floundeR

An R package to simplify the tidy analysis of Nanopore sequence data.

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The goal of floundeR is to provide a robust and Tidyverse compliant toolbox that can be used to explore Nanopore sequence data. The analytical R code contained within has been forked from earlier projects such as nanopoRe. The R code has been deduplicated and reimplemented as R6 objects.

The project goals diverge from earlier versions of nanopoRe and the ambition is now to enable abbreviated and simplified data exploration.

The documentation for the floundeR package can be found at https://sagrudd.github.io/floundeR/

Installation

There are a couple of dependencies for the successful usage of the floundeR package.

You can install the released version of floundeR from github with:

install.packages("devtools")
devtools::install_github("sagrudd/floundeR")

# devtools does not appear to pull in some of the bioconductor stuff ...
install.packages("BiocManager")
BiocMananger::install("rhdf5")
# please see documents below - this requires the vbz plugin

floundeR and a BasicQC analysis to assess a flowcell run

BasicQC was the name of the original Nanopore tutorial that introduced an R workflow to question a flowcell’s performance on the basis of the sequencing_summary file produced by MinKNOW or Guppy (Albacore in the past). With the transition to (Python based) EPI2ME Labs and the deprecation of the original tutorial this workflow is being maintained to support the requirements of R-aficionados.

Instead of using the packaged and toy dataset, let’s use a slightly more robust dataset to show what the tool can really do.

aws.s3::save_object(
   "/gm24385_2020.11/flowcells/20201026_1645_6B_PAG07165_d42912aa/sequencing_summary_PAG07165_2dfda515.txt", 
   bucket = "s3://ont-open-data/", 
   region="eu-west-1")
library(floundeR)
sequencing_summary <- "sequencing_summary_PAG07165_2dfda515.txt"
seqsum <- SequencingSummary$new(sequencing_summary)
seqsum$flowcell$density_data$plot