View source: R/utils_format_conversion.R
convert_to_bigWig | R Documentation |
Convert to BigWig
convert_to_bigWig(
df,
in_files = filepath(df, "pshifted"),
out_dir = file.path(libFolder(df), "bigwig"),
split.by.strand = TRUE,
split.by.readlength = FALSE,
seq_info = seqinfo(df),
weight = "score",
is_pre_collapsed = FALSE,
verbose = TRUE
)
df |
an ORFik |
in_files |
paths to input files, default pshifted files:
|
out_dir |
paths to output files, default
|
split.by.strand |
logical, default TRUE, split into forward and reverse strand RleList inside covRle object. |
split.by.readlength |
logical, default FALSE, split into files for each readlength, defined by readWidths(x) for each file. |
seq_info |
SeqInfo object, default |
weight |
integer, numeric or single length character. Default "score". Use score column in loaded in_files. |
is_pre_collapsed |
logical, default FALSE. Have you already collapsed reads with collapse.by.scores, so each positions is only in 1 GRanges object with a score column per readlength? Set to TRUE, only if you are sure, will give a speedup. |
verbose |
logical, default TRUE, message about library output status. |
invisible(NULL), files saved to disc
Other lib_converters:
convertLibs()
,
convert_bam_to_ofst()
,
convert_to_covRle()
,
convert_to_covRleList()
df <- ORFik.template.experiment()[10,]
## Usually do default folder, here we use tmpdir
folder_to_save <- file.path(tempdir(), "bigwig")
convert_to_bigWig(df, out_dir = folder_to_save)
fimport(file.path(folder_to_save, c("RFP_Mutant_rep2_forward.bigWig",
"RFP_Mutant_rep2_reverse.bigWig")))
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