RunBicluster {IRISFGM} | R Documentation |
This function will identify the Biclusters based on LTMG or Quantile normalization
RunBicluster(object, ...) .runBicluster( object = NULL, DiscretizationModel = "Quantile", OpenDual = FALSE, Extension = 1, NumBlockOutput = 100, BlockOverlap = 0.7, BlockCellMin = 15 ) ## S4 method for signature 'IRISFGM' RunBicluster( object = NULL, DiscretizationModel = "Quantile", OpenDual = FALSE, Extension = 1, NumBlockOutput = 100, BlockOverlap = 0.7, BlockCellMin = 15 )
object |
input IRIS-FGM object |
... |
other arguments passed to methods |
DiscretizationModel |
use different discretization method, including 'Quantile' and 'LTMG.' |
OpenDual |
the flag using the lower bound of condition number. Default: 5 percent of the gene number in current bicluster. |
Extension |
consistency level of the block (0.5-1.0], the minimum ratio between the number of identical valid symbols in a column and the total number of rows in the output. Default: 1.0. |
NumBlockOutput |
number of blocks to report. Default: 100. |
BlockOverlap |
filtering overlapping blocks. Default: 0.7. |
BlockCellMin |
minimum column width of the block. Default: 15 columns. |
It will generate a temporal file on local directory for processed data named 'tmp_expression.txt', discretized file named 'tmp_expression.txt.chars', and biclsuter block named 'tmp_expression.txt.chars.block'.
# based on LTMG discretization data("example_object") example_object<- RunLTMG(example_object,Gene_use = "200") example_object <- CalBinaryMultiSignal(example_object) # Due to generate intermedie files, please make sure to set working directory example_object <- RunBicluster(example_object, DiscretizationModel = 'LTMG', OpenDual = FALSE, NumBlockOutput = 1000, BlockOverlap = 0.7, BlockCellMin = 15)