Revised Analysis Workflow

1 MinION Sequencing

Data was generated on an Oxford Nanopore MinION with an R10.4.1 flow cell. Basecalling used the HAC model (dna_r10.4.1_e8.2_400bps_hac@v5.2.0) with built-in demultiplexing into 24 barcode directories.

Raw reads are located at:

$FASTQ_BASE/barcode01/*.fastq.gz
$FASTQ_BASE/barcode02/*.fastq.gz
...
$FASTQ_BASE/barcode24/*.fastq.gz

2 Raw Read QC (FastQC)

Run FastQC on the raw reads to assess base quality, read length distributions, and adapter content before any trimming.

# Run FastQC on raw reads for a single barcode
fastqc "$FASTQ_BASE/barcode01"/*.fastq.gz -o "$OUTDIR/fastqc_raw" --threads 2

# Loop over all barcodes
mkdir -p "$OUTDIR/fastqc_raw"
for i in $(seq -w 1 24); do
  fastqc "$FASTQ_BASE/barcode${i}"/*.fastq.gz -o "$OUTDIR/fastqc_raw" --threads 2
done

Check the HTML reports for per-base quality scores, read length distributions, and any adapter contamination flags.

5 Alignment (minimap2)

Align the trimmed reads to the 699 bp genomic reference using minimap2 with the ONT preset. The --MD flag adds MD tags for accurate variant display in IGV.

# Build minimap2 index (if not already done)
minimap2 -d "$REF_MMI" "$REF"

# Align a single barcode
minimap2 -a -x map-ont --MD "$REF_MMI" \
  "$OUTDIR/trimmed/barcode01_trimmed.fastq.gz" \
  > "$OUTDIR/barcode01_aligned.sam"

We write SAM first here to keep alignment and BAM processing as separate steps, but they can be piped together (see Step 6).

6 BAM Sorting & Indexing (samtools)

Convert SAM to sorted BAM and create an index for fast random access in IGV.

# Sort and convert to BAM
samtools sort -o "$OUTDIR/barcode01_aligned.bam" "$OUTDIR/barcode01_aligned.sam"

# Index the BAM
samtools index "$OUTDIR/barcode01_aligned.bam"

# Clean up SAM
rm "$OUTDIR/barcode01_aligned.sam"

Combined pipeline (all barcodes)

For efficiency, pipe alignment directly into sorting:

for i in $(seq -w 1 24); do
  BC="barcode${i}"

  minimap2 -a -x map-ont --MD "$REF_MMI" \
    "$OUTDIR/trimmed/${BC}_trimmed.fastq.gz" 2>/dev/null | \
    samtools sort -o "$OUTDIR/${BC}_aligned.bam" -

  samtools index "$OUTDIR/${BC}_aligned.bam"
done

Quick alignment stats

# Check mapping rate and read counts per barcode
for i in $(seq -w 1 24); do
  echo -n "barcode${i}: "
  samtools flagstat "$OUTDIR/barcode${i}_aligned.bam" 2>/dev/null | head -1
done

7 Indel Analysis (IGV)

Open the aligned BAMs in IGV to visually inspect CRISPR-induced indels at the sgRNA cut site.

Loading files in IGV

1. Genomes > Load Genome from File → select NSP_genomic_ref.fasta
2. File > Load from File → select one or more barcodeXX_aligned.bam files
3. Navigate to position ~230 in the reference — this is the sgRNA cut site

IGV settings for indel visualization

• Color alignments by: → insert size and pair orientation or read strand
• Sort alignments by: → base (at the cut site position) to group indel alleles
• Show soft-clipped bases to see if reads extend beyond expected amplicon boundaries
• Right-click track → Collapsed or Squished view for high-coverage samples
• Look for consistent insertion/deletion patterns clustered at position ~230

What to look for

• Deletions appear as horizontal black lines spanning the cut site
• Insertions appear as purple marks (I) at the cut position
• Wild-type reads align cleanly through the cut site with no gaps
• Editing efficiency = proportion of reads with indels vs. wild-type at the sgRNA target