TreeExp can be loaded the package in the usual way:
library('TreeExp')
TreeExp package takes in reads count data and gene information file in certain format:
Gene information file should be a text file in the shape of a matrix, in which values are separated by tabs. Rows
correspond to orthologous genes and columns
correspond to species names. And the values in the matrix are in the format of "GeneId:GeneLength
".
Reads count file should also be a text file in the matrix shape, Rows
correspond to orthologous genes which should be in one-to-one correspondence with rows in Gene information file, though gene ids are displayed in reads count file. Columns
correspond to sample names. Sample names are in format of "TaxaName_SubtaxaName_ReplicatesName
".
The example files are included in the TreeExp package, which can be found in extdata
folder in the package. One can load them in to take a look:
readsCount.table = read.table(system.file('extdata/tetraexp.read.counts.raw.txt', package='TreeExp'), header = T) head(readsCount.table[,1:10]) geneInfo.table = read.table(system.file('extdata/tetraexp.length.ortholog.txt', package='TreeExp'), header = T) head(geneInfo.table)
The construction function TEconstruct
loads in the reads count data file as well as a gene information file, and wraps them in a list of taxonExp objects (one taxaExp object).
In the package, we include files transformed from six tissues' expression reads count data of nine tetrapod species.
If you want to transform your own data, a transformation Perl script format2treeexp.pl
to format raw outputs of TopHat2 to "TreeExp compatible" is available at tools
folder in the package.
Or you can access the script at
https://github.com/hr1912/TreeExp/blob/master/tools/format2treeexp.pl
taxa.objects = TEconstruct(readCountsFP = system.file('extdata/tetraexp.read.counts.raw.txt', package='TreeExp'), geneInfoFP = system.file('extdata/tetraexp.length.ortholog.txt', package='TreeExp'), taxa = "all", subtaxa = c("Brain", "Cerebellum"), normalize = "TPM")
The construction process takes several minutes on a desktop computer depending on data size and hardware performance. Specify "taxa" and "subtaxa" options in the function when using partial of your data. The construction process will be faster. If you are hesitated to test the TreeExp, the package has already bundled a constructed object and you can load the object through:
data(tetraexp)
You can take a look at what the loaded objects:
print(tetraexp.objects, details = TRUE)
print(tetraexp.objects[[1]], printlen = 6) head(tetraexp.objects[[1]]$normExp.val)
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