The frame function is one of the two main workhorses in the denoising pipeline. # "Available in the current DNAseq object:" Print("Available in the current DNAseq object:") #can always check to see the available components with the names function As data are generated by the denoising process, they can also be accessed using this notation. The raw sequence, phred score and name can then be accessed through the dollar sign notation. # attcaaccaatcataaagatattgg.tgattttttggtcaccctgaagttt i = 33 #the row number from the example dataframe to be analyzed in the single sequence demonstrationĮx = DNAseq(data$sequence], name = data$header_data], phred = data$quality]) The debar denoising pipeline is built around the custom DNAseq object, which is used to store the input sequence data and the outputs generated by the denoising process.īelow the varible ' ex' will store a DNAseq object, with the raw sequence, the name of the sequence (in this case the read id) and optionally the PHRED quality scores as well. #head(data) - to view the first few records fastq_example_file = system.file('extdata/coi_sequel_data_', package = 'debar') These functions produce dataframes with columns containing the header data, sequence data and PHRED quality scores (for fastq only - there is an option to discard the quality scores if they are not of interest to the user). The read_fasta and read_fastq functions allow users to read data into R for denoising. All of the discussed parameters for these individual components can be passed to the denoise function. It goes through the processing of a single sequence, step-by-step. This vignette contains a detailed walk-through of the denoise algorithm. Denoiser pipeline - components and walk-through library(debar)ĭenoiser pipeline - components and walk-through
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