peek

A couple of small utilities to quickly peek at results from nanopore-based sequencing runs.

Install

# create a virtual environment (e.g. using conda)
# cd into a directory where you store source code
git clone https://github.com/phiweger/peek
cd peek 
pip install -r requirements.txt -e .

Usage

List subcommands:

peek

Look at the API of subcommands:

peek stats --help

Usage: peek stats [OPTIONS]

  Return basic stats from basecalled fastq.

  stats: read name, length, median quality, label

  Usage:

  peek stats -f bar.fq -o bar.txt -l bad
  # 3964e59a-f07d-46ff-bff5-1e2c03e4254a    981 10.0    bad
  # c0dd59b3-bd29-488f-a78f-fa75d6fc6a3d    987 12.0    bad
  # 3f6a3cd0-c788-40c2-900a-4ea3a6eb424c    869 13.0    bad

  # only summary
  peek stats --summary -f bar.fq > /dev/null

  # or read from stdin
  seqtk sample -s42 bar.fq 10000 | peek stats -f - -o bar.txt -l bad
  cat workspace/pass/barcode01/* | peek stats --summary -f - > /dev/null

  # concatenate multiple fastq stats and plot using R
  peek stats --label bc01 -f BC01.fastq --summary > read_len_dist.tsv
  peek stats --label bc02 -f BC02.fastq --summary >> read_len_dist.tsv
  R

  library(ggplot2)
  library(readr)
  df <- read_tsv('read_len_dist.tsv', col_names=c('name', 'length', 'quality', 'label'))
  ggplot(df, aes(x=length, colour=label)) +
      geom_histogram(bins=100) +
      scale_x_log10(labels=scales::comma)

Options:
  --summary         Write summary to stderr
  --header          Include header
  -l, --label TEXT  Label
  -n INTEGER        How many reads?
  -o TEXT           Where to write output?
  -f TEXT           Raw fastq file from e.g. Albacore basecaller  [required]
  --help            Show this message and exit.