Gigascience_Indels_SAV_non-normal_demonstration_STS26T-Gent_Workflow
proteomics-neoantigen-2-non-normal-database-generation/main-workflow
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flowchart TD 0["ℹ️ Input Dataset\nHomo_sapiens.GRCh38_canon.106.gtf"]; style 0 stroke:#2c3143,stroke-width:4px; 1["ℹ️ Input Dataset\nRNA-Seq_Reads_2.fastq"]; style 1 stroke:#2c3143,stroke-width:4px; 2["ℹ️ Input Dataset\nRNA-Seq_Reads_1.fastq"]; style 2 stroke:#2c3143,stroke-width:4px; 3["ℹ️ Input Dataset\nHUMAN-Uniprot-and-isoforms_and_cRAP-FASTA-Database"]; style 3 stroke:#2c3143,stroke-width:4px; 4["Uncompressed_RNA_Seq_Reads_2"]; 1 -->|output| 4; 5983317a-db25-4f0f-8a0b-290d15aafd14["Output\nUncompressed_RNA_Seq_Reads_2"]; 4 --> 5983317a-db25-4f0f-8a0b-290d15aafd14; style 5983317a-db25-4f0f-8a0b-290d15aafd14 stroke:#2c3143,stroke-width:4px; 5["Uncompressed_RNA_Seq_Reads_1"]; 2 -->|output| 5; d6f2044c-cd3b-4fde-901a-2c6c7db5db4f["Output\nUncompressed_RNA_Seq_Reads_1"]; 5 --> d6f2044c-cd3b-4fde-901a-2c6c7db5db4f; style d6f2044c-cd3b-4fde-901a-2c6c7db5db4f stroke:#2c3143,stroke-width:4px; 6["Convert_HUMAN_Uniprot_and_CRAP_FASTA_to_tabular"]; 3 -->|output| 6; 067e8f48-59d2-4f9c-bce9-13d1dca9d74e["Output\nHUMAN_Uniprot_and_CRAP.tabular"]; 6 --> 067e8f48-59d2-4f9c-bce9-13d1dca9d74e; style 067e8f48-59d2-4f9c-bce9-13d1dca9d74e stroke:#2c3143,stroke-width:4px; 7["HISAT2_Alignment_BAM"]; 5 -->|output1| 7; 4 -->|output1| 7; 0137dcb5-9d02-427f-82da-995723a93c85["Output\nHISAT2_Alignment_BAM"]; 7 --> 0137dcb5-9d02-427f-82da-995723a93c85; style 0137dcb5-9d02-427f-82da-995723a93c85 stroke:#2c3143,stroke-width:4px; 8["Filtering_HUMAN_Uniprot_and_cRAP_Accessions_tabular"]; 6 -->|output| 8; 4a2dbdd0-8e12-418c-a8f9-38256a760be8["Output\nFiltering_HUMAN_Uniprot_and_cRAP_Accessions_tabular"]; 8 --> 4a2dbdd0-8e12-418c-a8f9-38256a760be8; style 4a2dbdd0-8e12-418c-a8f9-38256a760be8 stroke:#2c3143,stroke-width:4px; 9["StringTie_Alignment_GTF"]; 0 -->|output| 9; 7 -->|output_alignments| 9; a4ff5eba-c73a-424b-8a9e-cfe76a0fe77f["Output\nStringTie_Alignment_GTF"]; 9 --> a4ff5eba-c73a-424b-8a9e-cfe76a0fe77f; style a4ff5eba-c73a-424b-8a9e-cfe76a0fe77f stroke:#2c3143,stroke-width:4px; 10["FreeBayes_variants_VCF"]; 7 -->|output_alignments| 10; b4ebb058-327d-4284-b96e-f7491262912e["Output\nFreeBayes_variants_VCF"]; 10 --> b4ebb058-327d-4284-b96e-f7491262912e; style b4ebb058-327d-4284-b96e-f7491262912e stroke:#2c3143,stroke-width:4px; 11["GffCompare_Annotated_Transcripts_GTF"]; 0 -->|output| 11; 9 -->|output_gtf| 11; 72c73a0b-6677-4701-ab52-4d296c553df9["Output\nGffCompare_Annotated_Transcripts_GTF"]; 11 --> 72c73a0b-6677-4701-ab52-4d296c553df9; style 72c73a0b-6677-4701-ab52-4d296c553df9 stroke:#2c3143,stroke-width:4px; 12["CustomProDB_protein_FASTAs_from_BAM_and_VCF"]; 7 -->|output_alignments| 12; 10 -->|output_vcf| 12; 8ce883fd-1961-47f6-b7b0-8153b7d1b4be["Output\nCustomProDB_INDEL_FASTA"]; 12 --> 8ce883fd-1961-47f6-b7b0-8153b7d1b4be; style 8ce883fd-1961-47f6-b7b0-8153b7d1b4be stroke:#2c3143,stroke-width:4px; b31fbd26-fec0-42d9-a079-a28ae64ec009["Output\nCustomProDB_VARIANT_ANNOTATION_RDATA"]; 12 --> b31fbd26-fec0-42d9-a079-a28ae64ec009; style b31fbd26-fec0-42d9-a079-a28ae64ec009 stroke:#2c3143,stroke-width:4px; b7944440-cbca-4fb5-96fd-03e952854728["Output\nCustomProDB_Genomic_SQLlite"]; 12 --> b7944440-cbca-4fb5-96fd-03e952854728; style b7944440-cbca-4fb5-96fd-03e952854728 stroke:#2c3143,stroke-width:4px; 9cee39b1-2766-43b0-b002-697e496a11d7["Output\nCustomProDB_VARIANT_ANNOTATION_SQLite"]; 12 --> 9cee39b1-2766-43b0-b002-697e496a11d7; style 9cee39b1-2766-43b0-b002-697e496a11d7 stroke:#2c3143,stroke-width:4px; 8258d64c-c755-4b49-b417-32ea722773bd["Output\nCustomProDB_RPKM_FASTA"]; 12 --> 8258d64c-c755-4b49-b417-32ea722773bd; style 8258d64c-c755-4b49-b417-32ea722773bd stroke:#2c3143,stroke-width:4px; 9ce1b014-b001-4ed8-9144-5890bb8cdbd5["Output\nCustomProDB_SNV_FASTA"]; 12 --> 9ce1b014-b001-4ed8-9144-5890bb8cdbd5; style 9ce1b014-b001-4ed8-9144-5890bb8cdbd5 stroke:#2c3143,stroke-width:4px; 13["GffCompare_Annotated_GTF_to_BED"]; 11 -->|transcripts_annotated| 13; 751c3898-45a0-4836-bd33-44affbe9748a["Output\nGffCompare_Annotated_GTF_to_BED"]; 13 --> 751c3898-45a0-4836-bd33-44affbe9748a; style 751c3898-45a0-4836-bd33-44affbe9748a stroke:#2c3143,stroke-width:4px; 14["Convert_INDEL_FASTA_to_tabular"]; 12 -->|output_indel| 14; dc1bb9c3-0f77-4f30-a0ea-d164563269d8["Output\nCustomProDB_INDEL.tabular"]; 14 --> dc1bb9c3-0f77-4f30-a0ea-d164563269d8; style dc1bb9c3-0f77-4f30-a0ea-d164563269d8 stroke:#2c3143,stroke-width:4px; 15["Convert-SNV_FASTA_to_tabular"]; 12 -->|output_snv| 15; 0d8682f5-66fa-40db-b280-d6f1bb4a5717["Output\nCustomProDB_SNV.tabular"]; 15 --> 0d8682f5-66fa-40db-b280-d6f1bb4a5717; style 0d8682f5-66fa-40db-b280-d6f1bb4a5717 stroke:#2c3143,stroke-width:4px; 16["Convert-RPKM_FASTA_to_tabular"]; 12 -->|output_rpkm| 16; 88cfd137-3b8e-4c69-b38a-0b9ea8fea7fc["Output\nCustomProDB_RPKM.tabular"]; 16 --> 88cfd137-3b8e-4c69-b38a-0b9ea8fea7fc; style 88cfd137-3b8e-4c69-b38a-0b9ea8fea7fc stroke:#2c3143,stroke-width:4px; 17["Converting_Genomic_SQLite_to_database_mode"]; 12 -->|output_genomic_mapping_sqlite| 17; 91eaaad0-e93e-434b-b87c-2de0f9c232ef["Output\nConvert_Genomic_SQLite_to_tabular"]; 17 --> 91eaaad0-e93e-434b-b87c-2de0f9c232ef; style 91eaaad0-e93e-434b-b87c-2de0f9c232ef stroke:#2c3143,stroke-width:4px; 18["Converting_CustomProDB_FASTA_to_tabular"]; 12 -->|output_rpkm| 18; 6bcf6e52-85a8-439e-83cc-50de2cc8749d["Output\nCustomProDB_FASTA_to_tabular"]; 18 --> 6bcf6e52-85a8-439e-83cc-50de2cc8749d; style 6bcf6e52-85a8-439e-83cc-50de2cc8749d stroke:#2c3143,stroke-width:4px; 19["Converting_Variant_SQLite_to_database_mode"]; 12 -->|output_variant_annotation_sqlite| 19; 7698d1f1-7979-4deb-9ac2-0f1541d905ce["Output\nConvert_Variant_SQLite_to_tabular"]; 19 --> 7698d1f1-7979-4deb-9ac2-0f1541d905ce; style 7698d1f1-7979-4deb-9ac2-0f1541d905ce stroke:#2c3143,stroke-width:4px; 20["Translate_BED_Transcripts"]; 13 -->|output| 20; 9510c804-d13e-4cd6-b08e-1c670623e296["Output\nTranslation_FASTA"]; 20 --> 9510c804-d13e-4cd6-b08e-1c670623e296; style 9510c804-d13e-4cd6-b08e-1c670623e296 stroke:#2c3143,stroke-width:4px; 4ebcd87a-1526-4c05-914d-6051b996201d["Output\nTranslate_BED_Transcripts"]; 20 --> 4ebcd87a-1526-4c05-914d-6051b996201d; style 4ebcd87a-1526-4c05-914d-6051b996201d stroke:#2c3143,stroke-width:4px; 21["Annotating-INDEL"]; 14 -->|output| 21; aff83bc0-c7af-4257-a51c-93dfe90ae6c0["Output\nAnnotating-INDEL"]; 21 --> aff83bc0-c7af-4257-a51c-93dfe90ae6c0; style aff83bc0-c7af-4257-a51c-93dfe90ae6c0 stroke:#2c3143,stroke-width:4px; 22["Annotating-SNV"]; 15 -->|output| 22; 960e7c54-1a91-4b92-b75c-0da23fe1650a["Output\nAnnotating-SNV"]; 22 --> 960e7c54-1a91-4b92-b75c-0da23fe1650a; style 960e7c54-1a91-4b92-b75c-0da23fe1650a stroke:#2c3143,stroke-width:4px; 23["Annotating-RPKM"]; 16 -->|output| 23; ef203c53-9e5b-4120-a508-a0dcbbfaec3b["Output\nAnnotating-RPKM"]; 23 --> ef203c53-9e5b-4120-a508-a0dcbbfaec3b; style ef203c53-9e5b-4120-a508-a0dcbbfaec3b stroke:#2c3143,stroke-width:4px; 24["Annotating_Genomic_SQLite"]; 17 -->|query_results| 24; 045776fe-4fc9-4da1-b808-4ab674dcced4["Output\nAnnotating_Genomic_SQLite"]; 24 --> 045776fe-4fc9-4da1-b808-4ab674dcced4; style 045776fe-4fc9-4da1-b808-4ab674dcced4 stroke:#2c3143,stroke-width:4px; 25["Filtering_RPKM_accessions"]; 18 -->|output| 25; d23ae9b0-374f-4668-831c-c08217161834["Output\nFiltering_RPKM_accessions"]; 25 --> d23ae9b0-374f-4668-831c-c08217161834; style d23ae9b0-374f-4668-831c-c08217161834 stroke:#2c3143,stroke-width:4px; 26["Annotating_Variant_SQLite"]; 19 -->|query_results| 26; 0238c405-dbcb-40a0-b9ce-6bc091cc01c5["Output\nAnnotating_Variant_SQLite"]; 26 --> 0238c405-dbcb-40a0-b9ce-6bc091cc01c5; style 0238c405-dbcb-40a0-b9ce-6bc091cc01c5 stroke:#2c3143,stroke-width:4px; 27["Convert_Translation_BED_to_tabular_for_protein_map"]; 20 -->|translation_bed| 27; 873fc597-ac53-4dfa-8f5a-d5532af8886c["Output\nTranslation_tabular_for_protein_map"]; 27 --> 873fc597-ac53-4dfa-8f5a-d5532af8886c; style 873fc597-ac53-4dfa-8f5a-d5532af8886c stroke:#2c3143,stroke-width:4px; 28["Converting_Annotated_Indel_to_FASTA"]; 21 -->|out_file1| 28; ae642819-14c2-46d9-a31f-0b142c074a8c["Output\nConverting_Annotated_Indel_to_FASTA"]; 28 --> ae642819-14c2-46d9-a31f-0b142c074a8c; style ae642819-14c2-46d9-a31f-0b142c074a8c stroke:#2c3143,stroke-width:4px; 29["Converting_Annotated_SNV_to_FASTA"]; 22 -->|out_file1| 29; 49e24e6a-ae3e-463c-915b-65f895a471e4["Output\nConverting_Annotated_SNV_to_FASTA"]; 29 --> 49e24e6a-ae3e-463c-915b-65f895a471e4; style 49e24e6a-ae3e-463c-915b-65f895a471e4 stroke:#2c3143,stroke-width:4px; 30["Converting_Annotated_RPKM_to_FASTA"]; 23 -->|out_file1| 30; 0969ba6f-4bd8-4464-94cc-c990cf395507["Output\nConverting_Annotated_RPKM_to_FASTA"]; 30 --> 0969ba6f-4bd8-4464-94cc-c990cf395507; style 0969ba6f-4bd8-4464-94cc-c990cf395507 stroke:#2c3143,stroke-width:4px; 31["Concatenate_HUMAN_Crap_protein-accessions"]; 8 -->|output| 31; 25 -->|output| 31; e3f2a023-888a-4d80-b16c-ea87adbc6588["Output\nConcatenate_HUMAN_Crap_protein-accessions"]; 31 --> e3f2a023-888a-4d80-b16c-ea87adbc6588; style e3f2a023-888a-4d80-b16c-ea87adbc6588 stroke:#2c3143,stroke-width:4px; 32["Variant_input_for_MVP"]; 26 -->|out_file1| 32; ef638bf1-2cd7-4c4f-acc7-0fc5ce771756["Output\nVariant_input_for_MVP"]; 32 --> ef638bf1-2cd7-4c4f-acc7-0fc5ce771756; style ef638bf1-2cd7-4c4f-acc7-0fc5ce771756 stroke:#2c3143,stroke-width:4px; 33["Concatenate_databases_from_Genomic_SQlite_and_translation_BED_file"]; 24 -->|out_file1| 33; 27 -->|output| 33; 77671f49-26c7-4eeb-b38c-62f09933e99b["Output\nConcatenate_databases_from_Genomic_SQlite_and_translation_BED_file"]; 33 --> 77671f49-26c7-4eeb-b38c-62f09933e99b; style 77671f49-26c7-4eeb-b38c-62f09933e99b stroke:#2c3143,stroke-width:4px; 34["Merge_Indel_SNV_RPKM_to_make_Non_normal_CustomProDB_FASTA"]; 30 -->|output| 34; 29 -->|output| 34; 28 -->|output| 34; 81e3ae85-7111-4517-a9fe-64f245654ad4["Output\nNon-normal_CustomProDB_FASTA"]; 34 --> 81e3ae85-7111-4517-a9fe-64f245654ad4; style 81e3ae85-7111-4517-a9fe-64f245654ad4 stroke:#2c3143,stroke-width:4px; 35["Genomic_input_for_MVP"]; 33 -->|out_file1| 35; d72ce75b-6ee3-4bcb-b829-f3c85b3c5a65["Output\nGenomic_input_for_MVP"]; 35 --> d72ce75b-6ee3-4bcb-b829-f3c85b3c5a65; style d72ce75b-6ee3-4bcb-b829-f3c85b3c5a65 stroke:#2c3143,stroke-width:4px; 36["Human_cRAP_Non_normal_transcripts_dB generation"]; 3 -->|output| 36; 34 -->|output| 36; 20 -->|translation_fasta| 36; 400380de-2047-4c30-a9e4-320a19489be4["Output\nHuman_cRAP_Non_normal_transcripts_dB generation"]; 36 --> 400380de-2047-4c30-a9e4-320a19489be4; style 400380de-2047-4c30-a9e4-320a19489be4 stroke:#2c3143,stroke-width:4px;
Inputs
Input | Label |
---|---|
Input dataset | Homo_sapiens.GRCh38_canon.106.gtf |
Input dataset | RNA-Seq_Reads_2.fastq |
Input dataset | RNA-Seq_Reads_1.fastq |
Input dataset | HUMAN-Uniprot-and-isoforms_and_cRAP-FASTA-Database |
Outputs
From | Output | Label |
---|---|---|
CONVERTER_gz_to_uncompressed | Convert compressed file to uncompressed. | Uncompressed_RNA_Seq_Reads_2 |
CONVERTER_gz_to_uncompressed | Convert compressed file to uncompressed. | Uncompressed_RNA_Seq_Reads_1 |
toolshed.g2.bx.psu.edu/repos/devteam/fasta_to_tabular/fasta2tab/1.1.1 | FASTA-to-Tabular | Convert_HUMAN_Uniprot_and_CRAP_FASTA_to_tabular |
toolshed.g2.bx.psu.edu/repos/iuc/hisat2/hisat2/2.2.1+galaxy1 | HISAT2 | HISAT2_Alignment_BAM |
toolshed.g2.bx.psu.edu/repos/iuc/filter_tabular/filter_tabular/3.3.1 | Filter Tabular | Filtering_HUMAN_Uniprot_and_cRAP_Accessions_tabular |
toolshed.g2.bx.psu.edu/repos/iuc/stringtie/stringtie/2.2.3+galaxy0 | StringTie | StringTie_Alignment_GTF |
toolshed.g2.bx.psu.edu/repos/devteam/freebayes/freebayes/1.3.6+galaxy0 | FreeBayes | FreeBayes_variants_VCF |
toolshed.g2.bx.psu.edu/repos/iuc/gffcompare/gffcompare/0.12.6+galaxy0 | GffCompare | GffCompare_Annotated_Transcripts_GTF |
toolshed.g2.bx.psu.edu/repos/galaxyp/custom_pro_db/custom_pro_db/1.22.0 | CustomProDB | CustomProDB_protein_FASTAs_from_BAM_and_VCF |
toolshed.g2.bx.psu.edu/repos/galaxyp/gffcompare_to_bed/gffcompare_to_bed/0.2.1 | Convert gffCompare annotated GTF to BED | GffCompare_Annotated_GTF_to_BED |
toolshed.g2.bx.psu.edu/repos/devteam/fasta_to_tabular/fasta2tab/1.1.1 | FASTA-to-Tabular | Convert_INDEL_FASTA_to_tabular |
toolshed.g2.bx.psu.edu/repos/devteam/fasta_to_tabular/fasta2tab/1.1.1 | FASTA-to-Tabular | Convert-SNV_FASTA_to_tabular |
toolshed.g2.bx.psu.edu/repos/devteam/fasta_to_tabular/fasta2tab/1.1.1 | FASTA-to-Tabular | Convert-RPKM_FASTA_to_tabular |
toolshed.g2.bx.psu.edu/repos/iuc/sqlite_to_tabular/sqlite_to_tabular/2.0.0 | SQLite to tabular | Converting_Genomic_SQLite_to_database_mode |
toolshed.g2.bx.psu.edu/repos/devteam/fasta_to_tabular/fasta2tab/1.1.1 | FASTA-to-Tabular | Converting_CustomProDB_FASTA_to_tabular |
toolshed.g2.bx.psu.edu/repos/iuc/sqlite_to_tabular/sqlite_to_tabular/2.0.0 | SQLite to tabular | Converting_Variant_SQLite_to_database_mode |
toolshed.g2.bx.psu.edu/repos/galaxyp/translate_bed/translate_bed/0.1.0 | Translate BED transcripts | Translate_BED_Transcripts |
toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3 | Column Regex Find And Replace | Annotating-INDEL |
toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3 | Column Regex Find And Replace | Annotating-SNV |
toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3 | Column Regex Find And Replace | Annotating-RPKM |
toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3 | Column Regex Find And Replace | Annotating_Genomic_SQLite |
toolshed.g2.bx.psu.edu/repos/iuc/filter_tabular/filter_tabular/3.3.1 | Filter Tabular | Filtering_RPKM_accessions |
toolshed.g2.bx.psu.edu/repos/galaxyp/regex_find_replace/regexColumn1/1.0.3 | Column Regex Find And Replace | Annotating_Variant_SQLite |
toolshed.g2.bx.psu.edu/repos/galaxyp/bed_to_protein_map/bed_to_protein_map/0.2.0 | bed to protein map | Convert_Translation_BED_to_tabular_for_protein_map |
toolshed.g2.bx.psu.edu/repos/devteam/tabular_to_fasta/tab2fasta/1.1.1 | Tabular-to-FASTA | Converting_Annotated_Indel_to_FASTA |
toolshed.g2.bx.psu.edu/repos/devteam/tabular_to_fasta/tab2fasta/1.1.1 | Tabular-to-FASTA | Converting_Annotated_SNV_to_FASTA |
toolshed.g2.bx.psu.edu/repos/devteam/tabular_to_fasta/tab2fasta/1.1.1 | Tabular-to-FASTA | Converting_Annotated_RPKM_to_FASTA |
toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1 | Concatenate datasets | Concatenate_HUMAN_Crap_protein-accessions |
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | Variant_input_for_MVP |
toolshed.g2.bx.psu.edu/repos/bgruening/text_processing/tp_cat/9.3+galaxy1 | Concatenate datasets | Concatenate_databases_from_Genomic_SQlite_and_translation_BED_file |
toolshed.g2.bx.psu.edu/repos/galaxyp/fasta_merge_files_and_filter_unique_sequences/fasta_merge_files_and_filter_unique_sequences/1.2.0 | FASTA Merge Files and Filter Unique Sequences | Merge_Indel_SNV_RPKM_to_make_Non_normal_CustomProDB_FASTA |
toolshed.g2.bx.psu.edu/repos/iuc/query_tabular/query_tabular/3.3.2 | Query Tabular | Genomic_input_for_MVP |
toolshed.g2.bx.psu.edu/repos/galaxyp/fasta_merge_files_and_filter_unique_sequences/fasta_merge_files_and_filter_unique_sequences/1.2.0 | FASTA Merge Files and Filter Unique Sequences | Human_cRAP_Non_normal_transcripts_dB generation |
Tools
To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.
Importing into Galaxy
Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!Hands-on: Importing a workflow
- Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
- Click on galaxy-upload Import at the top-right of the screen
- Provide your workflow
- Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
- Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
- Click the Import workflow button
Below is a short video demonstrating how to import a workflow from GitHub using this procedure:
Version History
Version | Commit | Time | Comments |
---|---|---|---|
1 | 6e4ce4916 | 2024-11-14 15:41:21 | Made sure the order is right |
For Admins
Installing the workflow tools
wget https://training.galaxyproject.org/training-material/topics/proteomics/tutorials/neoantigen-2-non-normal-database-generation/workflows/main_workflow.ga -O workflow.ga workflow-to-tools -w workflow.ga -o tools.yaml shed-tools install -g GALAXY -a API_KEY -t tools.yaml workflow-install -g GALAXY -a API_KEY -w workflow.ga --publish-workflows