Description Usage Arguments Details Value Author(s) See Also Examples
constructor function for ballgown objects
1 2 3 4 5 6 7 8 9 |
samples |
vector of file paths to folders containing sample-specific
ballgown data (generated by |
dataDir |
file path to top-level directory containing sample-specific
folders with ballgown data in them. Only used if |
samplePattern |
regular expression identifying the subdirectories of\
|
bamfiles |
optional vector of file paths to read alignment files for
each sample. If provided, make sure to sort properly (e.g., in the same
order as |
pData |
optional |
verbose |
if |
meas |
character vector containing either "all" or one or more of: "rcount", "ucount", "mrcount", "cov", "cov_sd", "mcov", "mcov_sd", or "FPKM". The resulting ballgown object will only contain the specified expression measurements, for the appropriate features. See vignette for which expression measurements are available for which features. "all" creates the full object. |
Because experimental data is recorded so variably, it is the user's
responsibility to format pData
correctly. In particular, it's
really important that the rows of pData
(corresponding to samples)
are ordered the same way as samples
or the
dataDir
/samplePattern
combo. You can run
list.files(path = dataDir, pattern = samplePattern)
to see the sample
order if samples
was not used.
If you are creating a ballgown object for a large experiment, this function may run slowly and use a large amount of RAM. We recommend running this constructor as a batch job and saving the resulting ballgown object as an rda file. The rda file usually has reasonable size on disk, and the object in it shouldn't take up too much RAM when loaded, so the time and memory use in creating the object is a one-time cost.
an object of class ballgown
Leonardo Collado-Torres, Alyssa Frazee
ballgownrsem
, for loading RSEM output into a ballgown
object
1 2 3 | bg = ballgown(dataDir=system.file('extdata', package='ballgown'),
samplePattern='sample')
pData(bg) = data.frame(id=sampleNames(bg), group=rep(c(1,0), each=10))
|
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