IsomirDataSeqFromFiles {isomiRs} | R Documentation |
This function parses output of seqbuster tool to allow isomiRs/miRNAs analysis of samples in different groups such as characterization, differential expression and clustering. It creates an isomiRs::IsomirDataSeq object.
IsomirDataSeqFromFiles(files, coldata, rate = 0.2, canonicalAdd = TRUE, uniqueMism = TRUE, uniqueHits = FALSE, design = ~1L, minHits = 1L, header = TRUE, skip = 0, quiet = TRUE, ...) IsomirDataSeqFromRawData(rawdata, coldata, design = ~1L, ...)
files |
files with the output of seqbuster tool |
coldata |
data frame containing groups for each sample |
rate |
minimum counts fraction to consider a mismatch a real mutation |
canonicalAdd |
|
uniqueMism |
|
uniqueHits |
|
design |
a |
minHits |
Minimum number of reads in the sample to consider it in the final matrix. |
header |
boolean to indicate files contain headers |
skip |
skip first line when reading files |
quiet |
boolean indicating to print messages
while reading files. Default |
... |
arguments provided to
|
rawdata |
data.frame stored in metadata slot of IsomirDataSeq object. |
This function parses the output of http://seqcluster.readthedocs.org/mirna_annotation.html for each sample to create a count matrix for isomiRs, miRNAs or isomiRs grouped in types (i.e all sequences with variations at 5' but ignoring any other type). It creates isomiRs::IsomirDataSeq object (see link to example usage of this class) to allow visualization, queries, differential expression analysis and clustering. To create the isomiRs::IsomirDataSeq, it parses the isomiRs files, and generates an initial matrix having all isomiRs detected among samples. As well, it creates a summary for each isomiR type (trimming, addition and substitution) to visualize general isomiRs distribution.
IsomirDataSeq class object.
path <- system.file("extra", package="isomiRs") fn_list <- list.files(path, full.names = TRUE) de <- data.frame(row.names=c("f1" , "f2"), condition = c("newborn", "newborn")) ids <- IsomirDataSeqFromFiles(fn_list, coldata=de) head(counts(ids)) IsomirDataSeqFromRawData(metadata(ids)[["rawData"]], de)