Nanopore raw data visualization using squigualiser

# Create environment
mamba create --name ont python=3.9
mamba activate ont


# Install blue-crab
mamba install zstd
python3 -m pip install --upgrade pip
pip install blue-crab

# Install slow5tools
mamba install hdf5
mamba install slow5tools

mamba install f5c=1.4

pip install squigualiser

slow5tools f2s ./fast5_dir -d blow5_dir # convert multiple FAST5 files to multiple BLOW5 files
slow5tools merge blow5_dir -o data.blow5 # merge BLOW5 into one
slow5tools get data.blow5 -l read_ids.txt --to blow5 -o target.blow5 # extract records from a blow5 file based on a list of read ids
slow5tools index target.blow5 # index BLOW5 file

blue-crab p2s data.pod5 -o data.blow5

f5c resquiggle -c --rna --pore r9 -o target.paf target.fastq target.blow5

squigualiser plot -f target.fastq -s target.blow5 -a target.paf -o out_dir --save_svg

# show the whole fastq sequence, output in the HTML file
squigualiser plot -f target.fastq -s target.blow5 -a target.paf -o target_dir --rna --sig_scale znorm --fixed_width --base_limit 20000 --sig_plot_limit 99999999

# show the whole fastq sequence, output in the SVG file
squigualiser plot -f target.fastq -s target.blow5 -a target.paf -o target_dir --rna --sig_scale znorm --fixed_width --base_limit 20000 --sig_plot_limit 99999999 --no_samples --no_colours --save_svg --region 200-500 --xrange 6000 --plot_limit 9000

-r read_id # specify the read with read_id to plot
--rna # specify for RNA reads
--fixed_width # plot with fixed base width
--base_limit # maximum number of bases to plot
--sig_plot_limit # maximum number of signal samples to plot