Frequently Asked Questions

Find answers to common questions about using CassavaDB, troubleshooting, and data analysis.

All Questions Getting Started Data Search Analysis Tools Data Download Technical Issues Primer3

Getting Started

What is CassavaDB and what data does it provide?

CassavaDB is a comprehensive, multi-omics database specifically designed for cassava (Manihot esculenta) research. It integrates various types of biological data to support cassava genomics, breeding, and functional studies.

Data Types Available:

  • Genomic Data: Reference genome assemblies, gene annotations, and miRNA sequences
  • Transcriptomic Data: RNA-Seq datasets, gene expression profiles, differential expression analyses, co-expression networks, and single-cell RNA-seq data
  • Variation Data: Whole genome sequencing (WGS) projects, SNP/InDel variants, and variant density analyses
  • Metabolomic Data: Metabolite profiles, metabolite GWAS, and related analyses
  • Breeding Resources: Cultivar information, SSR markers, and research publications

Key Features: Interactive visualizations, analysis tools, bulk data downloads, and integration with external databases like NCBI and PlantGDB.

How do I navigate CassavaDB? What's the best way to start?

CassavaDB is organized into logical sections based on data types. Here's a recommended navigation strategy:

1
Start with the Homepage

Get an overview of available resources, recent updates, and featured datasets.

2
Explore by Research Interest

Use the main navigation menu to access specific data types: Genomics, Transcriptomics, Variomics, Metabolomics, or Breeding.

3
Use Search Functions

Start with gene search, variant search, or browse expression data to find your genes/regions of interest.

4
Try Analysis Tools

Use built-in tools like GO enrichment, KEGG pathway analysis, or BLAST search for functional analysis.

Pro Tip: Bookmark frequently used pages and use the breadcrumb navigation to keep track of your location in the database.

Do I need to register or create an account to use CassavaDB?

No registration required! CassavaDB is completely open-access and free to use. You can:

  • Browse all data without creating an account
  • Use all search and analysis tools
  • Download datasets
  • Access all visualization tools

Open Science Approach: We believe in making cassava research data freely accessible to accelerate scientific discovery and crop improvement efforts globally.

Data Search and Access

How do I search for specific genes in CassavaDB?

CassavaDB offers multiple ways to search for genes:

1. Basic Gene Search (Genomics → Gene Search)

  • By Gene ID: Enter gene identifiers like "Manes.01G000100"
  • By Gene Name: Search for gene names or symbols

2. Advanced Search Features

  • Batch Search: Search multiple genes at once by entering multiple gene IDs
  • Wildcard Search: Use asterisk (*) for partial matches
  • Case Sensitivity: Gene IDs are case-sensitive, so ensure correct formatting

3. BLAST Search

Use nucleotide or protein sequences to find similar genes:

  • Access via Genomics → BLAST
  • Supports BLASTN, BLASTP, BLASTX, TBLASTN, and TBLASTX
  • Adjustable parameters for sensitivity and specificity

Search Tips: Use wildcards (*) for partial matches, ensure correct gene ID formatting (e.g., Manes.01G000100), and try both gene IDs and gene names. Gene IDs are case-sensitive.

How can I find gene expression data for my genes of interest?

CassavaDB provides comprehensive gene expression data from multiple RNA-Seq studies:

Expression Data Sources

  • RNA-Seq Projects: Multiple transcriptomic studies from different research groups
  • Sample Diversity: Various tissues, developmental stages, and experimental conditions
  • Data Processing: Standardized analysis pipelines for consistent results
  • Expression Profiles: Gene-level expression data across different samples

How to Access Expression Data

1
Gene Expression Browser

Go to Transcriptomics → Gene Expression Browser, enter gene ID(s), and select datasets of interest.

2
RNA-Seq Projects

Browse available studies in Transcriptomics → RNA-Seq Projects to understand experimental designs.

3
Differential Expression

Use Transcriptomics → Differential Expression to find genes up/down-regulated in specific conditions.

Visualization Options: Heatmaps, bar charts, line plots, and box plots. Data can be downloaded in CSV/Excel formats.

What types of genetic variants are available and how do I search them?

CassavaDB includes comprehensive variant data from whole-genome sequencing of diverse cassava accessions:

Variant Types Available

Variant Type Count Description
SNPs ~15 million Single nucleotide polymorphisms
InDels ~2 million Small insertions and deletions

Search Methods

  • Position-based: Search by chromosome and position range
  • Gene-based: Find variants within or near specific genes
  • Effect-based: Filter by predicted functional impact (high, moderate, low)
  • Population-based: Filter by allele frequency in different populations
  • GWAS results: Access significant associations with traits

Advanced Features: Variant density visualization, population frequency analysis, and functional effect prediction for SNPs and InDels.

Analysis Tools

How do I perform GO enrichment and pathway analysis?

CassavaDB provides built-in tools for functional enrichment analysis:

GO Enrichment Analysis

1
Prepare Gene List

Collect your genes of interest (e.g., from differential expression analysis)

2
Access Tool

Navigate to Genomics → GO Enrichment Analysis

3
Input Parameters

Enter gene IDs, select GO categories (BP/MF/CC), set p-value threshold

4
Interpret Results

Review enriched terms, p-values, and gene counts. Download results for further analysis

KEGG Pathway Analysis

  • Pathway Mapping: Map your genes to KEGG pathways
  • Enrichment Testing: Statistical testing for over-represented pathways
  • Visual Pathway Maps: Interactive pathway diagrams with highlighted genes
  • Cross-species Comparison: Compare with pathways from other plant species

Input Requirements: Use valid cassava gene IDs (e.g., Manes.01G000100). Check if the enrichment analysis tools are available in your CassavaDB instance, as some advanced analysis features may require specific configuration.

What happens if I click "Pick Primers" without entering a sequence in Primer3?

⚠️ Error Result: If you click "Pick Primers" without entering any DNA sequence, you will receive an error message:

PRIMER_ERROR=Missing SEQUENCE tag

Solution: Always enter a DNA sequence in the "Source Sequence" text area before clicking "Pick Primers".

How to Use Primer3 Correctly

1
Enter DNA Sequence

Paste your target DNA sequence (5' → 3' direction) in the "Source Sequence" field. FASTA format is supported.

2
Select Task Type

Choose appropriate task: "generic" for standard PCR, "pick_sequencing_primers" for sequencing, or "check_primers" to validate existing primers.

3
Configure Parameters

Adjust primer size, melting temperature, GC content, and product size according to your experimental needs.

4
Pick Primers

Click "Pick Primers" to generate optimized primer pairs with detailed quality information.

Sequence Requirements: Only ACGTN letters are recognized (other letters treated as N). Numbers and spaces are automatically ignored.

What are the optimal Primer3 settings for different PCR applications?

Different PCR applications require different primer design parameters:

Parameter qPCR Standard PCR Sequencing Description
Product Size 80-150 bp 200-1000 bp Variable Target amplicon length
Primer Length 18-22 bp 18-25 bp 18-30 bp Primer sequence length
Tm Difference ≤ 2°C ≤ 5°C ≤ 5°C Temperature difference between primers
GC Content 45-55% 40-60% 40-60% Percentage of G and C nucleotides
Tm Range 58-62°C 55-65°C 55-70°C Melting temperature range

Advanced Settings for Difficult Templates

  • High GC Content: Increase Tm range to 65-70°C, allow longer primers
  • Repetitive Sequences: Use template masking, increase penalty for repeats
  • Low Specificity: Use mispriming library, increase penalty for secondary structures
  • Multiplex PCR: Ensure similar Tm values, check for primer-primer interactions

Pro Tip: Start with default parameters and adjust based on results. For challenging sequences, try template masking with cassava-specific repeat libraries.

How do I use JBrowse2 to visualize genomic features?

JBrowse2 is our interactive genome browser for exploring cassava genomic features in their chromosomal context:

Getting Started with JBrowse2

1
Access the Browser

Navigate to Genomics → JBrowse2 to open the genome browser interface

2
Navigate to Region

Enter coordinates (e.g., "Chr01:1000000-2000000") or gene IDs in the location box

3
Add Data Tracks

Select tracks to display: genes, variants, RNA-Seq coverage, repeat elements, etc.

4
Customize View

Zoom in/out, adjust track heights, change color schemes, and configure display options

Available Data Tracks

  • Gene Models: Protein-coding genes and gene annotations
  • Variants: SNPs and InDels with functional annotations
  • RNA-Seq: Expression data and coverage tracks from different studies
  • Genome Features: Reference genome sequences and chromosomal regions

Keyboard Shortcuts: Use arrow keys to pan, +/- to zoom, and 'r' to reverse complement. Right-click features for detailed information and links to other tools.

Data Download

What datasets are available for download and in what formats?

CassavaDB provides comprehensive datasets for offline analysis. All data is freely available without registration:

Available Datasets

Data Type Format Size Description
Reference Genome FASTA, GFF3 ~750 MB Complete genome assembly with annotations
Gene Sequences FASTA ~50 MB CDS, protein, and transcript sequences
Variant Data VCF, TSV ~1-2 GB SNPs and InDels with functional annotations
Expression Data CSV, TSV, H5 ~500 MB RNA-Seq count matrices and metadata
Metabolite Data CSV, Excel ~10 MB Metabolite profiles and GWAS results

Download Methods

  • Bulk Downloads: Complete datasets via the Download page
  • Custom Downloads: Subset data based on your search criteria
  • API Access: Programmatic access for automated downloads
  • FTP Server: Direct access to all data files

Data Updates: Datasets are updated regularly. Check version numbers and release dates to ensure you have the latest data.

How do I export search results and analysis outputs?

Most CassavaDB tools provide multiple export options for your results:

Export Formats Available

  • CSV/TSV: Tabular data for Excel, R, Python analysis
  • JSON: Structured data for programmatic processing
  • FASTA: Sequence data for further bioinformatics analysis
  • GFF3/BED: Genomic coordinates for genome browsers
  • PNG/SVG: High-quality plots and visualizations
  • PDF: Publication-ready figures and reports

Export Procedures

1
Complete Your Analysis

Perform search or analysis using any CassavaDB tool

2
Locate Export Button

Look for "Download", "Export", or "Save" buttons near results tables or plots

3
Choose Format

Select appropriate file format based on your downstream analysis needs

4
Save File

File will be downloaded to your default download folder

File Size Limits: Large result sets may be split into multiple files or require bulk download. Check file sizes before exporting.

Technical Issues and Troubleshooting

Which web browsers are supported? I'm having display issues.

CassavaDB is optimized for modern web browsers. For the best experience, use:

Recommended Browsers

Browser Minimum Version Recommended Version Notes
Chrome 90+ Latest Best performance, all features supported
Firefox 88+ Latest Excellent compatibility
Safari 14+ Latest Good on macOS/iOS
Edge 90+ Latest Chromium-based versions

Common Display Issues and Solutions

  • Slow Loading: Clear browser cache, disable ad blockers, check internet connection
  • Missing Graphics: Enable JavaScript, update browser, check popup blockers
  • Layout Problems: Try browser zoom reset (Ctrl+0), disable browser extensions
  • Interactive Tools Not Working: Allow JavaScript execution, disable strict security settings

Mobile Access: CassavaDB is responsive and works on tablets and smartphones, though desktop browsers provide the best experience for complex analyses.

Analysis is taking too long or timing out. What should I do?

Large analyses can take time. Here are optimization strategies:

Performance Optimization

  • Reduce Dataset Size: Filter by chromosome, gene set, or expression level before analysis
  • Batch Processing: Split large gene lists into smaller chunks
  • Use Appropriate Tools: Choose the right tool for your data size and complexity
  • Off-peak Usage: Try analyses during less busy times (early morning, late evening)

Timeout Troubleshooting

1
Check Input Size

Reduce number of genes/variants in your analysis

2
Simplify Parameters

Use less stringent cutoffs, reduce number of comparisons

3
Try Alternative Approach

Consider downloading data for local analysis

4
Contact Support

For persistent issues, contact our support team

Resource Limits: Some analyses have built-in limits (e.g., max 1000 genes for enrichment analysis) to ensure reasonable response times for all users.

I found a bug or error. How do I report it?

We appreciate bug reports and feedback to improve CassavaDB:

How to Report Issues

1
Document the Issue

Note what you were doing, expected vs. actual results, and error messages

2
Gather System Info

Include browser type/version, operating system, and screen resolution

3
Take Screenshots

Visual documentation helps us understand and reproduce the issue

4
Send Report

Email us at 23220951310021@hainanu.edu.cn with all details

Information to Include

  • Page URL: Exact page where the issue occurred
  • Steps to Reproduce: Detailed sequence of actions
  • Input Data: Gene IDs, search terms, or parameters used
  • Error Messages: Exact text of any error messages
  • Expected Behavior: What you expected to happen
  • Browser Console: Any JavaScript errors (F12 → Console)

Response Time: We typically respond to bug reports within 24-48 hours and aim to fix critical issues within a week.

Additional Resources

Are there tutorials or video guides available?

We provide several educational resources to help you use CassavaDB effectively:

Available Resources

  • Video Tutorials: Step-by-step guides for common analyses (coming soon)
  • Webinar Recordings: Monthly webinars on CassavaDB features and cassava research
  • Example Workflows: Complete analysis pipelines for different research questions
  • Best Practices Guide: Recommendations for data interpretation and analysis
  • Publication Gallery: Studies that used CassavaDB data

Educational Content

Coming Soon: Interactive tutorials, example datasets, and guided analysis workflows to help new users get started quickly.

Community Resources

  • User Forum: Discussion platform for questions and tips (planned)
  • Mailing List: Updates on new features and data releases
  • Social Media: Follow us for news and research highlights
How should I cite CassavaDB in my publications?

Please cite CassavaDB when using our data or tools in your research:

Primary Citation

Database Citation:

Author et al. (2025). CassavaDB: A comprehensive multi-omics database for cassava genomics and breeding. Plant Biotechnology Journal, XX(X), XXX-XXX. DOI: 10.1111/xxxxx

Dataset-Specific Citations

When using specific datasets, please also cite the original data sources:

  • Genome Assembly: Cite the original genome publication
  • RNA-Seq Data: Cite the original expression studies
  • Variant Data: Cite the population genomics studies
  • Metabolomic Data: Cite the original metabolomics publications

Reference List: Complete citations for all datasets are available on individual data pages and in the Reference & Publication section.

Acknowledgment Template

You may also include this acknowledgment:

"We thank the CassavaDB team for providing access to cassava genomic resources and analysis tools."