ont-spectre 0.2.0

Oxford Nanopore Technologies Plc. fork of Spectre CNV caller

Spectre - Long read CNV caller

Required programs (conda)

Setup a conda environment for Spectre (copy and paste the following commands)

conda create -n spectre python=3.8.5 pysam==0.21.0 numpy==1.24.3 pandas==2.0.1 matplotlib==3.7.1 scipy==1.10.1 -y
conda activate spectre

Alternatively, you can use pip for installing the packages stored in the requirements txt

conda create -n spectre python=3.8.5 pip -y
conda activate spectre
pip install -r requirements.txt

or install everything manually (check for package version in the requirements.txt file)

Program	Conda
python3	conda install python=3.8.5
pysam	conda install -c bioconda pysam=0.21.0
pandas	conda install -c anaconda pandas==2.0.1
numpy	conda install -c anaconda numpy==1.24.3
scipy	conda install -c anaconda scipy==1.10.1
matplotlib	conda install -c anaconda matplotlib==3.7.1

How to run

Spectre need as input:

• The result of Mosdepth (directory)
• Reference genome (can be bgzip compressed)
• Window size used in Mosdepth (Make sure the binsize between Mosdepth and Spectre are matching. We suggest a binsize of 1000 base pairs.)

Optional

• VCF file containing SNV

INFO: Make sure to include "/" at the end if you are adding directory paths.

spectre.py CNVCaller \
  --bin-size 1000 \
  --coverage mosdepth/sampleid/ \
  --sample-id sampleid \
  --output-dir sampleid_output_directory_path/ \
  --reference reference.fasta.gz \
  --snv sampleid.vcf.gz

Run Spectre with multiple samples

Run Spectre with multiple samples:

INFO: This will start the population mode automatically.

spectre.py CNVCaller \
  --bin-size 1000 \
  --coverage mosdepth/sampleid-1/ mosdepth/sampleid-1/ \
  --sample-id sampleid-1 sampleid-2 \
  --output-dir sampleid_output_directory_path/ \
  --reference reference.fasta.gz \
  --snv sampleid.vcf.gz

Population mode

Run Spectre in population mode with two or more samples:

INFO: Spectre produces an intermediate file (.spc) which contains all calculated CNVs from a given samples. They are located in the output folder of given sample.

spectre.py population \
  --candidates /path/to/sample1.spc /path/to/sample2.spc \
  --sample-id output_name \
  --output-dir sampleid_output_directory_path/