# Research Object Crate for Gene Expression Analysis Workflow in Complex Microbiomes

Original URL: https://workflowhub.eu/workflows/1955/ro_crate?version=1

![GitHub last commit (branch)](https://img.shields.io/github/last-commit/RyoMameda/workflow_cwl/main) ![Status](https://img.shields.io/badge/status-development-yellow) [![cwltool](https://img.shields.io/badge/cwltool-3.1.20250110105449-success)](https://github.com/common-workflow-language/cwltool/releases/tag/3.1.20250110105449) [![License](https://img.shields.io/badge/License-MIT-blue.svg)](./LICENSE) [![Version](https://img.shields.io/badge/version-1.0-brightgreen)](https://github.com/RyoMameda/ComplexMicrobiome_GeneExpression_CWL/releases/tag/v1.0) [![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=python3.11&color=blue&logo=docker)](https://github.com/yonesora56/plant2human/tree/main/.devcontainer) # Gene Expression Analysis Workflow in Complex Microbiomes ## Workflow Schema - more details: [Optimization of Mapping Tools and Investigation of Ribosomal RNA Influence for Data-Driven Gene Expression Analysis in Complex Microbiomes](https://doi.org/10.3390/microorganisms13050995) ![image](./image/microorganisms-13-00995-g001.png) ### 1. Overview of the Workflow This analysis focuses on transcriptional profiling of complex microbiomes. It requires both metagenomic and metatranscriptomic NGS short-read data, along with annotation reference information (e.g., ribosomal RNA sequences and referenced protein databases, listed below). The metagenomic and metatranscriptomic reads should be derived from the same microbiome samples. Assembled metagenomic contigs are then used as reference sequences to map both types of reads, enabling gene-level quantification. ### 2. Minimum Requirements - `Docker` - `cwltool` ### 3. Workflow Component This analysis workflow is composed of three sub-workflows; metagenomic contig assembling, reads mapping and annotation. #### Metagenomic contig assembling In this process, the following steps are performed: 1. Assembly process using `Megahit`. 2. Prediction Protein sequences using `Prodigal`. 3. Statical analysis of contigs useing `SeqKit`. #### Reads mapping In this process, the following steps are performed: 1. Mapping process using `BWA MEM`. 2. Statical analysis of mapping results using `SAMtools` #### Annotation In this process, the following steps are performed: 1. Searching contaminated ribosomal RNA sequences using `BLAST`. 2. Searching referenced proteins using `DIAMOND`. 3. Creation GTF formated file contained annotation informations. ### 4. Test Dataset and Your Own Dataset - If you are testing with the following files, please place them in the `Data` directory! - You can also obtain metagenomic and metatranscriptomic FASTQ files either by downloading them from public databases or by using your own samples, and then place them in your `Data` directory. #### Metagenome data - [SRR27548858](https://www.ncbi.nlm.nih.gov/sra/?term=SRR27548858) #### Metatranscriptome data - [SRR27548863](https://www.ncbi.nlm.nih.gov/sra/?term=SRR27548863) - [SRR27548864](https://www.ncbi.nlm.nih.gov/sra/?term=SRR27548864) - [SRR27548865](https://www.ncbi.nlm.nih.gov/sra/?term=SRR27548865) ### 5. Annotation References These reference files are used in the BLAST and DIAMOND processes. The downloaded files are available in the `Data` directory (accessed on September 17, 2025). If you wish to use the latest versions of the references, please download them using the following scripts. ```bash # rRNA data from SILVA website (release138.1; accessed on 17,September,2025) curl -O https://ftp.arb-silva.de/release_138.1/Exports/SILVA_138.1_LSUParc_tax_silva.fasta.gz curl -O https://ftp.arb-silva.de/release_138.1/Exports/SILVA_138.1_SSUParc_tax_silva.fasta.gz # Swiss-Prot data from UniProt for diamond makedb process (accessed on 17,September,2025) curl -O https://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz # Pfam data from InterPro (accessed on 17,September,2025)) for hmmscan proess. Appling HMMER process in this workflow is on going, however this process takes time. This step will be optional. # curl -O https://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz ``` ### 6. Command Execution We recommend creating a `cache` directory to store cache and intermediate files. Since metagenomic and metatranscriptomic reads are mapped to contigs, the assembled results can be reused to reduce analytical costs. The `cwltool` properly recognizes caches when the `--cachedir` option is specified. ```bash # main workflow cwltool --debug --cachedir --outdir ./Worlkflow/main_w.cwl ./config/main_w.yml ``` ### 7. based shell script & python script GitHub: https://github.com/RyoMameda/workflow This workflow is developed at [DBCLS BioHackathon 2025](https://github.com/dbcls/bh25/), and the preprint of developing project is https://doi.org/10.37044/osf.io/qd5sz_v1.

Author
  Ryo Mameda, Sora Yonezawa
License
  MIT

## Contents

Main Workflow: Gene Expression Analysis Workflow in Complex Microbiomes
Size: 4342 bytes
Main Workflow Diagram: workflow-1955-95a536b953f51f802b0c80729fefc1cb765d10f1-diagram.svg
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