methRead {methylKit} | R Documentation

## read file(s) to methylRaw or methylRawList objects

### Description

The function reads a list of files or single files with methylation information for bases/region in the genome and creates a methylrawList or methylraw object. The information can be stored as flat file database by creating a methylrawlistDB or methylrawDB object.

### Usage

    methRead(
      location,
      sample.id,
      assembly,
      dbtype = NA,
      pipeline = "amp",
      header = TRUE,
      skip = 0,
      sep = "\t",
      context = "CpG",
      resolution = "base",
      treatment = NA,
      dbdir = getwd(),
      mincov = 10
    )

    ## S4 method for signature 'character,character,character'
    methRead(
      location,
      sample.id,
      assembly,
      dbtype,
      pipeline,
      header,
      skip,
      sep,
      context,
      resolution,
      dbdir,
      mincov
    )

    ## S4 method for signature 'character,ANY,ANY'
    methRead(
      location,
      sample.id,
      assembly,
      dbtype,
      pipeline,
      header,
      skip,
      sep,
      context,
      resolution,
      dbdir,
      mincov
    )

    ## S4 method for signature 'list,list,character'
    methRead(
      location,
      sample.id,
      assembly,
      dbtype = NA,
      pipeline = "amp",
      header = TRUE,
      skip = 0,
      sep = "\t",
      context = "CpG",
      resolution = "base",
      treatment = NA,
      dbdir = getwd(),
      mincov = 10
    )

    ## S4 method for signature 'list,ANY,ANY'
    methRead(
      location,
      sample.id,
      assembly,
      dbtype = NA,
      pipeline = "amp",
      header = TRUE,
      skip = 0,
      sep = "\t",
      context = "CpG",
      resolution = "base",
      treatment = NA,
      dbdir = getwd(),
      mincov = 10
    )

### Arguments

`location` | file location(s), either a list of locations (each a character string) or one location string
`sample.id` | sample.id(s)
`assembly` | a string that defines the genome assembly such as hg18, mm9. this is just a string for book keeping. It can be any string. Although, when using multiple files from the same assembly, this string should be consistent in each object.
`dbtype` | type of the flat file database, currently only option other than NA is "tabix". When "tabix" is given the objects are stored in tabix files, which are compressed and indexed. The default value is NA, in which case the objects are stored in memory.
`pipeline` | name of the alignment pipeline, it can be either "amp", "bismark","bismarkCoverage", "bismarkCytosineReport" or a list (default:'amp'). The methylation text files generated from other pipelines can be read as generic methylation text files by supplying a named `list` argument as "pipeline" argument. The named `list` should containt column numbers which denotes which column of the text file corresponds to values and genomic location of the methylation events. See Details for more on possible values for this argument.
`header` | if the input file has a header or not (default: TRUE)
`skip` | number of lines to skip when reading. Can be set to 1 for bed files with track line (default: 0)
`sep` | seperator between fields, same as `read.table` argument (default: "\t")
`context` | methylation context string, ex: CpG,CHG,CHH, etc. (default:CpG)
`resolution` | designates whether methylation information is base-pair resolution or regional resolution. allowed values 'base' or 'region'. Default 'base'
`treatment` | a vector contatining 0 and 1 denoting which samples are control which samples are test
`dbdir` | directory where flat file database(s) should be stored, defaults to getwd(), working directory.
`mincov` | minimum read coverage to be included in the methylKit objects. defaults to 10. Any methylated base/region in the text files below the mincov value will be ignored.

### Value

returns methylRaw, methylRawList, methylRawDB, methylRawListDB object

### Details

The output of `methRead` is determined by specific input arguments,as there are `location`, `sample.id`, `assembly` and `dbtype`. The first three are obligatory, while if the last argument is given database features are enabled. If then `location` refers to an uncompressed file the function will create a flat file database and the associated methylRawDB object will link to this database. If then `location` refers to an earlier created database file then the object will directly link to this database, skipping the preprocessing steps.

When `pipeline` argument is a list, it is exptected to provide a named list with following names. 'fraction' is a logical value, denoting if the column frequency of Cs has a range from [0-1] or [0-100]. If true it assumes range is [0-1]. 'chr.col" is the number of the column that has chrosome string. 'start.col' is the number of the column that has start coordinate of the base/region of the methylation event. 'end.col' is the number of the column that has end coordinate of the base/region of the methylation event. 'coverage.col' is the number of the column that has read coverage values. 'strand.col' is the number of the column that has strand information, the strand information in the file has to be in the form of '+' or '-', 'freqC.col' is the number of the column that has the frequency of Cs. See examples to see how to read a generic methylation text file.

Other possible values for `pipeline` argument are 'amp','bismark', 'bismarkCoverage' and 'bismarkCytosineReport'. For 'amp' and 'bismark' the function expects a tabular format shown in the webpage (http://github.com/al2na/methylKit). "amp" and "bismark" expect identical input and are kept for historical reasons. 'amp' was a pipeline used in Akalin et al. 2012 Plos Genetics paper, publicly available in googlecode.

Bismark aligner can output methylation information per base in multiple formats. With `pipeline='bismarkCoverage'`, the function reads bismark coverage files, which have chr,start,end, number of cytosines (methylated bases) and number of thymines (unmethylated bases) format. If bismark coverage files are used the function will not have the strand information,so beware of that fact. With `pipeline='bismarkCytosineReport'`, the function expects cytosine report files from Bismark, which have chr,start, strand, number of cytosines (methylated bases) , number of thymines (unmethylated bases),context and trinucletide context format.

The function can also read gzipped files. On unix systems, this is achieved by using `zcat filename` and feeding that into `data.table::fread` . On Windows, the file is first uncompressed then read into R using `data.table::fread`.

### Examples

    # this is a list of example files, ships with the package
    # for your own analysis you will just need to provide set of paths to files
    # you will not need the "system.file(..."  part
    file.list=list(
             system.file("extdata", "test1.myCpG.txt", package = "methylKit"),
             system.file("extdata", "test2.myCpG.txt", package = "methylKit"),
             system.file("extdata", "control1.myCpG.txt", package = "methylKit"),
             system.file("extdata", "control2.myCpG.txt", package = "methylKit")
             )

    # read the files to a methylRawList object: myobj
    myobj=methRead(file.list,
                sample.id=list("test1","test2","ctrl1","ctrl2"),
                assembly="hg18",treatment=c(1,1,0,0))

    # read one file as methylRaw object
    myobj=methRead( file.list[[1]],
                sample.id="test1",assembly="hg18")

    # read a generic text file containing CpG methylation values
    # let's first look at the content of the file
    generic.file=system.file("extdata", "generic1.CpG.txt",package = "methylKit")
    read.table(generic.file,header=TRUE)

    # And this is how you can read that generic file as a methylKit object
     myobj=methRead( generic.file,
                 pipeline=list(fraction=FALSE,chr.col=1,start.col=2,end.col=2,
                               coverage.col=4,strand.col=3,freqC.col=5),
                 sample.id="test1",assembly="hg18")

    # This creates tabix files that save methylation data
    # Without specified dbdir first creates a folder named the following
    # in working directory:
    # paste("methylDB",Sys.Date(),paste(sample(c(0:9, letters, LETTERS),3,
    # replace=TRUE),collapse=""))
    #
    # Then, saves tabix files from methylKit objects there
     myobj=methRead( file.list,
                   sample.id=list("test1","test2","ctrl1","ctrl2"),
                   assembly="hg18",treatment=c(1,1,0,0),
                   dbtype="tabix")

    # This creates a single tabix files that saves methylation data
    # first creates a "methylDB_objects" directory
    # Then, saves tabix file from methylKit objects there
     myobj=methRead(file.list[[1]],
                   sample.id="test1",
                   assembly="hg18",
                   dbtype="tabix",dbdir="methylDB_objects")

     # tidy up
     rm(myobj)
     unlink(list.files(pattern = "methylDB",full.names = TRUE),recursive = TRUE)

[Package methylKit version 1.16.1 Index]