🧬 JCAP_ATAC_SEQ APP — Multi-Species Usage Guide Step 1 | Upload Your Data
Upload a ZIP of BED files for consensus peak calling.
Click “Make Consensus Peaks.”
✅ Confirmation message will display the number of merged peaks.
Step 2 | Peak Annotation (Organism-Aware)
Click “Run Peak Annotation.”
Peaks are annotated with nearest gene and distance to TSS using species-specific Bioconductor packages:
Species TxDb Package OrgDb Package Human TxDb.Hsapiens.UCSC.hg38.knownGene org.Hs.eg.db Mouse TxDb.Mmusculus.UCSC.mm10.knownGene org.Mm.eg.db Zebrafish TxDb.Drerio.UCSC.danRer11.refGene org.Dr.eg.db Fly TxDb.Dmelanogaster.UCSC.dm6.ensGene org.Dm.eg.db
View results in:
📊 Peak Annotation Table — searchable & downloadable
🥧 Annotation Pie Chart — visual gene distribution
Step 3 | Motif Enrichment (Optional)
Select the species and TF family (e.g., ALL, TP53) from the dropdown.
Click “Run Motif Enrichment.”
Uses:
TFBSTools + JASPAR2020 (species filtered via taxID)
motifmatchr for genome-wide PWM matching
BSgenome.* for the chosen organism:
BSgenome.Hsapiens.UCSC.hg38
BSgenome.Mmusculus.UCSC.mm10
BSgenome.Drerio.UCSC.danRer11
BSgenome.Dmelanogaster.UCSC.dm6
View results in:
📊 Motif Enrichment Table
📈 Top Motif Plot
Step 4 | Counts & Metadata
Upload a CSV count matrix (peaks × samples).
Upload a CSV metadata file (samples × condition).
Click “Run DAA on Uploaded Counts.”
Runs DESeq2 for differential accessibility analysis.
View results in 📉 Uploaded DAA Results.
Step 5 | Exploratory Visualizations
Run PCA → PCA plot of samples
Run UMAP → UMAP embedding of samples
Plot Heatmap → Heatmap of log₂(count + 1)
Step 6 | Machine Learning — Random Forest
Click “Run Random Forest Classifier.”
Trains a 2-class classifier on uploaded counts.
View results in:
📋 RF Metrics (AUC, Accuracy)
📈 ROC Curve
🔥 Feature Importance Plot
Step 7 | Power Analysis
Set Effect Size, FDR α, and Replicates per Group.
Click “Run Power Analysis.”
View results in:
📈 Power Plot (with 95 % CI)
📊 Power Table (replicates vs power)
Downloadable CSV via Download Power Table
💾 Downloadable Results
You can save:
Peak Annotation Table
Motif Enrichment Table
DAA Results
Power Table
📂 Tab Summary
Tab Name Description
README Usage instructions (this document)
Peak Annotation Table Annotated peaks with download
Annotation Pie Chart Gene distribution pie chart
Motif Enrichment Table Matched TF motifs across species
Motif Enrichment Plot Top motif bar chart
Uploaded DAA Results DESeq2 differential analysis
PCA Plot Principal component analysis
UMAP Plot UMAP sample embedding
Heatmap log₂(count + 1) heatmap
RF Metrics AUC and accuracy
Feature Importance Top important peaks
ROC Curve ROC performance curve
Power Plot Power vs replicates
Power Table Numeric power estimates
All runtime errors are written to error_log.txt.
Admin scripts (e.g., email_log.R) can aggregate or forward logs.
💡 Tips
Rerun any module without reuploading data.
Use included example datasets to verify formats.
“Run Power Analysis” helps plan ATAC-seq replicates for desired power.
Built by scientists, for scientists 🧬 — reproducible, species-aware ATAC-seq analytics with no coding required.