@@ -43,7 +43,6 @@ library(NbClust)
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library(fpc )
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library(class )
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-
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source(" analysis_library.R" )
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# Load the data
@@ -266,7 +265,8 @@ write.table(data_bulk,
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# Run DrImpute
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# ---------------------------------------------------------------------------------
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- dir.create(file.path(" imputation_drimpute_data/" ))
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+ dir.create(file.path(" imputation_drimpute_data/" ),
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+ showWarnings = FALSE )
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data_sc <- as.matrix(fread(" /data_all/sc_data_ES.csv" ))
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@@ -279,7 +279,8 @@ saveRDS(extdata, file = "imputation_drimpute_data/data_drimpute_imputation.rds")
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# ---------------------------------------------------------------------------------
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# create the folder of the imputation result
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- dir.create(file.path(" imputation_drimpute_data/" ))
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+ dir.create(file.path(" imputation_drimpute_data/" ),
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+ showWarnings = FALSE )
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# load the data
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data_sc <- as.matrix(fread(" /data_all/sc_data_ES.csv" ))
@@ -311,8 +312,8 @@ write.table(tmp1, file = "imputation_drimpute_data/data_scimpute_imputation.csv"
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# cwd = os.getwd()
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#
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- # if not os.path.exists(cwd+"/magic_data "):
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- # os.makedirs(cwd+"/magic_data ")
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+ # if not os.path.exists(cwd+"/imputation_magic_data "):
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+ # os.makedirs(cwd+"/imputation_magic_data ")
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#
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#
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# X = pd.read_csv(cwd + "/data_all/sc_data_ES.csv",sep = ',',header=None)
@@ -331,7 +332,8 @@ write.table(tmp1, file = "imputation_drimpute_data/data_scimpute_imputation.csv"
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# ---------------------------------------------------------------------------------
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# create the folder
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- dir.create(file.path(" /imputation_scrabble_data/" ))
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+ dir.create(file.path(" /imputation_scrabble_data/" ),
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+ showWarnings = FALSE )
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# load the scRNAseq data
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data_sc <- as.matrix(fread(paste0(cwd ," /data_all/sc_data_ES.csv" )))
@@ -392,7 +394,7 @@ data_sc_scimpute <- read.table(file = "imputation_scimpute_data/data_scimpute_im
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data_sc_scimpute <- log10(data_sc_scimpute + 1 )
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# load the imputed data of MAGIC
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- data_sc_magic <- read.table(file = " magic_data /data_magic_imputation.csv" ,
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+ data_sc_magic <- read.table(file = " imputation_magic_data /data_magic_imputation.csv" ,
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header = FALSE , sep = " ," ,
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stringsAsFactors = FALSE )
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