Introduction
This recipe provides a standardized and reproducible workflow to analyze high-throughput biological data and transform raw files into interpretable results.
It is designed to answer questions such as:
- What biological changes are present between samples or conditions?
- Which features (genes, variants, regions) are significantly affected?
Data
Describe the input data (e.g., bulk RNA-seq, WGS, scRNA-seq) and starting format (e.g., FASTQ, count matrices).
Methods & Tools
Briefly describe the main processing steps and tools used (e.g., QC, alignment, quantification, statistics, Nextflow, nf-core).
Target Audience
State who this recipe is for (e.g., bioinformaticians, lab scientists, data analysts) and the required skill level.
Purpose
Explain why this recipe is useful (e.g., reproducibility, automation, standardized analysis).
Input Data Overview
Briefly describe the structure and type of input data required for this recipe.
Required Files
-
Raw reads (
.fastq.gz)
Primary sequencing reads -
Sample metadata (
.csv)
Sample IDs and experimental conditions -
Reference genome (
.fa)
Genome sequence for alignment -
Gene annotation (
.gtf)
Gene models for quantification
Input Directory Structure (optional)
project/
data/
sample1_R1.fastq.gz
sample1_R2.fastq.gz
metadata/
samples.csv
reference/
genome.fa
genes.gtf
(Optional) Input figure or screenshot showing the data layout.
Tutorial
Step-by-step guide to run the recipe.
1. Prepare the Environment
Describe how to access the platform, workspace, or compute environment
(e.g., login, project setup, permissions).
2. Configure Parameters (optional)
Describe which parameters must be defined and where they are configured
(e.g., config file, UI form, environment variables).
<parameter_name>: <value>
<parameter_name>: <value>
3. Run the Workflow
Describe how the workflow is started (e.g., command-line, web interface, job submission button).
<command or action to start the workflow>
4. Monitor & Troubleshoot
Explain how users can:
- Track job status
- Access logs and reports
- Resume or restart failed runs
Result Data Overview
Explain what the outputs are and how to find them.
Key Outputs
| Output | Location | Description |
| --------- | ----------------------------- | --------------- |
| Report | results/multiqc_report.html | QC summary |
| Counts | results/counts.tsv | Raw gene counts |
| BAM files | results/bams/ | Aligned reads |
Output Tree (optional)
results/
bams/
counts.tsv
multiqc_report.html
Example Figure
Final Analysis & Interpretation
Describe what users should look for in the results.
- What does a successful run look like?
- How should users interpret findings?
- Common next steps (e.g., DEG analysis, enrichment)
References & Resources
- Pipeline documentation
- Relevant paper or method
- THOA support: hello@thoa.io