Remove sequences with non-identified bases (Ns) from a ShortReadQ object — n_filter • FastqCleaner
Description: This program is a wrapper to nFilter. It removes the sequences with a number of N's above a threshold value 'rm.N'. All the sequences with a number of N &gt; rm.N (N &gt;= rm.N) will be removed

# Remove sequences with non-identified bases (Ns) from a ShortReadQ object

`n_filter.Rd`

This program is a wrapper to `nFilter`. It removes the sequences with a number of N's above a threshold value 'rm.N'. All the sequences with a number of N > rm.N (N >= rm.N) will be removed

    n_filter(input, rm.N)

## Arguments

input | `ShortReadQ` object
rm.N | Threshold value of N's to remove a sequence from the output (sequences with number of Ns > threshold are removed) For example, if rm.N is 3, all the sequences with a number of Ns > 3 (Ns >= 4) will be removed

## Value

Filtered `ShortReadQ` object

## Examples

    require('Biostrings')
    require('ShortRead')

    # create 6 sequences of width 20
    set.seed(10)
    input <- random_seq(50, 20)

    # inject N's
    set.seed(10)
    input <- inject_letter_random(input, how_many_seqs = 1:30,
    how_many = 1:10)

    input <- DNAStringSet(input)

    # watch the N's frequency
    hist(letterFrequency(input, 'N'), breaks = 0:10,
    main  = 'Ns Frequency', xlab = '# Ns')
    # create qualities of width 20
    set.seed(10)
    input_q <- random_qual(50, 20)

    # create names
    input_names <- seq_names(50)

    # create ShortReadQ object
    my_read <- ShortReadQ(sread = input, quality = input_q, id = input_names)

    # apply the filter
    filtered <- n_filter(my_read, rm.N = 3)

    # watch the filtered sequences
    sread(filtered)#>   A DNAStringSet instance of length 40
    #>      width seq
    #>  [1]    20 TGGTCCGGTGTTCTGGCGGA
    #>  [2]    20 ATAGGTACAGTCCAGTAATT
    #>  [3]    20 GCCTCCCGCAGACGCTGGGT
    #>  [4]    20 CCGGAATGCCCTTTCTGAGC
    #>  [5]    20 AGCTCCAGCCGTTTGACTTC
    #>  ...   ... ...
    #> [36]    20 ATCAATTCGTCCTGAGTTCA
    #> [37]    20 AGCCCACTGGGGGAGAACGC
    #> [38]    20 CGAGGGAAGCCAAGCAAAGC
    #> [39]    20 GGGAAGATCCGTTACTCTTT
    #> [40]    20 AGGAATTCCCGGAAGTCGCA
    # watch the N's frequency
    hist(letterFrequency(sread(filtered), 'N'),
    main = 'Ns distribution', xlab = '')