View source: R/computeRefTissue.R
computeRefTissue | R Documentation |
Compute reference control samples from OCTAD database using precomputed EncoderDF
models.
computeRefTissue(case_id = NULL, adjacent = FALSE, source = "octad", n_varGenes = 500, method = c("varGenes",'random'), expSet = NULL, control_size = length(case_id), outputFolder = NULL, cor_cutoff = "0", output = TRUE)
case_id |
vector of cases used to compute references. |
source |
by default set |
adjacent |
by default set to |
expSet |
input for expression matrix. By default NULL, since autoencoder results are used. |
n_varGenes |
number of genes used to select control cases. |
method |
one of two options is avaliable. |
control_size |
number of control samples to be selected. |
outputFolder |
path to output folder. By default, the function produces result files in working directory. |
cor_cutoff |
cut-off for correlation values, by default |
output |
if |
Return
control_id |
a vector of an appropriate set of control samples. |
Besides, if output=TRUE
, two files are created in the working directory:
case_normal_corMatrix.csv |
contains pairwise correlation between case samples vs control samples. |
case_normal_median_cor.csv |
contains median correlation values with case samples for returned control samples. |
diffExp
.
#select data #load data.frame with samples included in the OCTAD database phenoDF=get_ExperimentHub_data('EH7274') HCC_primary=subset(phenoDF,cancer=='Liver Hepatocellular Carcinoma'& sample.type == 'primary'&data.source == 'TCGA') #select cases case_id=HCC_primary$sample.id #computing reference tissue, by default using small autoEncoder, #but can use custom expression set, #by default output=TRUE and outputFolder option is empty, #which creates control corMatrix.csv to working directory control_id=computeRefTissue(case_id,outputFolder='',output=TRUE, expSet = "octad",control_size = 50)
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