly VFs, we use again **ABRicate** but this time with the [__VFDB__](ht > > > > > -> > 1. 178 +> > 1. 188 > > 2. 287 > > > {: .solution} diff --git a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/gene_based_pathogen_identification.ga b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/gene_based_pathogen_identification.ga index ee0f1760b08001..4280e1f9ac46e0 100644 --- a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/gene_based_pathogen_identification.ga +++ b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/gene_based_pathogen_identification.ga @@ -62,7 +62,7 @@ 490.20000000000005 ], "size": [ - 1468.9, + 1469, 676 ], "type": "frame" @@ -335,8 +335,8 @@ } ], "position": { - "left": 567.3965680047581, - "top": 600.4380260342729 + "left": 576.4000244140625, + "top": 602.433349609375 }, "post_job_actions": { "RenameDatasetActionassembly_gfa": { @@ -491,8 +491,8 @@ } ], "position": { - "left": 866.8164079423491, - "top": 530.2435125197246 + "left": 923.816650390625, + "top": 543.25 }, "post_job_actions": { "RenameDatasetActionout_calls": { @@ -544,6 +544,16 @@ "uuid": "9e88fc55-f41e-4e87-852e-044359dcea53", "when": null, "workflow_outputs": [ + { + "label": "medaka_gaps_in_draft_bed_file", + "output_name": "out_gaps", + "uuid": "9e5ad6ec-b408-4132-ba07-dec9fa626923" + }, + { + "label": "medaka_log_file", + "output_name": "out_log", + "uuid": "fcbd3e3f-2e93-4798-b696-dad7db9f2efd" + }, { "label": "medaka_propability_h5_file", "output_name": "out_probs", @@ -558,16 +568,6 @@ "label": "sample_all_contigs", "output_name": "out_consensus", "uuid": "df361e19-b6d1-405b-96cc-b48c1ab7c604" - }, - { - "label": "medaka_gaps_in_draft_bed_file", - "output_name": "out_gaps", - "uuid": "9e5ad6ec-b408-4132-ba07-dec9fa626923" - }, - { - "label": "medaka_log_file", - "output_name": "out_log", - "uuid": "fcbd3e3f-2e93-4798-b696-dad7db9f2efd" } ] }, @@ -592,8 +592,8 @@ } ], "position": { - "left": 865.4604146352689, - "top": 952.5388644706219 + "left": 927.4666748046875, + "top": 965.5333251953125 }, "post_job_actions": { "RenameDatasetActionoutfile": { @@ -602,6 +602,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "outfile" + }, + "TagDatasetActionoutfile": { + "action_arguments": { + "tags": "bandage_contigs_image" + }, + "action_type": "TagDatasetAction", + "output_name": "outfile" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/bandage/bandage_image/2022.09+galaxy4", @@ -684,8 +691,8 @@ } ], "position": { - "left": 1140.4696953781227, - "top": 704.7343141173069 + "left": 1210.4666748046875, + "top": 757.7333374023438 }, "post_job_actions": { "RenameDatasetActionoutput": { @@ -737,8 +744,8 @@ } ], "position": { - "left": 1841.7640500107245, - "top": 40.58262725656508 + "left": 1831.7666625976562, + "top": 31.583328247070312 }, "post_job_actions": { "RenameDatasetActionreport": { @@ -747,6 +754,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "report" + }, + "TagDatasetActionreport": { + "action_arguments": { + "tags": "vfs_of_genes_identified_by_vfdb" + }, + "action_type": "TagDatasetAction", + "output_name": "report" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/abricate/abricate/1.0.1", @@ -790,8 +804,8 @@ } ], "position": { - "left": 1850.2448752594782, - "top": 680.3198211345596 + "left": 1847.25, + "top": 671.316650390625 }, "post_job_actions": { "RenameDatasetActionreport": { @@ -800,6 +814,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "report" + }, + "TagDatasetActionreport": { + "action_arguments": { + "tags": "amr_identified_by_ncbi" + }, + "action_type": "TagDatasetAction", + "output_name": "report" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/abricate/abricate/1.0.1", @@ -847,8 +868,8 @@ } ], "position": { - "left": 1402.327121827037, - "top": 721.534701862199 + "left": 1528.3333740234375, + "top": 802.5333251953125 }, "post_job_actions": { "RenameDatasetActionoutfile": { @@ -914,6 +935,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "outfile" + }, + "TagDatasetActionoutfile": { + "action_arguments": { + "tags": "vfs" + }, + "action_type": "TagDatasetAction", + "output_name": "outfile" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4", @@ -971,6 +999,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "outfile" + }, + "TagDatasetActionoutfile": { + "action_arguments": { + "tags": "amrs" + }, + "action_type": "TagDatasetAction", + "output_name": "outfile" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_find_and_replace/1.1.4", @@ -1014,8 +1049,8 @@ } ], "position": { - "left": 1558.8806090867188, - "top": 1032.6658496782338 + "left": 1542.88330078125, + "top": 1009.6666870117188 }, "post_job_actions": { "RenameDatasetActionoutput": { @@ -1024,6 +1059,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "output" + }, + "TagDatasetActionoutput": { + "action_arguments": { + "tags": "contigs" + }, + "action_type": "TagDatasetAction", + "output_name": "output" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/devteam/tabular_to_fasta/tab2fasta/1.1.1", @@ -1053,6 +1095,6 @@ "name:IWC", "name:microGalaxy" ], - "uuid": "99635f92-f694-4a3e-bf28-411c0973dc6a", - "version": 132 + "uuid": "d6795753-1562-4ccc-8f9c-f598acd5404e", + "version": 142 } diff --git a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_allele_based_pathogen_identification.ga b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_allele_based_pathogen_identification.ga index 74376aa637e382..4d41cf3073e7ae 100644 --- a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_allele_based_pathogen_identification.ga +++ b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_allele_based_pathogen_identification.ga @@ -302,7 +302,7 @@ "owner": "iuc", "tool_shed": "toolshed.g2.bx.psu.edu" }, - "tool_state": "{\"alignment_options\": {\"splicing\": {\"splice_mode\": \"preset\", \"__current_case__\": 0}, \"A\": null, \"B\": null, \"O\": null, \"O2\": null, \"E\": null, \"E2\": null, \"z\": null, \"z2\": null, \"s\": null, \"no_end_flt\": true}, \"fastq_input\": {\"fastq_input_selector\": \"single\", \"__current_case__\": 0, \"fastq_input1\": {\"__class__\": \"RuntimeValue\"}, \"analysis_type_selector\": {\"__class__\": \"ConnectedValue\"}}, \"indexing_options\": {\"H\": false, \"k\": null, \"w\": null, \"I\": null}, \"io_options\": {\"output_format\": \"BAM\", \"Q\": false, \"L\": false, \"K\": null, \"cs\": null, \"c\": false, \"eqx\": false, \"Y\": false}, \"mapping_options\": {\"N\": null, \"F\": null, \"f\": null, \"kmer_ocurrence_interval\": {\"interval\": \"\", \"__current_case__\": 1}, \"min_occ_floor\": null, \"q_occ_frac\": \"0.01\", \"g\": null, \"r\": null, \"n\": null, \"m\": null, \"max_chain_skip\": null, \"max_chain_iter\": null, \"X\": false, \"p\": null, \"mask_len\": null}, \"reference_source\": {\"reference_source_selector\": \"history\", \"__current_case__\": 1, \"ref_file\": {\"__class__\": \"RuntimeValue\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_state": "{\"alignment_options\": {\"splicing\": {\"splice_mode\": \"preset\", \"__current_case__\": 0}, \"A\": null, \"B\": null, \"O\": null, \"O2\": null, \"E\": null, \"E2\": null, \"z\": null, \"z2\": null, \"s\": null, \"no_end_flt\": true}, \"fastq_input\": {\"fastq_input_selector\": \"single\", \"__current_case__\": 0, \"fastq_input1\": {\"__class__\": \"ConnectedValue\"}, \"analysis_type_selector\": {\"__class__\": \"ConnectedValue\"}}, \"indexing_options\": {\"H\": false, \"k\": null, \"w\": null, \"I\": null}, \"io_options\": {\"output_format\": \"BAM\", \"Q\": false, \"L\": false, \"K\": null, \"cs\": null, \"c\": false, \"eqx\": false, \"Y\": false}, \"mapping_options\": {\"N\": null, \"F\": null, \"f\": null, \"kmer_ocurrence_interval\": {\"interval\": \"\", \"__current_case__\": 1}, \"min_occ_floor\": null, \"q_occ_frac\": \"0.01\", \"g\": null, \"r\": null, \"n\": null, \"m\": null, \"max_chain_skip\": null, \"max_chain_iter\": null, \"X\": false, \"p\": null, \"mask_len\": null}, \"reference_source\": {\"reference_source_selector\": \"history\", \"__current_case__\": 1, \"ref_file\": {\"__class__\": \"ConnectedValue\"}}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "2.24+galaxy0", "type": "tool", "uuid": "6da37636-966d-4975-bce3-d650feaeb17c", @@ -787,6 +787,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "output" + }, + "TagDatasetActionoutput": { + "action_arguments": { + "tags": "extracted_fields_from_the_vcf_output" + }, + "action_type": "TagDatasetAction", + "output_name": "output" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/snpsift/snpSift_extractFields/4.3+t.galaxy0", @@ -968,8 +975,8 @@ } ], "position": { - "left": 1868.6611511712222, - "top": 952.9024800002072 + "left": 1861.2076226643767, + "top": 940.9587935676732 }, "post_job_actions": { "RenameDatasetActionoutput": { @@ -978,6 +985,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "output" + }, + "TagDatasetActionoutput": { + "action_arguments": { + "tags": "mapping_coverage_percentage_per_sample" + }, + "action_type": "TagDatasetAction", + "output_name": "output" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/nml/collapse_collections/collapse_dataset/5.1.0", @@ -1130,8 +1144,8 @@ } ], "position": { - "left": 2254.026959999296, - "top": 632.8951200002152 + "left": 2249.0333251953125, + "top": 620.8999938964844 }, "post_job_actions": { "RenameDatasetActionout_file1": { @@ -1140,6 +1154,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "out_file1" + }, + "TagDatasetActionout_file1": { + "action_arguments": { + "tags": "mapping_mean_depth_per_sample" + }, + "action_type": "TagDatasetAction", + "output_name": "out_file1" } }, "tool_id": "Paste1", @@ -1265,6 +1286,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "out_file1" + }, + "TagDatasetActionout_file1": { + "action_arguments": { + "tags": "number_of_variants_per_sample" + }, + "action_type": "TagDatasetAction", + "output_name": "out_file1" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3", @@ -1295,6 +1323,6 @@ "name:Nanopore", "name:IWC" ], - "uuid": "34e3f52d-531d-4ef4-916d-a988098c1914", - "version": 67 + "uuid": "deb94861-ed4d-41fe-881a-8565c6b8fa82", + "version": 69 } diff --git a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_preprocessing.ga b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_preprocessing.ga index 661cb93835c4e6..b001e9a10a619b 100644 --- a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_preprocessing.ga +++ b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/nanopore_preprocessing.ga @@ -4,40 +4,28 @@ "comments": [ { "child_steps": [ - 2, - 5 + 11, + 17, + 25, + 14, + 23, + 24 ], "color": "green", "data": { - "title": "Trimming to retain samples reads quality" + "title": "Creating a table for samples reads count before and after hosts sequences removal and the percentage of found hosts sequences" }, - "id": 1, + "id": 7, "position": [ - 294, - 474 + 2025.8999999999999, + 798.6999999999999 ], "size": [ - 498, - 346.8 + 1403, + 223 ], "type": "frame" }, - { - "color": "lime", - "data": { - "text": "In this workflow, we recommend nanopore samples since we are using some tools that are specified for nanopore such as: Minimap2, Nanoplot porechp and fastp.\n\nIn order to switch to illumina please remove the nanoplot step, replace porechop and fastp with cutadapt or trimmomatic, and finally replace Minimap2 with Bowtie2.\n\nThis workflow also take single-end reads to switch to paired-end, you have to check this option in most of the tools used. " - }, - "id": 0, - "position": [ - 294.3, - 145.60000000000002 - ], - "size": [ - 460, - 228 - ], - "type": "markdown" - }, { "child_steps": [ 13, @@ -71,12 +59,12 @@ }, "id": 5, "position": [ - 890.2, - 918.9 + 892.1, + 911.2 ], "size": [ - 571.2, - 785.3 + 569.3, + 815 ], "type": "frame" }, @@ -92,12 +80,12 @@ }, "id": 4, "position": [ - 292, - 923.4 + 293, + 915.4 ], "size": [ - 521, - 780 + 520, + 810 ], "type": "frame" }, @@ -141,34 +129,46 @@ 0 ], "size": [ - 1688.1, - 294.5 + 1772, + 293 ], "type": "frame" }, { "child_steps": [ - 11, - 17, - 25, - 14, - 23, - 24 + 2, + 5 ], "color": "green", "data": { - "title": "Creating a table for samples reads count before and after hosts sequences removal and the percentage of found hosts sequences" + "title": "Trimming to retain samples reads quality" }, - "id": 7, + "id": 1, "position": [ - 2025.8999999999999, - 798.6999999999999 + 294, + 474 ], "size": [ - 1403, - 223 + 498, + 346.8 ], "type": "frame" + }, + { + "color": "lime", + "data": { + "text": "In this workflow, we recommend nanopore samples since we are using some tools that are specified for nanopore such as: Minimap2, Nanoplot porechp and fastp.\n\nIn order to switch to illumina please remove the nanoplot step, replace porechop and fastp with cutadapt or trimmomatic, and finally replace Minimap2 with Bowtie2.\n\nThis workflow also take single-end reads to switch to paired-end, you have to check this option in most of the tools used. " + }, + "id": 0, + "position": [ + 294.3, + 145.60000000000002 + ], + "size": [ + 460, + 228 + ], + "type": "markdown" } ], "creator": [ @@ -334,8 +334,8 @@ } ], "position": { - "left": 312, - "top": 963.4027630516179 + "left": 314, + "top": 955.4031261035689 }, "post_job_actions": { "RenameDatasetActionlog_read_length": { @@ -387,6 +387,11 @@ "uuid": "60c022d4-2cc5-4caf-a9f0-333cf8a3edc7", "when": null, "workflow_outputs": [ + { + "label": "nanoplot_qc_on_reads_before_preprocessing_nanostats", + "output_name": "nanostats", + "uuid": "15ecf5b1-e0eb-405a-ac3a-359feb66d4cd" + }, { "label": "nanoplot_on_reads_before_preprocessing_nanostats_post_filtering", "output_name": "nanostats_post_filtering", @@ -396,11 +401,6 @@ "label": "nanoplot_qc_on_reads_before_preprocessing_html_report", "output_name": "output_html", "uuid": "f2bd0a1f-cd60-4a36-a7d0-8025cc19ea2e" - }, - { - "label": "nanoplot_qc_on_reads_before_preprocessing_nanostats", - "output_name": "nanostats", - "uuid": "15ecf5b1-e0eb-405a-ac3a-359feb66d4cd" } ] }, @@ -459,6 +459,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "text_file" + }, + "TagDatasetActionhtml_file": { + "action_arguments": { + "tags": "FastQC_Before_Preprocessing_HTM" + }, + "action_type": "TagDatasetAction", + "output_name": "html_file" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/devteam/fastqc/fastqc/0.74+galaxy0", @@ -516,8 +523,8 @@ } ], "position": { - "left": 572, - "top": 513.9721887008918 + "left": 575, + "top": 505.969807011772 }, "post_job_actions": { "RenameDatasetActionout1": { @@ -533,6 +540,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "report_html" + }, + "TagDatasetActionreport_html": { + "action_arguments": { + "tags": "fastp_HTML" + }, + "action_type": "TagDatasetAction", + "output_name": "report_html" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/fastp/fastp/0.23.4+galaxy0", @@ -602,6 +616,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "stats" + }, + "TagDatasetActionhtml_report": { + "action_arguments": { + "tags": "MultiQC_Before_Preprocessing_HTML" + }, + "action_type": "TagDatasetAction", + "output_name": "html_report" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1", @@ -617,15 +638,15 @@ "uuid": "cf00d759-c11e-4e7c-bc39-2735ada49668", "when": null, "workflow_outputs": [ - { - "label": "multiQC_html_report_before_preprocessing", - "output_name": "html_report", - "uuid": "0f92196d-047d-4918-819d-c0ff7cd3ae85" - }, { "label": "multiQC_stats_before_preprocessing", "output_name": "stats", "uuid": "ebffe782-a56c-431f-8af4-c0cb8d7a02fc" + }, + { + "label": "multiQC_html_report_before_preprocessing", + "output_name": "html_report", + "uuid": "0f92196d-047d-4918-819d-c0ff7cd3ae85" } ] }, @@ -663,8 +684,8 @@ } ], "position": { - "left": 906.0314896173257, - "top": 55.860022459943664 + "left": 895.0333251953125, + "top": 55.86977039067824 }, "post_job_actions": { "RenameDatasetActionalignment_output": { @@ -724,8 +745,8 @@ } ], "position": { - "left": 910.1959411446596, - "top": 958.9066643599034 + "left": 914.2000122070312, + "top": 951.2031138965376 }, "post_job_actions": { "RenameDatasetActionlog_read_length": { @@ -782,15 +803,15 @@ "output_name": "output_html", "uuid": "b5899290-4c57-4662-ad22-860654652ade" }, - { - "label": "nanoplot_qc_on_reads_after_preprocessing_nanostats", - "output_name": "nanostats", - "uuid": "42db7f93-919e-4bbb-81a1-06411a9da410" - }, { "label": "nanoplot_on_reads_after_preprocessing_nanostats_post_filtering", "output_name": "nanostats_post_filtering", "uuid": "949bfdf5-3d79-4dad-bdd8-c3a25e6af4cf" + }, + { + "label": "nanoplot_qc_on_reads_after_preprocessing_nanostats", + "output_name": "nanostats", + "uuid": "42db7f93-919e-4bbb-81a1-06411a9da410" } ] }, @@ -849,6 +870,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "text_file" + }, + "TagDatasetActionhtml_file": { + "action_arguments": { + "tags": "FastQC_After_Preprocessing_HTML" + }, + "action_type": "TagDatasetAction", + "output_name": "html_file" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/devteam/fastqc/fastqc/0.74+galaxy0", @@ -901,8 +929,8 @@ } ], "position": { - "left": 1132.9258865960498, - "top": 48.92628195373835 + "left": 1109.933349609375, + "top": 59.936451298881366 }, "post_job_actions": { "RenameDatasetActionmapped": { @@ -933,15 +961,15 @@ "uuid": "f4882cef-bfad-45ca-8274-d5b6b18fa314", "when": null, "workflow_outputs": [ - { - "label": "host_sequences_bam", - "output_name": "mapped", - "uuid": "3b1e626f-6bc1-484c-be01-366534361b73" - }, { "label": "non_host_sequences_bam", "output_name": "unmapped", "uuid": "14a53fe2-f296-43aa-86b7-243278c1050c" + }, + { + "label": "host_sequences_bam", + "output_name": "mapped", + "uuid": "3b1e626f-6bc1-484c-be01-366534361b73" } ] }, @@ -1013,8 +1041,8 @@ } ], "position": { - "left": 1361.5906451294316, - "top": 45.38566689542016 + "left": 1331.5833129882812, + "top": 44.38643298833449 }, "post_job_actions": { "ChangeDatatypeActionoutput": { @@ -1172,8 +1200,8 @@ } ], "position": { - "left": 1488, - "top": 172 + "left": 1516, + "top": 176.0031322070845 }, "post_job_actions": {}, "tool_id": "__FILTER_FAILED_DATASETS__", @@ -1343,8 +1371,8 @@ } ], "position": { - "left": 1709.433349609375, - "top": 28.41668701171875 + "left": 1766.433349609375, + "top": 33.419788701225116 }, "post_job_actions": { "RenameDatasetActionhtml_file": { @@ -1421,8 +1449,8 @@ } ], "position": { - "left": 1896.4151368086827, - "top": 454.89742134783603 + "left": 1897.4166870117188, + "top": 442.90312610356887 }, "post_job_actions": { "RenameDatasetActionoutput_1": { @@ -1431,6 +1459,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "output_1" + }, + "TagDatasetActionoutput_1": { + "action_arguments": { + "tags": "collection_of_preprocessed_samples" + }, + "action_type": "TagDatasetAction", + "output_name": "output_1" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/krakentools_extract_kraken_reads/krakentools_extract_kraken_reads/1.2+galaxy1", @@ -1474,8 +1509,8 @@ } ], "position": { - "left": 1925.4666748046875, - "top": 40.866668701171875 + "left": 1985.4666748046875, + "top": 32.86977039067824 }, "post_job_actions": { "RenameDatasetActionout_file1": { @@ -1521,8 +1556,8 @@ } ], "position": { - "left": 2136.9000244140625, - "top": 50.01666259765625 + "left": 2199.9000244140625, + "top": 38.01979480474074 }, "post_job_actions": {}, "tool_id": "toolshed.g2.bx.psu.edu/repos/nml/collapse_collections/collapse_dataset/5.1.0", @@ -1560,8 +1595,8 @@ } ], "position": { - "left": 2354.113604572875, - "top": 54.17820869704319 + "left": 2434.11669921875, + "top": 40.186451298881366 }, "post_job_actions": { "RenameDatasetActionout_file1": { @@ -1701,6 +1736,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "out_file1" + }, + "TagDatasetActionout_file1": { + "action_arguments": { + "tags": "removed_hosts_percentage_tabular" + }, + "action_type": "TagDatasetAction", + "output_name": "out_file1" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3", @@ -1769,6 +1811,13 @@ }, "action_type": "RenameDatasetAction", "output_name": "stats" + }, + "TagDatasetActionhtml_report": { + "action_arguments": { + "tags": "MultiQC_After_Preprocessing_HTML" + }, + "action_type": "TagDatasetAction", + "output_name": "html_report" } }, "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/multiqc/multiqc/1.11+galaxy1", @@ -1784,15 +1833,15 @@ "uuid": "df53a320-802c-459a-a4cb-fd41aac4af92", "when": null, "workflow_outputs": [ - { - "label": "multiQC_stats_after_preprocessing", - "output_name": "stats", - "uuid": "13cbf6c7-6954-4458-aa66-a5b020c63822" - }, { "label": "multiQC_html_report_after_preprocessing", "output_name": "html_report", "uuid": "0b1b5a73-36ee-42a2-a220-1ced6ec7378b" + }, + { + "label": "multiQC_stats_after_preprocessing", + "output_name": "stats", + "uuid": "13cbf6c7-6954-4458-aa66-a5b020c63822" } ] } @@ -1804,6 +1853,6 @@ "name:Nanopore", "name:IWC" ], - "uuid": "688c0ce8-11ec-4db2-94d9-70bb6a0f31aa", - "version": 176 + "uuid": "188d6f86-3bbf-4dfb-9451-74d8448592e1", + "version": 181 } diff --git a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/pathogen_detection_pathoGFAIR_samples_aggregation_and_visualisation.ga b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/pathogen_detection_pathoGFAIR_samples_aggregation_and_visualisation.ga index b63e22eb78d21b..7003d8a3d923b1 100644 --- a/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/pathogen_detection_pathoGFAIR_samples_aggregation_and_visualisation.ga +++ b/topics/microbiome/tutorials/pathogen-detection-from-nanopore-foodborne-data/workflows/pathogen_detection_pathoGFAIR_samples_aggregation_and_visualisation.ga @@ -5,178 +5,183 @@ { "child_steps": [ 23, - 35, - 68, - 15, - 5, - 29, - 41, - 46, - 50, + 24, + 25, + 30, + 36, + 37, + 42, + 48, 53, - 56, - 59, - 62, + 57, + 60, + 63, + 74, + 18, + 8, + 19, + 9, + 31, + 43, + 49, + 54, + 58, + 61, 64, - 66 + 66, + 68, + 70, + 72 ], "color": "yellow", "data": { - "title": "AMR Phylogenetic tree for all samples" + "title": "VFs Phylogenetic Tree for all samples and Phylogenetic trees for each VF genes across all samples" }, - "id": 4, + "id": 5, "position": [ - 18, - 1783.3000000000002 + 27, + 2195.3 ], "size": [ 4170, - 273.4 + 620 ], "type": "frame" }, { "child_steps": [ - 12, - 13, - 14, - 16, - 17, - 3, - 4, - 6, - 7, - 2 + 44, + 38, + 32, + 26, + 20, + 10, + 0, + 50 ], "color": "yellow", "data": { - "title": "Bar Chart Plots of Tabular outputs" + "title": "AMR Count table" }, - "id": 3, + "id": 0, "position": [ - 1753.7, - 0 + 0, + 966.3 ], "size": [ - 568.3, - 878.4 + 1859.9, + 219.3 ], "type": "frame" }, { "child_steps": [ - 40, 45, - 11, - 1, - 22, - 28, - 34 + 55, + 39, + 33, + 27 ], "color": "yellow", "data": { - "title": "VF count table and heatmap" + "title": "Both VF and AMR count table" }, - "id": 2, + "id": 1, "position": [ - 2, - 1341.4 + 609.7, + 1198.5 ], "size": [ - 1888, - 284.8 + 1438.3, + 199.5 ], "type": "frame" }, { "child_steps": [ - 39, - 49, - 33, - 27, - 21 + 46, + 51, + 21, + 11, + 1, + 28, + 34, + 40 ], "color": "yellow", "data": { - "title": "Both VF and AMR count table" + "title": "VF count table and heatmap" }, - "id": 1, + "id": 2, "position": [ - 596.7, - 1113.5 + 15, + 1426.4 ], "size": [ - 1438.3, - 199.5 + 1888, + 285 ], "type": "frame" }, { "child_steps": [ - 38, - 32, - 26, - 20, - 10, - 0, - 44 + 12, + 13, + 14, + 16, + 17, + 3, + 4, + 6, + 7, + 2 ], "color": "yellow", "data": { - "title": "AMR Count table" + "title": "Bar Chart Plots of Tabular outputs" }, - "id": 0, + "id": 3, "position": [ - 0, - 882.5 + 1833.7, + 0 ], "size": [ - 1660.9, - 209.1 + 642, + 963 ], "type": "frame" }, { "child_steps": [ - 18, - 24, - 25, - 30, - 36, - 37, - 42, + 22, + 35, + 73, + 15, + 5, + 29, + 41, 47, - 51, - 54, - 57, - 60, - 69, - 8, - 19, - 9, - 31, - 43, - 48, 52, - 55, - 58, - 61, - 63, + 56, + 59, + 62, 65, - 67 + 67, + 69, + 71 ], "color": "yellow", "data": { - "title": "VFs Phylogenetic Tree for all samples and Phylogenetic trees for each VF genes across all samples" + "title": "AMR Phylogenetic tree for all samples" }, - "id": 5, + "id": 4, "position": [ - 14, - 2110.3 + 31, + 1868.3000000000002 ], "size": [ 4170, - 620.4 + 273 ], "type": "frame" } @@ -205,7 +210,7 @@ "release": "0.1", "name": "Pathogen Detection PathoGFAIR Samples Aggregation and Visualisation", "report": { - "markdown": "# Pathogen Detection - PathoGFAIR Samples Aggregation and Visualisation workflow Report\nBelow are the results for the PathoGFAIR Samples Aggregation and Visualisation Workflow\n\nThis workflow was run on:\n\n```galaxy\ngenerate_time()\n```\n\nWith Galaxy version:\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Workflow Inputs\nTabular files and a FASTA file from the Gene based Pathogenic Identification workflow, four other tabular files from Nanopore Preprocessing and Nanopore - Allele bases Pathogen Identification workflow, and an optional Metadata tabular file with more sample information:\n\nFrom Gene based Pathogenic Identification workflow: \n- contigs, FASTA file\n- vfs, Tabular file\n- vfs_of_genes_identified_by_vfdb, Tabular file\n- amrs, Tabular file\n- amr_identified_by_ncbi, Tabular file\n\nFrom Nanopore - Allele bases Pathogen Identification workflow: \n- number_of_variants_per_sample, Tabular file\n- mapping_mean_depth_per_sample, Tabular file\n- mapping_coverage_percentage_per_sample, Tabular file\n\nFrom Nanopore Preprocessing: \n- removed_hosts_percentage_tabular, Tabular file\n\n## Some of the Workflow Outputs\n\n1- All Samples VFs Heatmap\n\n```galaxy\nhistory_dataset_as_image(output=\"heatmap_png\")\n```\n\n2- All samples phylogenetic tree VFs based\n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_vfs\")\n```\n\n3- All samples Phylogenetic tree AMR based \n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_amrs\")\n```\n\n4- Barplot for the Number of reads before and after host sequences removal per sample, performed in the Nanopore - Preprocessing workflow\n\n```galaxy\nhistory_dataset_as_image(output=\"number_of_read_before_and_after_host_removal_fig\")\n```\n\n5- Barplot for the total number of removed host sequences per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"removed_host_percentage_fig\")\n```\n \n6- Barplot for the Mapping mean depth per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"mapping_mean_depth_per_sample_fig\")\n```\n\n6- Barplot for the Mapping coverage percentage per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"mapping_coverage_percentage_per_sample_fig\")\n```\n\n7- Barplot for the total number of variants and SNPs identified per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"number_of_Variants_and_SNPs_indentified_fig\")\n```\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n" + "markdown": "# Pathogen Detection - PathoGFAIR Samples Aggregation and Visualisation workflow Report\nBelow are the results for the PathoGFAIR Samples Aggregation and Visualisation Workflow\n\nThis workflow was run on:\n\n```galaxy\ngenerate_time()\n```\n\nWith Galaxy version:\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Workflow Inputs\nTabular files and a FASTA file from the Gene based Pathogenic Identification workflow, four other tabular files from Nanopore Preprocessing and Nanopore - Allele bases Pathogen Identification workflow, and an optional Metadata tabular file with more sample information:\n\nFrom Gene based Pathogenic Identification workflow: \n- contigs, FASTA file\n- vfs, Tabular file\n- vfs_of_genes_identified_by_vfdb, Tabular file\n- amrs, Tabular file\n- amr_identified_by_ncbi, Tabular file\n\nFrom Nanopore - Allele bases Pathogen Identification workflow: \n- number_of_variants_per_sample, Tabular file\n- mapping_mean_depth_per_sample, Tabular file\n- mapping_coverage_percentage_per_sample, Tabular file\n\nFrom Nanopore Preprocessing: \n- removed_hosts_percentage_tabular, Tabular file\n\n## Some of the Workflow Outputs\n\n1- All Samples VFs Heatmap\n\n```galaxy\nhistory_dataset_as_image(output=\"heatmap_png\")\n```\n\n2- All samples phylogenetic tree VFs based\n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_vfs\")\n```\n\n3- All samples Phylogenetic tree AMR based \n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_amrs\")\n```\n\n4- Barplot for the Number of reads before host sequences removal and Number of found host reads per sample, performed in the Nanopore - Preprocessing workflow\n\n```galaxy\nhistory_dataset_as_image(output=\"number_of_reads_before_host_removal_and_number_of_host_reads_found_per_sample_fig\")\n```\n\n5- Barplot for the total number of removed host sequences per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"removed_host_percentage_fig\")\n```\n \n6- Barplot for the Mapping mean depth per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"mapping_mean_depth_per_sample_fig\")\n```\n\n6- Barplot for the Mapping coverage percentage per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"mapping_coverage_percentage_per_sample_fig\")\n```\n\n7- Barplot for the total number of variants and SNPs identified per sample\n\n```galaxy\nhistory_dataset_as_image(output=\"number_of_Variants_and_SNPs_indentified_fig\")\n```\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n" }, "steps": { "0": { @@ -224,8 +229,8 @@ "name": "Input dataset collection", "outputs": [], "position": { - "left": 19.98484848484827, - "top": 962.3448387920441 + "left": 19.98333740234375, + "top": 1006.3443929882739 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", @@ -251,8 +256,8 @@ "name": "Input dataset collection", "outputs": [], "position": { - "left": 21.98484848484827, - "top": 1423.441282170953 + "left": 34.98484848484827, + "top": 1508.441282170953 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", @@ -278,7 +283,7 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 1778.3511974496448, + "left": 1858.3512218637072, "top": 209.99121532505262 }, "tool_id": null, @@ -305,7 +310,7 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 1773.6663567247697, + "left": 1853.666381138832, "top": 289.6725384559728 }, "tool_id": null, @@ -332,7 +337,7 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 1774.0957670982182, + "left": 1854.0957915122806, "top": 419.61832235919906 }, "tool_id": null, @@ -359,8 +364,8 @@ "name": "Input dataset collection", "outputs": [], "position": { - "left": 37.9848484848481, - "top": 1849.2745890557185 + "left": 50.9848484848481, + "top": 1934.2745890557185 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", @@ -386,7 +391,7 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 1776.9262155311626, + "left": 1856.926239945225, "top": 545.6990912189043 }, "tool_id": null, @@ -413,7 +418,7 @@ "name": "Input dataset", "outputs": [], "position": { - "left": 1778.9172871362339, + "left": 1858.9173115502963, "top": 671.3113831546217 }, "tool_id": null, @@ -440,8 +445,8 @@ "name": "Input dataset collection", "outputs": [], "position": { - "left": 873.984848484848, - "top": 2207.307975286187 + "left": 600.9833984375, + "top": 2266.2999877929688 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", @@ -467,8 +472,8 @@ "name": "Input dataset collection", "outputs": [], "position": { - "left": 33.984848484848044, - "top": 2402.3079752861872 + "left": 46.984848484848044, + "top": 2487.3079752861872 }, "tool_id": null, "tool_state": "{\"optional\": false, \"tag\": \"\", \"collection_type\": \"list\"}", @@ -480,7 +485,7 @@ }, "10": { "annotation": "", - "content_id": "Remove beginning1", + "content_id": "__FILTER_FAILED_DATASETS__", "errors": null, "id": 10, "input_connections": { @@ -491,29 +496,29 @@ }, "inputs": [], "label": null, - "name": "Remove beginning", + "name": "Filter failed datasets", "outputs": [ { - "name": "out_file1", + "name": "output", "type": "input" } ], "position": { - "left": 265.31818181818164, - "top": 949.0115054587109 + "left": 241, + "top": 1010 }, "post_job_actions": {}, - "tool_id": "Remove beginning1", - "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"num_lines\": \"1\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_id": "__FILTER_FAILED_DATASETS__", + "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "3f11deed-67b9-48d5-a56d-59203e12ef78", + "uuid": "43b72f45-df6b-487a-94bb-b8c296796a54", "when": null, "workflow_outputs": [] }, "11": { "annotation": "", - "content_id": "Remove beginning1", + "content_id": "__FILTER_FAILED_DATASETS__", "errors": null, "id": 11, "input_connections": { @@ -524,23 +529,23 @@ }, "inputs": [], "label": null, - "name": "Remove beginning", + "name": "Filter failed datasets", "outputs": [ { - "name": "out_file1", + "name": "output", "type": "input" } ], "position": { - "left": 301.98484848484827, - "top": 1417.441282170953 + "left": 249, + "top": 1503 }, "post_job_actions": {}, - "tool_id": "Remove beginning1", - "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"num_lines\": \"1\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_id": "__FILTER_FAILED_DATASETS__", + "tool_state": "{\"input\": {\"__class__\": \"ConnectedValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", - "uuid": "4e7d838b-f28d-419d-99b7-14e81ff93513", + "uuid": "96c9024b-3f8e-4d1d-8467-e467c92a7974", "when": null, "workflow_outputs": [] }, @@ -565,29 +570,36 @@ } ], "position": { - "left": 2088.984799656723, - "top": 40.04289532499695 + "left": 2210.9833374023438, + "top": 53.05000305175781 }, "post_job_actions": { "RenameDatasetActionout_file1": { "action_arguments": { - "newname": "number_of_read_before_and_after_host_removal_fig" + "newname": "number_of_reads_before_host_removal_and_number_of_host_reads_found_per_sample_fig" }, "action_type": "RenameDatasetAction", "output_name": "out_file1" + }, + "TagDatasetActionout_file1": { + "action_arguments": { + "tags": "number_of_reads_before_host_removal_and_number_of_host_reads_found_per_sample_fig" + }, + "action_type": "TagDatasetAction", + "output_name": "out_file1" } }, "tool_id": "barchart_gnuplot", - "tool_state": "{\"colList\": \"2,3\", \"input\": {\"__class__\": \"ConnectedValue\"}, \"pdf_size\": \"800,600\", \"title\": \"Number of Reads Before and After Host Removal\", \"xtic\": {\"userSpecified\": \"Yes\", \"__current_case__\": 0, \"xticColumn\": \"1\"}, \"ylabel\": \"Number of Reads\", \"ymax\": \"0\", \"ymin\": \"0\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", + "tool_state": "{\"colList\": [\"2\", \"3\"], \"input\": {\"__class__\": \"ConnectedValue\"}, \"pdf_size\": \"800,600\", \"title\": \"Number of Reads Before Host Removal and Number of Found Host Reads\", \"xtic\": {\"userSpecified\": \"Yes\", \"__current_case__\": 0, \"xticColumn\": \"1\"}, \"ylabel\": \"Number of Reads\", \"ymax\": \"0\", \"ymin\": \"0\", \"__page__\": null, \"__rerun_remap_job_id__\": null}", "tool_version": "1.0.0", "type": "tool", "uuid": "444ec0b5-dde4-4ac6-b816-72344bf3bd6f", "when": null, "workflow_outputs": [ { - 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