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Project description
amp-depth-viz
visualise amplicon genome coverage by bokeh using mosdepth output
install
conda create -n amp-depth-viz -c conda-forge -c bioconda -c nanoporetech fastcat python=3.14
conda activate amp-depth-viz
pip install amp-depth-viz
Instruction
#running fastcat and provide a samplesheet
#fastq_pass is the fastq_pass folder from the sars ONT run
#samplesheet requests at least two columns: sampleID,barcode
#It helps to filter the barcode and relate to right sampleID
amp-depth-viz sample/sample_input.bed --fastq_pass Data/sars/fastq_pass --samplesheet samplesheet.csv --output test.html
#if you already ran fastcat and have the per reads summary file, you can do
amp-depth-viz sample/sample_input.bed --fastcat_perreads Data/per-reads-summary.tsv --samplesheet samplesheet.csv --output test.html
Usage
usage: amp-depth-viz [-h] [--fastcat_perreads FASTCAT_PERREADS | --fastq_pass FASTQ_PASS] [--template TEMPLATE]
[--samplesheet SAMPLESHEET] [--output OUTPUT] [--xlim XLIM] [--ylim YLIM] [--threshold THRESHOLD]
[--threads THREADS] [--ncols NCOLS]
coveragebed
create wf-artic like amplicon coverage plots using bokeh
positional arguments:
coveragebed a full sample bed files contains all genome depth information from mosdepth
options:
-h, --help show this help message and exit
--fastcat_perreads FASTCAT_PERREADS
per-read-stats.tsv output from fastcat
--fastq_pass FASTQ_PASS
the fastq_folder from a sars cov run
--template TEMPLATE jinja2 template to render -- default in template/template.html
--samplesheet SAMPLESHEET
An optional samplesheet to rename the barcode, at least two columns required: sampleID, barcode
--output OUTPUT html output file
--xlim XLIM max of the genome position
--ylim YLIM the expected max depth
--threshold THRESHOLD
depth threshold for passing QC , default as 20
--threads THREADS max number of cpus to use for fastcat analysis
--ncols NCOLS number of columns to grid the plots in the html pages, default as 3
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