subdivide_data {transite} | R Documentation

## Subdivides Sequences into n Bins

### Description

Preprocessing function for SPMA, divides transcript sequences into n bins.

### Usage

    subdivide_data(sorted_transcript_sequences, n_bins = 40)

### Arguments

`sorted_transcript_sequences` | character vector of named sequences (names are usually RefSeq identifiers and sequence region labels, e.g., "NM_1_DUMMY|3UTR"). It is important that the sequences are already sorted by fold change, signal-to-noise ratio or any other meaningful measure.
`n_bins` | specifies the number of bins in which the sequences will be divided, valid values are between 7 and 100

### Value

An array of `n_bins` length, containing the binned sequences

### See Also

Other SPMA functions: `classify_spectrum()`, `run_kmer_spma()`, `run_matrix_spma()`, `score_spectrum()`

### Examples

    # toy example
    toy_seqs <- c(
      "CAACAGCCUUAAUU", "CAGUCAAGACUCC", "CUUUGGGGAAU", "UCAUUUUAUUAAA",
      "AAUUGGUGUCUGGAUACUUCCCUGUACAU", "AUCAAAUUA", "AGAU", "GACACUUAAAGAUCCU",
      "UAGCAUUAACUUAAUG", "AUGGA", "GAAGAGUGCUCA", "AUAGAC", "AGUUC", "CCAGUAA"
    )
    # names are used as keys in the hash table (cached version only)
    # ideally sequence identifiers (e.g., RefSeq ids) and
    # sequence region labels (e.g., 3UTR for 3'-UTR)
    names(toy_seqs) <- c(
      "NM_1_DUMMY|3UTR", "NM_2_DUMMY|3UTR", "NM_3_DUMMY|3UTR",
      "NM_4_DUMMY|3UTR", "NM_5_DUMMY|3UTR", "NM_6_DUMMY|3UTR",
      "NM_7_DUMMY|3UTR",
      "NM_8_DUMMY|3UTR", "NM_9_DUMMY|3UTR", "NM_10_DUMMY|3UTR",
      "NM_11_DUMMY|3UTR",
      "NM_12_DUMMY|3UTR", "NM_13_DUMMY|3UTR", "NM_14_DUMMY|3UTR"
    )

    foreground_sets <- subdivide_data(toy_seqs, n_bins = 7)

    # example data set
    background_df <- transite:::ge$background_df
    # sort sequences by signal-to-noise ratio
    background_df <- dplyr::arrange(background_df, value)
    # character vector of named sequences
    background_seqs <- background_df$seq
    names(background_seqs) <- paste0(background_df$refseq, "|",
      background_df$seq_type)

    foreground_sets <- subdivide_data(background_seqs)

[Package transite version 1.10.0 Index]