IsomirDataSeqFromFiles {isomiRs} | R Documentation

## Loads miRNA annotation from seqbuster tool or pre-processed data.

### Description

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.

### Usage

    IsomirDataSeqFromFiles(
      files,
      coldata,
      rate = 0.2,
      canonicalAdd = TRUE,
      uniqueMism = TRUE,
      uniqueHits = FALSE,
      design = ~1L,
      minHits = 1L,
      header = TRUE,
      skip = 0,
      quiet = TRUE,
      ...
    )

### Arguments

`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` | `boolean` only keep A/T non-template addition. All non-template nucleotides at the 3' end will be removed if they contain C/G nts.
`uniqueMism` | `boolean` only keep mutations that have a unique hit to one miRNA molecule. For instance, if the sequence map to two different miRNAs, then it would be removed.
`uniqueHits` | `boolean` whether filtering ambigous sequences or not.
`design` | a `formula` to pass to DESeq2::DESeqDataSet
`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 `FALSE`.
`...` | arguments provided to `SummarizedExperiment` and IsomirDataSeqFromRawData. including rowData.

### Details

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.

### Value

IsomirDataSeq class object.

### Examples

    path <- system.file("extra", package="isomiRs")
    fn_list <- list.files(path, pattern="mirna", 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)

[Package isomiRs version 1.16.2 Index]