Genome annotation with Maker

genome-annotation-annotation-with-maker/main-workflow

Author(s)
Anthony Bretaudeau, French National Institute for Agriculture, Food, and Environment (INRAE)
version Version
12
last_modification Last updated
Jul 9, 2021
license License
GPL-3.0-or-later
galaxy-tags Tags
genome-annotation

Features

Tutorial
hands_on Genome annotation with Maker

Workflow Testing
Tests: ❌
Results: Not yet automated
FAIRness purl PURL
https://gxy.io/GTN:W00086
RO-Crate logo with flask Download Workflow RO-Crate Workflowhub cloud with gears logo View on WorkflowHub
Launch in Tutorial Mode question
galaxy-download Download
flowchart TD
  0["ℹ️ Input Dataset\nEST and/or cDNA"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nProtein sequences"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\nGenome sequence"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["Maker"];
  0 -->|output| 3;
  2 -->|output| 3;
  1 -->|output| 3;
  4["Fasta Statistics"];
  2 -->|output| 4;
  2d3829e6-f5b9-46d1-83e3-17efff814e09["Output\nFasta Statistics on input dataset(s): Fasta summary stats"];
  4 --> 2d3829e6-f5b9-46d1-83e3-17efff814e09;
  style 2d3829e6-f5b9-46d1-83e3-17efff814e09 stroke:#2c3143,stroke-width:4px;
  5["Busco"];
  2 -->|output| 5;
  a15e1214-23a2-484b-9c75-1635fcd61fe3["Output\nBUSCO: short summary"];
  5 --> a15e1214-23a2-484b-9c75-1635fcd61fe3;
  style a15e1214-23a2-484b-9c75-1635fcd61fe3 stroke:#2c3143,stroke-width:4px;
  7806088d-f657-4389-9d54-6a3bdfa233b2["Output\nBUSCO: list of missing ortholog genes"];
  5 --> 7806088d-f657-4389-9d54-6a3bdfa233b2;
  style 7806088d-f657-4389-9d54-6a3bdfa233b2 stroke:#2c3143,stroke-width:4px;
  6a27d0f6-d83c-42b1-a7af-5f99ba5debe2["Output\nBUSCO: full table"];
  5 --> 6a27d0f6-d83c-42b1-a7af-5f99ba5debe2;
  style 6a27d0f6-d83c-42b1-a7af-5f99ba5debe2 stroke:#2c3143,stroke-width:4px;
  6["Train Augustus"];
  2 -->|output| 6;
  3 -->|output_gff| 6;
  7["Genome annotation statistics"];
  3 -->|output_gff| 7;
  2 -->|output| 7;
  2bed9aa6-5f22-494d-9caa-f0ece8464f15["Output\nGenome annotation statistics: graphs (first round)"];
  7 --> 2bed9aa6-5f22-494d-9caa-f0ece8464f15;
  style 2bed9aa6-5f22-494d-9caa-f0ece8464f15 stroke:#2c3143,stroke-width:4px;
  71d41ce2-e90d-435b-9b64-ab4320524770["Output\nGenome annotation statistics: summary (first round)"];
  7 --> 71d41ce2-e90d-435b-9b64-ab4320524770;
  style 71d41ce2-e90d-435b-9b64-ab4320524770 stroke:#2c3143,stroke-width:4px;
  8["gffread"];
  3 -->|output_gff| 8;
  2 -->|output| 8;
  9["Train SNAP"];
  2 -->|output| 9;
  3 -->|output_gff| 9;
  10["Busco"];
  8 -->|output_exons| 10;
  a79ab19d-9802-42ca-8ffa-8c197a16c8b8["Output\nBusco summary first round"];
  10 --> a79ab19d-9802-42ca-8ffa-8c197a16c8b8;
  style a79ab19d-9802-42ca-8ffa-8c197a16c8b8 stroke:#2c3143,stroke-width:4px;
  11["Maker"];
  6 -->|output_tar| 11;
  9 -->|output| 11;
  2 -->|output| 11;
  3 -->|output_full| 11;
  12["gffread"];
  11 -->|output_gff| 12;
  2 -->|output| 12;
  13["Train Augustus"];
  2 -->|output| 13;
  11 -->|output_gff| 13;
  42d5aadd-3a8c-441d-913f-ee8745a99b0b["Output\nAugus: trained model"];
  13 --> 42d5aadd-3a8c-441d-913f-ee8745a99b0b;
  style 42d5aadd-3a8c-441d-913f-ee8745a99b0b stroke:#2c3143,stroke-width:4px;
  14["Genome annotation statistics"];
  11 -->|output_gff| 14;
  2 -->|output| 14;
  9def2c6e-fd3c-4969-b5d4-d13c187c1144["Output\nGenome annotation statistics: graphs (second round)"];
  14 --> 9def2c6e-fd3c-4969-b5d4-d13c187c1144;
  style 9def2c6e-fd3c-4969-b5d4-d13c187c1144 stroke:#2c3143,stroke-width:4px;
  61f7a150-a4a2-46b1-89f5-2170d466656e["Output\nGenome annotation statistics: summary (second round)"];
  14 --> 61f7a150-a4a2-46b1-89f5-2170d466656e;
  style 61f7a150-a4a2-46b1-89f5-2170d466656e stroke:#2c3143,stroke-width:4px;
  15["Train SNAP"];
  2 -->|output| 15;
  11 -->|output_gff| 15;
  458887f7-0661-4bde-ab1a-875aac6caed8["Output\nSNAP: trained model"];
  15 --> 458887f7-0661-4bde-ab1a-875aac6caed8;
  style 458887f7-0661-4bde-ab1a-875aac6caed8 stroke:#2c3143,stroke-width:4px;
  16["Busco"];
  12 -->|output_exons| 16;
  f52b1b41-0ea5-4384-bd43-4927273c909c["Output\nBusco summary second round"];
  16 --> f52b1b41-0ea5-4384-bd43-4927273c909c;
  style f52b1b41-0ea5-4384-bd43-4927273c909c stroke:#2c3143,stroke-width:4px;
  17["Maker"];
  13 -->|output_tar| 17;
  15 -->|output| 17;
  2 -->|output| 17;
  11 -->|output_full| 17;
  18["Map annotation ids"];
  17 -->|output_gff| 18;
  63575dcf-54d1-4cb1-b5fb-a2810b4da807["Output\nMap annotation ids: renamed GFF"];
  18 --> 63575dcf-54d1-4cb1-b5fb-a2810b4da807;
  style 63575dcf-54d1-4cb1-b5fb-a2810b4da807 stroke:#2c3143,stroke-width:4px;
  19["JBrowse"];
  2 -->|output| 19;
  3 -->|output_gff| 19;
  18 -->|renamed| 19;
  11 -->|output_gff| 19;
  3 -->|output_evidences| 19;
  11 -->|output_evidences| 19;
  17 -->|output_evidences| 19;
  5a38ae83-e177-45f3-aa9f-4c1844584fa5["Output\nJBrowse: report"];
  19 --> 5a38ae83-e177-45f3-aa9f-4c1844584fa5;
  style 5a38ae83-e177-45f3-aa9f-4c1844584fa5 stroke:#2c3143,stroke-width:4px;
  20["gffread"];
  18 -->|renamed| 20;
  2 -->|output| 20;
  52fcac23-b612-4377-a19a-2e3b667a23e3["Output\nGffread: exons"];
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  5c47c25e-0ddb-4ade-a5d0-873ff4add28c["Output\nGffread: translation of cds"];
  20 --> 5c47c25e-0ddb-4ade-a5d0-873ff4add28c;
  style 5c47c25e-0ddb-4ade-a5d0-873ff4add28c stroke:#2c3143,stroke-width:4px;
  84d9183b-9589-464b-9f82-4dae7f87133e["Output\nGffread: cds"];
  20 --> 84d9183b-9589-464b-9f82-4dae7f87133e;
  style 84d9183b-9589-464b-9f82-4dae7f87133e stroke:#2c3143,stroke-width:4px;
  21["Genome annotation statistics"];
  18 -->|renamed| 21;
  2 -->|output| 21;
  f5d4a6bf-1ff8-435a-8084-7921e25bff3a["Output\nGenome annotation statistics: graphs (third round)"];
  21 --> f5d4a6bf-1ff8-435a-8084-7921e25bff3a;
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  5a863bd4-10f2-4ac8-81b6-ce8b7f663e42["Output\nGenome annotation statistics: summary (third round)"];
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  22["Busco"];
  20 -->|output_exons| 22;
  0bc78676-eecc-4168-894d-34c4ca07cdf3["Output\nBusco summary final round"];
  22 --> 0bc78676-eecc-4168-894d-34c4ca07cdf3;
  style 0bc78676-eecc-4168-894d-34c4ca07cdf3 stroke:#2c3143,stroke-width:4px;

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:

Video: Importing a workflow from URL

Version History

Version Commit Time Comments
12 e61e9eba4 2021-07-09 16:50:50 Fix workflow
11 106af0888 2021-07-09 14:57:57 Update maker workflow
10 005d964a2 2021-01-04 09:29:57 fix workflows
9 774f2aa37 2020-12-31 16:14:33 update maker tutorial and add a short version
8 667ff3de9 2020-01-22 10:59:29 annotation
7 eb4d724e0 2020-01-15 10:41:35 Workflow renaming
6 1a3049ca8 2019-05-20 09:14:32 typos + update workflow
5 2318b970d 2019-05-09 15:27:27 udpate workflow
4 361236c41 2019-04-04 09:00:14 Changed format of workflows
3 6eef55b7e 2019-02-27 18:54:36 Updated install_tutorial_requirements.sh + minor fixes (#1275)
2 bc6d0ddca 2018-09-11 12:38:25 jbrowse part
1 7b73f26f8 2018-09-10 15:51:07 update wf

For Admins

Installing the workflow tools

wget https://training.galaxyproject.org/training-material/topics/genome-annotation/tutorials/annotation-with-maker/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