highlineR: a tool for visualizing NGS datasets in R

Highlighter is a web-based tool maintained by the Los Alamos National Laboratory (LANL) HIV Sequence Database that makes it easy for investigators to visually scan their sequence alignments for compositional differences. However, it is inconvenient for users to use Highlighter to process a large number of alignment files as the tool only accepts a single file as input. In addition, the LANL website limits users to a maximum of 500 sequences per file, which can be problematic for users working with alignments derived from next-generation sequencing platforms. Furthermore, the tool does not visualize the frequencies of different sequence variants in a dataset.

highlineR is a free, open-source R package that provides users with accessible functions for batch-processing of sequence alignments, including NGS data, to generate plots similar to Highlighter. In addition, highlineR extends the Highlighter plot by varying line widths to represent variant frequencies in the data (see Usage).

Installation

The simplest method to install highlineR is to use the R devtools package:

# install.packages("devtools")  # if not already installed
require(devtools)
devtools::install_github("PoonLab/highlineR")

Usage

As a basic example of using highlineR, we’re going to load a number of anonymized data sets sets from a published study of HIV-1 diversity within patients:

require(highlineR)
#> Loading required package: highlineR
# use glob to retrieve paths to FASTA files
files <- Sys.glob('~/git/highlineR/inst/extdata/*.fasta')
highline(files[1:2])  # render the first two alignments

Each horizontal grey band represents a sequence variant. The area of the band is proportional to the number of times that variant occurs in the alignment. (It may be more intuitive to make height proportional to variant counts, but this causes problems when a variant occurs 1000 times or more!) By default, highlineR selects the most common variant to be the master (reference) sequence and places it at the top of the plot — it is also labeled with an (m).

Each band is decorated with coloured tick marks to indicate the locations of nucleotide (or amino acid) differences relative to the master sequence. A colour reference key (legend) is provided at the top of the plot.

Note that for the above example, the files were loaded from a developer directory. To load these same files from your installed package as a user, you’d have to replace the following line:

# files <- Sys.glob('~/git/highlineR/inst/extdata/*.fasta')
files <- Sys.glob(paste0(system.file(package='highlineR'), '/extdata/*.fasta'))

Background

A multiple sequence alignment (MSA) is a hypothesis about how residues (nucleotides or amino acids) in two or more sequences were derived from residues in a common ancestral sequence. By convention, each sequence is arranged horizontally in rows to be read from left to right, and evolutionarily-related (homologous) residues are arranged vertically in a column. It is possible for two or more sequences to be exactly identical. When this occurs, we refer to the shared sequence as the “sequence variant”, and the number of times this variant appears in the data as its “count”. (Note there is no established terminology for these features.) It is common practice to reduce a sequence alignment to the unique variants, especially when certain variants predominate the sample population. By doing so, however, we lose information on the relative abundance of variants.

If an MSA comprises a large number of sequences, it may become difficult to visualize the composition of the alignment. Highlighter plots were developed to reduce the information in the MSA by marking the location of residues that are different from the reference sequence, which has been selected by the user or the program. We refer to this reference sequence the master sequence. By default, the highline function selects the most common sequence variant to be the master.

The highline function is actually a high-level wrapper for several functions in highlineR. These lower level functions are exposed to the user, so you have the option of doing more extensive customization than highline will allow. Detailed instructions for using (and potentially modifying) these functions are provided in the CONTRIBUTING.md document.

In summary, the pipeline for generating a plot in highlineR are:

1. Initialize a highlineR session. This creates an R environment for storing the sequence alignment data sets.

2. Import one or more sequence alignments from the respective files. highlineR supports FASTA, FASTQ and CSV file formats.

3. Parse the raw sequence data from each file.

4. Compress the sequence data so that identical sequences are represented by a single copy annotated by the number of instances in the alignment.

5. Calculate the sequence differences from the “master sequence” and generate the Highlighter style plot.

Further examples

• Batch process a set of FASTA files and save the results as PDF files.

require(highlineR)
files <- Sys.glob('~/git/highlineR/inst/extdata/*.fasta')
for (f in files) {
  # prepare output file path
  of <- sub(pattern=".fasta$", replacement=".pdf", x=f)
  of <- sub("inst/extdata", "working", of)  # switch dir
  # start plot device to PDF file
  pdf(of, width=6, height=6, onefile=F)
  print(highline(f))
  dev.off()  # turn off plot device
}

• Annotate the Highlighter plot by transitions and transversions.

highline(files[3], mode='tvt')

• Annotate the Highlighter plot by non-synonymous and synonymous differences (note that the reading frame can be modified with the rf argument.)

highline(files[2], mode='svn')

Feature requests and issues

Please use our issue tracker to report problems that you encountered while using this package. Provide information on your operating system, R version and (ideally) a minimum reproducible example. If there’s some change or additional feature that you’d like to see in highlineR, you can also post a request on the issue tracker.