CNery 1.1.0

An extension of breseq to determine copy number variations from coverage data

CNery

breseq copy-number-variation extension. CNery reads the sequencing coverage output from breseq and predicts copy-number variation (CNV) across the genome. Predictions are corrected for coverage biases introduced by sequencing chemistry (GC-content bias) and prokaryotic replication state during DNA isolation (origin-to-terminus / OTR bias).

Recent updates (latest commits):

• Multi-genome CNV analysis — CNery now processes all reference sequences found in the breseq BAM/FASTA in one pass. Each reference (chromosome, plasmid, contig, etc.) is preprocessed per genome, pooled for a shared LOWESS GC-bias fit, and then bias-corrected and CN-called independently.
• Input/output flexibility — inputs default to <input>/data/reference.bam and <input>/data/reference.fasta; output prefix defaults to <input>/CNV_out/. Output subfolders (CNV_plt/, CNV_csv/, GC_bias/, OTR_corr/) are created automatically.
• Modular bias correction — the --bias flag lets you choose all (GC + OTR), gc, otr, or none.
• Pip-installable package — requirements.txt and a fixed pyproject.toml allow install directly from GitHub via pip install git+....

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Installation

Recommended: create a conda/mamba environment from the provided spec.

mamba env create -f environment.yml
mamba activate CNery

Install CNery (a.k.a. breseq-ext-cnv) from GitHub:

pip install git+https://github.com/barricklab/breseq-ext-cnv.git

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Quick start

Run CNery inside a breseq output folder that contains the data/ and output/ subfolders:

CNery [-o <output folder>] [-w <window>] [-s <step size>] [-f <fragment length>]

To run from a different working directory, point -i at the breseq output folder (or supply -ref and the BAM path manually):

CNery -i <breseq output folder> \
      -ref <reference.fasta> \
      -o  <output folder> \
      -w  <window> \
      -s  <step size> \
      -f  <fragment length>

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Usage examples

Calculate coverage with a 500 bp window sliding in 250 bp steps; sequencing fragment length is 300 bp:

CNery -o <output folder> -w 500 -s 250 -f 300

Analyze coverage across the whole genome, but restrict CNV/coverage plots to a specific genomic segment:

CNery -o <output folder> --region 3497890-3955678 -w 1000 -s 500

The --region argument accepts open intervals too (-reg 3497890- from a start to end of genome, -reg -3955678 from start of genome to an end position).

Control which bias correction is applied before CN prediction:

# Both GC + OTR corrections (default)
CNery -o <output folder> -w 500 -s 250 --bias all

# Only correct OTR (replication) bias
CNery -o <output folder> -w 500 -s 250 --bias otr

# Only correct GC-content bias
CNery -o <output folder> -w 500 -s 250 --bias gc

# No bias correction before CN prediction
CNery -o <output folder> -w 500 -s 250 --bias none

When OTR correction is applied, the origin and terminus of replication are automatically inferred from the coverage profile — no manual coordinates are required.

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Outputs

Given an output folder CNV_out/, CNery writes:

• CNV_out/CNV_plt/ — per-reference CNV prediction plots.
• CNV_out/CNV_csv/ — per-window coverage + CN calls as CSV.
• CNV_out/GC_bias/ — pooled LOWESS GC-bias diagnostic plot.
• CNV_out/OTR_corr/ — per-reference OTR bias plots and a JSON summary (*_otr_results.json) containing the inferred origin window, terminus window, normalized coverage at each, and the origin-to-terminus ratio.

Each reference sequence in the BAM/FASTA produces its own set of outputs, named with the reference / genome identifier.

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All command-line options

$ CNery -h

usage: CNery [-h] [-i I] [-ref REF] [-reg REG] [-o O] [-w W] [-s S] [-f F] [-e E]
             [--bias {all,none,gc,otr}]

CNery is a Python package extension to breseq that analyzes the sequencing
coverage across the genome to predict copy number variation (CNV).

options:
  -h, --help            show this help message and exit
  -i, --input I         input folder path (the breseq output folder with
                        'data' and 'output' folders). Defaults to the current
                        folder.
  -ref REF              select the reference file used for breseq. Defaults
                        to data/reference.fasta.
  -reg REG              select the region of the genome to evaluate
                        (format: START-END, e.g. 1000-50000).
  -o, --output O        output file prefix / storage location. Defaults to
                        the 'CNV_out' folder in the current dir.
  -w, --window W        Window length used to parse the genome and compute
                        coverage and GC statistics. Default: 200.
  -s, --step-size S     Step size (<= window size) for each progression of
                        the window across the genome. Set step-size = window
                        size for non-overlapping windows. Default: 100.
  -f, --frag_size F     Average fragment size of the sequencing reads.
                        Default: 500.
  -e, --error-rate E    Approximate error rate in sequencing read coverage /
                        reference alignment. Default: 0.05.
  --bias {all,none,gc,otr}
                        Select which bias correction to apply before CN
                        prediction. 'all' applies GC + OTR, 'gc' or 'otr'
                        applies only that one, 'none' skips bias correction.
                        Default: all.

Run this script in the breseq output folder that contains 'data' and 'output'
folders.

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