SERtool User Guide
This tool analyzes enriched regions in biological sequences, supporting multiple input formats and analysis modes.
1. Run SERtool
To preview the output format, click the blue Example Result button. The example page shows downloadable files and a link redirecting to STRING for functional enrichment analysis of detected regions.
1.1 Quick Run: Analyze in 2 Steps
No need to adjust advanced settings, get started instantly.
- Input Pattern: Input the amino acid sequence to search.
- Click "Analyze Sequence": The tool will automatically use optimized default settings (Homo sapiens, Fixed Mode with point 1(18,20), point 2 (30,50)) to scan and detect enriched regions.
1.2 Advanced Settings
Fixed mode is faster than formula mode in some conditions because it only calculates one or two fixed points. (X = not required).
| Condition | Example | Start | End | Step | Mode | Point | Note |
|---|---|---|---|---|---|---|---|
| Single Class Amino Acid Enrichment | D-E | 20 | 100 | 1 | Formula | (18,20)(30,50) | DDDDEEEEEE |
| Fixed Sequence Enrichment | DE | 20 | 100 | 1 | Formula | (9,20)(15,50) | DEDEDEDEDE |
| Wildcard Containing Enrichment | H.K | 20 | 100 | 1 | Formula | (4,20)(8,50) | HTKHSK |
| Continuous Sequence Enrichment | R | X | X | 1 | Fixed | (9,9) | RRRRRRRRR |
| Motif Sequence | KDEL | X | X | 1 | Fixed | (1,4) | KDEL |
| Score = 10 | E | 20 | 100 | 1 | Score | Built-in defaults | EEEEEEEEEEDE... |
| Proportion = 0.7 | E | 20 | 100 | 1 | Proportion | Built-in defaults | EEEDEDEDEE... |
2. Web Interface Design
SERtool employs a frontend-backend decoupled architecture with Redis-based task queuing. User requests are submitted to the frontend server, which asynchronously dispatches computational tasks to dedicated backend processing servers via Redis and relays the results back to the end user upon completion. When the search target is the FS dataset, an email can be automatically sent to the specified email address upon completion (optional).
The workflow of SERtool and provides a detailed example page for reference.
2.1 Query Interface
The query interface features a concise input panel with the following key components:
- Pattern input: Supports several search tasks, including equivalent-residue, wildcard, and fixed-motif searches.
- Sequence input: Commonly used sequences are built into the tool, with human sequences pre-selected by default. Users can paste FASTA sequences, upload sequence files, or select an organism from the built-in list for analysis.
- Start window: Defines the smallest window size.
- End window: Defines the largest window size.
- Step: The window step size, defaulting to 1 for maximum resolution.
- Search modes: Four modes are available, including Fixed mode, Formula mode, Score mode, and Proportion mode.
- Analyze button: Click to start the analysis.
2.2 Results Output Page
After submission, the server generates a unique job ID for each query. Results are presented on a dedicated output page, which displays:
- Download path: Directory link for retrieving result files.
- Submit to STRING: Enables users to explore protein-protein interaction networks, GO enrichment, and KEGG pathway mapping.
- Full sequence: The complete protein or genomic sequence submitted for analysis.
- Window sequences: All subsequences that satisfy the user-defined pattern and constraint criteria.
- Optimal SER: The highest-scoring segment identified by the linear constraint model.
2.3 Dedicated Mutation Search Interface
To maximize the utility of the mutation dataset, we have developed a dedicated search interface. Users can:
- Query mutant sequences for a specific gene.
- View both the mutant sequence and its corresponding wild-type counterpart dynamically.
- See nucleotide-level differences visually highlighted in red (mutant) and green (wild-type).
- Download the aligned sequence pair with difference annotations.
- Find source and ID information in the FASTA header; pathogenic entries are marked in red.
- Use the title switch to overview results efficiently.
Code Availability
The open-source code for SERtool is publicly available on https://github.com/rennmeng/SERtool, and the tool is registered in https://bio.tools/sertool.
Citing SERtool: Please cite the following publication when using this tool or dataset: