Wrapper for `MotifPeeker::summit_to_motif` to get motif-summit distances
for all peaks and motifs, generating a data.frame suitable
for plots.
Usage
get_df_distances(
result,
user_motifs,
genome_build,
out_dir = tempdir(),
workers = 1,
meme_path = NULL,
verbose = FALSE
)Arguments
- result
A
listwith the following elements:- peaks
A
listof peak files generated usingread_peak_file.- alignments
A
listof alignment files.- exp_type
A
charactervector of experiment types.- exp_labels
A
charactervector of experiment labels.- read_count
A
numericvector of read counts.- peak_count
A
numericvector of peak counts.
- user_motifs
A
listwith the following elements:- motifs
A
listof motif files.- motif_labels
A
charactervector of motif labels.
- genome_build
A character string with the abbreviated genome build name, or a BSGenome object. At the moment, only
hg38andhg19are supported as abbreviated input.- out_dir
A
charactervector of output directory.- workers
An integer specifying the number of threads to use for parallel processing. (default = 1)
IMPORTANT: For each worker, please ensure a minimum of 6GB of memory (RAM) is available asdenovo_motif_discoveryis memory-intensive.- meme_path
path to
meme/bin/(optional). Defaut:NULL, searches "MEME_PATH" environment variable or "meme_path" option for path to "meme/bin/".- verbose
A logical indicating whether to print verbose messages while running the function. (default = FALSE)
Value
A data.frame with the following columns:
- exp_label
Experiment labels.
- exp_type
Experiment types.
- motif_indice
Motif indices.
- distance
Distances between peak summit and motif.
See also
Other generate data.frames:
get_df_enrichment()
Examples
if (memes::meme_is_installed()) {
data("CTCF_ChIP_peaks", package = "MotifPeeker")
data("motif_MA1102.3", package = "MotifPeeker")
data("motif_MA1930.2", package = "MotifPeeker")
input <- list(
peaks = CTCF_ChIP_peaks,
exp_type = "ChIP",
exp_labels = "CTCF",
read_count = 150,
peak_count = 100
)
motifs <- list(
motifs = list(motif_MA1930.2, motif_MA1102.3),
motif_labels = list("MA1930.2", "MA1102.3")
)
if (requireNamespace("BSgenome.Hsapiens.UCSC.hg38")) {
genome_build <- BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38
distances_df <- get_df_distances(input, motifs, genome_build,
workers = 1)
print(distances_df)
}
}
#> exp_label exp_type motif_indice distance
#> 1 CTCF ChIP 1 24.0
#> 2 CTCF ChIP 1 -26.0
#> 3 CTCF ChIP 1 -20.0
#> 4 CTCF ChIP 1 21.0
#> 5 CTCF ChIP 1 -3.0
#> 6 CTCF ChIP 1 -18.0
#> 7 CTCF ChIP 1 14.0
#> 8 CTCF ChIP 1 2.0
#> 9 CTCF ChIP 1 -20.0
#> 10 CTCF ChIP 1 17.0
#> 11 CTCF ChIP 1 -27.0
#> 12 CTCF ChIP 1 -4.0
#> 13 CTCF ChIP 1 5.0
#> 14 CTCF ChIP 1 -17.0
#> 15 CTCF ChIP 1 8.0
#> 16 CTCF ChIP 1 -13.0
#> 17 CTCF ChIP 1 -5.0
#> 18 CTCF ChIP 1 14.0
#> 19 CTCF ChIP 1 25.0
#> 20 CTCF ChIP 1 0.0
#> 21 CTCF ChIP 1 14.0
#> 22 CTCF ChIP 1 -29.0
#> 23 CTCF ChIP 1 -245.0
#> 24 CTCF ChIP 1 3.0
#> 25 CTCF ChIP 1 16.0
#> 26 CTCF ChIP 1 -32.0
#> 27 CTCF ChIP 1 28.0
#> 28 CTCF ChIP 1 -22.0
#> 29 CTCF ChIP 1 -5.0
#> 30 CTCF ChIP 1 -7.0
#> 31 CTCF ChIP 1 2.0
#> 32 CTCF ChIP 1 -9.0
#> 33 CTCF ChIP 1 -116.0
#> 34 CTCF ChIP 1 11.0
#> 35 CTCF ChIP 1 1.0
#> 36 CTCF ChIP 1 -82.0
#> 37 CTCF ChIP 1 -22.0
#> 38 CTCF ChIP 1 -3.0
#> 39 CTCF ChIP 1 45.0
#> 40 CTCF ChIP 1 5.0
#> 41 CTCF ChIP 1 -3.0
#> 42 CTCF ChIP 1 9.0
#> 43 CTCF ChIP 1 -7.0
#> 44 CTCF ChIP 1 -168.0
#> 45 CTCF ChIP 1 119.0
#> 46 CTCF ChIP 1 74.0
#> 47 CTCF ChIP 1 -1.0
#> 48 CTCF ChIP 1 2.0
#> 49 CTCF ChIP 1 -26.0
#> 50 CTCF ChIP 1 15.0
#> 51 CTCF ChIP 1 1.0
#> 52 CTCF ChIP 1 -9.0
#> 53 CTCF ChIP 1 -70.0
#> 54 CTCF ChIP 1 1.0
#> 55 CTCF ChIP 1 22.0
#> 56 CTCF ChIP 1 -95.0
#> 57 CTCF ChIP 1 -13.0
#> 58 CTCF ChIP 1 16.0
#> 59 CTCF ChIP 1 30.0
#> 60 CTCF ChIP 1 2.0
#> 61 CTCF ChIP 1 2.0
#> 62 CTCF ChIP 1 -31.0
#> 63 CTCF ChIP 1 -9.0
#> 64 CTCF ChIP 1 -53.0
#> 65 CTCF ChIP 1 -64.0
#> 66 CTCF ChIP 1 -115.0
#> 67 CTCF ChIP 1 13.0
#> 68 CTCF ChIP 1 -3.0
#> 69 CTCF ChIP 1 -5.0
#> 70 CTCF ChIP 1 -10.0
#> 71 CTCF ChIP 1 34.0
#> 72 CTCF ChIP 1 -21.0
#> 73 CTCF ChIP 1 49.0
#> 74 CTCF ChIP 1 6.0
#> 75 CTCF ChIP 1 -24.0
#> 76 CTCF ChIP 1 8.0
#> 77 CTCF ChIP 1 -8.0
#> 78 CTCF ChIP 1 -8.0
#> 79 CTCF ChIP 1 -35.0
#> 80 CTCF ChIP 1 12.0
#> 81 CTCF ChIP 1 7.0
#> 82 CTCF ChIP 1 12.0
#> 83 CTCF ChIP 1 -21.0
#> 84 CTCF ChIP 1 -24.0
#> 85 CTCF ChIP 1 35.0
#> 86 CTCF ChIP 1 -34.0
#> 87 CTCF ChIP 1 -42.0
#> 88 CTCF ChIP 1 4.0
#> 89 CTCF ChIP 1 -46.0
#> 90 CTCF ChIP 1 -24.0
#> 91 CTCF ChIP 1 5.0
#> 92 CTCF ChIP 1 -9.0
#> 93 CTCF ChIP 1 0.0
#> 94 CTCF ChIP 1 -9.0
#> 95 CTCF ChIP 1 -11.0
#> 96 CTCF ChIP 1 3.0
#> 97 CTCF ChIP 1 -3.0
#> 98 CTCF ChIP 1 -9.0
#> 99 CTCF ChIP 1 -37.0
#> 100 CTCF ChIP 1 11.0
#> 101 CTCF ChIP 1 -15.0
#> 102 CTCF ChIP 1 1.0
#> 103 CTCF ChIP 1 -96.0
#> 104 CTCF ChIP 1 -7.0
#> 105 CTCF ChIP 1 -9.0
#> 106 CTCF ChIP 1 1.0
#> 107 CTCF ChIP 1 12.0
#> 108 CTCF ChIP 1 7.0
#> 109 CTCF ChIP 1 -19.0
#> 110 CTCF ChIP 1 -22.0
#> 111 CTCF ChIP 1 25.0
#> 112 CTCF ChIP 1 -29.0
#> 113 CTCF ChIP 1 -52.0
#> 114 CTCF ChIP 2 6.5
#> 115 CTCF ChIP 2 -14.5
#> 116 CTCF ChIP 2 63.5
#> 117 CTCF ChIP 2 17.5
#> 118 CTCF ChIP 2 -122.5
#> 119 CTCF ChIP 2 -126.5
#> 120 CTCF ChIP 2 21.5
#> 121 CTCF ChIP 2 -6.5
#> 122 CTCF ChIP 2 -122.5
#> 123 CTCF ChIP 2 -16.5
#> 124 CTCF ChIP 2 -10.5
#> 125 CTCF ChIP 2 -5.5
#> 126 CTCF ChIP 2 -19.5
#> 127 CTCF ChIP 2 -59.5
#> 128 CTCF ChIP 2 -9.5
#> 129 CTCF ChIP 2 -20.5
#> 130 CTCF ChIP 2 11.5
#> 131 CTCF ChIP 2 -20.5
#> 132 CTCF ChIP 2 8.5
#> 133 CTCF ChIP 2 -10.5
#> 134 CTCF ChIP 2 5.5
#> 135 CTCF ChIP 2 -79.5
#> 136 CTCF ChIP 2 5.5
#> 137 CTCF ChIP 2 -13.5
#> 138 CTCF ChIP 2 90.5
#> 139 CTCF ChIP 2 0.5
#> 140 CTCF ChIP 2 -5.5
#> 141 CTCF ChIP 2 33.5
#> 142 CTCF ChIP 2 -2.5
#> 143 CTCF ChIP 2 94.5
#> 144 CTCF ChIP 2 87.5
#> 145 CTCF ChIP 2 -24.5
#> 146 CTCF ChIP 2 72.5
#> 147 CTCF ChIP 2 -23.5
#> 148 CTCF ChIP 2 2.5
#> 149 CTCF ChIP 2 1.5
#> 150 CTCF ChIP 2 -120.5
#> 151 CTCF ChIP 2 -10.5
#> 152 CTCF ChIP 2 -93.5
#> 153 CTCF ChIP 2 -11.5
#> 154 CTCF ChIP 2 -4.5
#> 155 CTCF ChIP 2 88.5
#> 156 CTCF ChIP 2 -6.5
#> 157 CTCF ChIP 2 11.5
#> 158 CTCF ChIP 2 4.5
#> 159 CTCF ChIP 2 104.5
#> 160 CTCF ChIP 2 128.5