ggDNAvis (version 0.3.2)

merge_fastq_with_metadata: Merge FASTQ data with metadata

Description

Merge a dataframe of sequence and quality data (as produced by read_fastq() from an unmodified FASTQ file) with a dataframe of metadata, reverse-complementing sequences if required such that all reads are now in the forward direction. merge_methylation_with_metadata() is the equivalent function for working with FASTQs that contain DNA modification information.

FASTQ dataframe must contain columns of "read" (unique read ID), "sequence" (DNA sequence), and "quality" (FASTQ quality score). Other columns are allowed but not required, and will be preserved unaltered in the merged data.

Metadata dataframe must contain "read" (unique read ID) and "direction" (read direction, either "forward" or "reverse" for each read) columns, and can contain any other columns with arbitrary information for each read. Columns that might be useful include participant ID and family designations so that each read can be associated with its participant and family.

Important: A key feature of this function is that it uses the direction column from the metadata to identify which rows are reverse reads. These reverse reads will then be reversed-complemented and have quality scores reversed such that all reads are in the forward direction, ideal for consistent analysis or visualisation. The output columns are "forward_sequence" and "forward_quality". Calls reverse_sequence_if_needed() and reverse_quality_if_needed() to implement the reversing - see documentation for these functions for more details.

Usage

merge_fastq_with_metadata(
  fastq_data,
  metadata,
  reverse_complement_mode = "DNA"
)

Value

dataframe. A merged dataframe containing all columns from the input dataframes, as well as forward versions of sequences and qualities.

Arguments

fastq_data

dataframe. A dataframe contaning sequence and quality data, as produced by read_fastq().

Must contain a read id column (must be called "read"), a sequence column ("sequence"), and a quality column ("quality"). Additional columns are fine and will simply be included unaltered in the merged dataframe.

metadata

dataframe. A dataframe containing metadata for each read in fastq_data.

Must contain a "read" column identical to the column of the same name in fastq_data, containing unique read IDs (this is used to merge the dataframes). Must also contain a "direction" column of "forward" and "reverse" (e.g. c("forward", "forward", "reverse")) indicating the direction of each read.

Important: Reverse reads will have their sequence and quality scores reversed such that every output read is now forward. These will be stored in columns called "forward_sequence" and "forward_quality".

See reverse_sequence_if_needed() and reverse_quality_if_needed() documentation for details of how the reversing is implemented.

reverse_complement_mode

character. Whether reverse-complemented sequences should be converted to DNA (i.e. A complements to T) or RNA (i.e. A complements to U). Must be either "DNA" or "RNA". Only affects reverse-complemented sequences. Sequences that were forward to begin with are not altered.

Uses reverse_complement() via reverse_sequence_if_needed().

Examples

## Locate files
fastq_file <- system.file("extdata",
                          "example_many_sequences_raw.fastq",
                          package = "ggDNAvis")
metadata_file <- system.file("extdata",
                             "example_many_sequences_metadata.csv",
                             package = "ggDNAvis")

## Read files
fastq_data <- read_fastq(fastq_file)
metadata   <- read.csv(metadata_file)

## Merge data (including reversing if needed)
merge_fastq_with_metadata(fastq_data, metadata)