Output Examples

This page showcases example outputs from SeqNado pipelines to help you understand what to expect from your analyses. All examples are based on real test data processed through the pipeline.

SeqNado QC Report

The main seqnado_report.html provides a MultiQC report with comprehensive quality control metrics.

Report Sections

1. General Statistics

View high-level sample information and key metrics:

• Total reads: Raw sequencing depth
• Mapped reads: Alignment success rate
• Duplication rate: PCR duplicate percentage
• GC content: Library GC distribution
• Insert size: Fragment size metrics (PE data)

2. FastQC Results

Quality metrics on raw reads:

• Per base sequence quality: Quality scores across read positions
• Per sequence quality scores: Overall read quality distribution
• Per base sequence content: Nucleotide balance
• Sequence duplication levels: Library complexity indicators
• Adapter content: Contamination levels

3. Alignment Metrics

Mapping statistics from Bowtie2 (DNA assays) or STAR (RNA-seq):

• Alignment rates: Percentage uniquely mapped, multimapped, unmapped
• Paired-end concordance: Proper pair percentages
• Insert size distribution: Fragment size histograms

4. Peak Calling Summary (ChIP/ATAC/CUT&Tag)

Peak detection results:

• Number of peaks: Total peaks called per caller
• FRiP scores: Fraction of Reads in Peaks (if enabled)
• Peak caller comparison: Overlap between MACS2, HOMER, LanceOtron, SEACR

5. Library Complexity

Picard duplicate metrics:

• Unique reads: Non-duplicate read counts
• Duplication rates: PCR duplicate percentages
• Library complexity estimates: From Picard MarkDuplicates metrics

ChIP-seq Example Output

Directory Structure

seqnado_output/chip/
├── seqnado_report.html                    # Main QC dashboard
├── protocol.txt                           # Data processing protocol
├── aligned/
│   ├── chip-rx_MLL.bam                    # Final processed BAM
│   ├── chip-rx_MLL.bam.bai
│   ├── chip-rx_input.bam
│   └── chip-rx_input.bam.bai
├── bigwigs/
│   ├── bamnado/
│   │   └── unscaled/
│   │       ├── chip-rx_MLL.bigWig
│   │       └── chip-rx_input.bigWig
│   ├── deeptools/
│   │   └── unscaled/
│   │       ├── chip-rx_MLL.bigWig
│   │       └── chip-rx_input.bigWig
│   └── homer/
│       └── unscaled/
│           ├── chip-rx_MLL.bigWig
│           └── chip-rx_input.bigWig
├── peaks/
│   ├── macs2/
│   │   └── chip-rx_MLL.bed               # Simplified 3-column BED
│   ├── homer/
│   │   └── chip-rx_MLL.bed
│   └── lanceotron/
│       └── chip-rx_MLL.bed
├── qc/
│   ├── fastqc_raw/
│   │   ├── chip-rx_MLL_1_fastqc.html
│   │   ├── chip-rx_MLL_2_fastqc.html
│   │   ├── chip-rx_input_1_fastqc.html
│   │   └── chip-rx_input_2_fastqc.html
│   ├── fastq_screen/                      # If enabled
│   │   ├── chip-rx_MLL_1_screen.html
│   │   └── chip-rx_input_1_screen.html
│   ├── qualimap_bamqc/
│   │   ├── chip-rx_MLL/qualimapReport.html
│   │   └── chip-rx_input/qualimapReport.html
│   ├── alignment_stats.tsv
│   └── library_complexity/
│       ├── chip-rx_MLL.metrics
│       └── chip-rx_input.metrics
├── hub/
│   └── seqnado_hub.hub.txt
└── tag_dirs/
    └── chip-rx_MLL/

Example Peak File Content

SeqNado outputs simplified 3-column BED files for all peak callers:

BED format (chip-rx_MLL.bed):

chr1    3054728    3055228
chr1    3669834    3670334
chr2    5847291    5847791
...

Columns:

1. Chromosome
2. Start position
3. End position

ATAC-seq Example Output

Directory Structure

seqnado_output/atac/
├── seqnado_report.html
├── protocol.txt
├── aligned/
│   ├── atac_sample.bam                    # Tn5-shifted, filtered BAM
│   └── atac_sample.bam.bai
├── bigwigs/
│   ├── bamnado/
│   │   └── unscaled/
│   │       └── atac_sample.bigWig
│   ├── deeptools/
│   │   └── unscaled/
│   │       └── atac_sample.bigWig
│   └── homer/
│       └── unscaled/
│           └── atac_sample.bigWig
├── peaks/
│   └── lanceotron/                        # Default peak caller for ATAC
│       └── atac_sample.bed
├── qc/
│   ├── fastqc_raw/
│   ├── qualimap_bamqc/
│   │   └── atac_sample/
│   │       └── qualimapReport.html
│   ├── alignment_stats.tsv
│   └── library_complexity/
│       └── atac_sample.metrics
└── hub/
    └── seqnado_hub.hub.txt

Note

All intermediate BAM processing stages (sorting, blacklist removal, duplicate removal, Tn5 shifting, filtering) are temporary and automatically deleted. Only the final aligned/{sample}.bam is retained.

ATAC-seq Quality Indicators

Key metrics to check in the MultiQC report:

Metric	Good Quality	What to Look For
Nucleosome periodicity	Clear peaks at ~200bp intervals	Visible in insert size distribution
Mitochondrial %	<10%	Low mitochondrial read contamination
FRiP score	>30%	High fraction of reads in peaks
Unique reads	>80%	Good library complexity

Fragment Size Distribution

ATAC-seq shows characteristic nucleosome-free (~150bp) and mono-nucleosome (~200bp) peaks, visible in the insert size distribution within the MultiQC report.

Qualimap BAM QC Report

The Qualimap reports provide detailed alignment quality metrics. For RNA-seq, qualimap_rnaseq is used instead of qualimap_bamqc.

Key Visualisations

Coverage Histogram

• Distribution of genome coverage depths
• Helps identify over/under-sequenced regions
• Shows sequencing uniformity

Insert Size Distribution

• Fragment size histogram for paired-end data
• Critical for ATAC-seq quality assessment
• Reveals nucleosome positioning

GC Content Distribution

• AT/GC bias detection
• Compares observed vs theoretical
• Identifies contamination or bias

Mapping Quality

• Distribution of MAPQ scores
• Higher scores = more confident alignments
• Helps assess multi-mapping issues

Example FastQ Screen Results

FastQ Screen checks for contamination across reference genomes (when enabled via run_fastq_screen):

Typical Clean Sample

Library: chip-rx_MLL_1
Genome          %Mapping    %One_hit    %Multi_hit    Status
--------------------------------------------------------------
Human (hg38)    98.2%       85.4%       12.8%         OK
Mouse (mm10)     0.8%        0.5%        0.3%         OK
E. coli          0.0%        0.0%        0.0%         OK
Adapters         0.3%        0.3%        0.0%         OK
PhiX             0.0%        0.0%        0.0%         OK

Concerning Sample (Contamination)

Library: sample_contaminated
Genome          %Mapping    %One_hit    %Multi_hit    Status
--------------------------------------------------------------
Human (hg38)    65.2%       58.4%        6.8%         WARNING
Mouse (mm10)    32.8%       29.5%        3.3%         WARNING
E. coli          1.2%        1.1%        0.1%         WARNING

HOMER Tag Directory

HOMER creates tag directories for downstream analysis:

tag_dirs/chip-rx_MLL/
├── tagInfo.txt                     # Read statistics
├── tagLengthDistribution.txt       # Fragment sizes
├── tagCountDistribution.txt        # Tag depth per position
├── freqDistribution.txt            # Frequency statistics
├── chr1.tags.tsv                   # Per-chromosome tags
├── chr2.tags.tsv
└── ...

BigWig Coverage Tracks

BigWig files provide genome-wide signal visualisation.

File Naming Convention

BigWig files are organised by tool and scaling method:

bigwigs/{method}/{scale}/{sample}.bigWig

Examples:
- bigwigs/deeptools/unscaled/chip-rx_MLL.bigWig
- bigwigs/bamnado/unscaled/chip-rx_MLL.bigWig
- bigwigs/homer/unscaled/chip-rx_MLL.bigWig
- bigwigs/deeptools/csaw/chip-rx_MLL.bigWig
- bigwigs/deeptools/spikein/orlando/chip-rx_MLL.bigWig
- bigwigs/deeptools/merged/consensus_group.bigWig

For RNA-seq, stranded tracks include _plus and _minus suffixes:

- bigwigs/deeptools/unscaled/rna_sample_plus.bigWig
- bigwigs/deeptools/unscaled/rna_sample_minus.bigWig

Loading in UCSC Genome Browser

1. Upload BigWig files to a web-accessible location
2. Or use the auto-generated hub at hub/seqnado_hub.hub.txt
3. Tracks display sample signal across genome
4. Compare multiple samples side-by-side

GEO Submission Files

Ready-to-submit files for GEO/SRA (when enabled):

geo_submission/
├── samples_table.txt                       # Sample metadata (TSV format)
├── md5sums.txt                             # Combined checksums
├── raw_data_checksums.txt                  # Checksums for raw FASTQs
├── processed_data_checksums.txt            # Checksums for processed files
├── upload_instructions.txt                 # GEO upload instructions
├── chip-rx_MLL_1.fastq.gz                  # Symlinks to raw FASTQ R1
├── chip-rx_MLL_2.fastq.gz                  # Symlinks to raw FASTQ R2
├── chip-rx_MLL_deeptools_unscaled.bigWig   # Renamed processed files
├── chip-rx_MLL_macs2.bed                   
└── chip/                                   # Upload directory

Files are flattened from the nested directory structure into a single directory with descriptive filenames that encode the tool and scaling method.

Genome Browser Plots (PlotNado)

Publication-ready visualisations of genomic regions (when plotting coordinates are configured):

Output Files

genome_browser_plots/
├── MYC_promoter.svg             # Named region from BED file
├── chr1-1000000-1005000.svg     # Unnamed region uses coordinates
└── template.toml                # PlotNado configuration template

Plot filenames are derived from the Name column in the input BED file, or from {chr}-{start}-{end} if no name is provided. Output format can be svg, png, or pdf as configured.

Tips for Exploring Outputs

Quick Quality Check

# Check main report
firefox seqnado_output/chip/seqnado_report.html

# Count peaks called
wc -l seqnado_output/chip/peaks/macs2/*.bed

# View alignment stats
samtools flagstat seqnado_output/chip/aligned/chip-rx_MLL.bam

# Check bigwig file
bigWigInfo seqnado_output/chip/bigwigs/deeptools/unscaled/chip-rx_MLL.bigWig

Finding Specific Results

# All HTML reports
find seqnado_output/ -name "*.html"

# All peak files
find seqnado_output/ -name "*.bed"

# All coverage tracks
find seqnado_output/ -name "*.bigWig"

Understanding File Formats

BAM Files

• Binary alignment format (.bam extension)
• Stores aligned sequencing reads
• Includes alignment quality, CIGAR strings, and flags

BigWig Files

• Binary coverage track format (.bigWig extension)
• Efficient genome browser visualisation
• Contains normalised signal values

BED Files

• Tab-delimited genomic coordinates (.bed extension)
• SeqNado peak outputs use 3-column BED: chr, start, end
• Standard BED can include additional columns (name, score, strand)

FastQ Files

• Raw sequencing reads (.fastq.gz extension)
• Four lines per read: header, sequence, +, quality scores
• Usually gzip compressed (.gz)

---

For more information on interpreting these outputs for your specific experiment, consult the Pipeline Overview.