Class that contains all isomiRs annotation for all samples

Description

The IsomirDataSeq is a subclass of SummarizedExperiment used to store the raw data, intermediate calculations and results of an miRNA/isomiR analysis. This class stores all raw isomiRs data for each sample, processed information, summary for each isomiR type, raw counts, normalized counts, and table with experimental information for each sample.

Details

IsomirDataSeqFromFiles creates this object using seqbuster output files.

Methods for this objects are counts to get count matrix and isoSelect for miRNA/isomiR selection. Functions available for this object are isoCounts for count matrix creation, isoNorm for normalization, isoDE for differential expression and isoPLSDA for clustering. isoPlot helps with basic expression plot.

metadata contains two lists: rawList is a list with same length than number of samples and stores the input files for each sample; isoList is a list with same length than number of samples and stores information for each isomiR type summarizing the different changes for the different isomiRs (trimming at 3', trimming a 5', addition and substitution). For instance, you can get the data stored in isoList for sample 1 and 5' changes with this code metadata(ids)[['isoList']][[1]]$t5sum.

Examples

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, design=de)

head(counts(ids))

Results

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> library(isomiRs)
Loading required package: DiscriMiner
Loading required package: IRanges
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: GenomicRanges
Loading required package: GenomeInfoDb
Loading required package: SummarizedExperiment
Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/isomiRs/IsomirDataSeq.Rd_%03d_medium.png", width=480, height=480)
> ### Name: IsomirDataSeq-class
> ### Title: Class that contains all isomiRs annotation for all samples
> ### Aliases: IsomirDataSeq IsomirDataSeq-class
> 
> ### ** Examples
> 
> 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, design=de)
> 
> head(counts(ids))
              f1 f2
hsa-let-7a-5p  0 19
hsa-let-7b-5p  1  6
hsa-let-7c-5p  5 64
hsa-let-7d-5p  0  1
hsa-let-7f-5p  8  8
hsa-let-7g-5p 74  4
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>