Error in normalize.quantiles(dataset0) : vector types do not match in copyVector

[jmzvillarreal]

Hi, Thanks for developping this interesting tool. It seems that the error: Error in normalize.quantiles(dataset0) : vector types do not match in copyVector is quite common. I have tried : BiocManager::install("preprocessCore", configure.args="--disable-threading", force = TRUE) But it is not working... Could you please give some help on ow to debug it ? Many thanks. Jaime.

[jmzvillarreal]

I was able to fix the error by doing:

sc_data <- sc_data[["RNA"]]@counts sc_data <- Seurat_preprocessing(sc_data, min.cells= 1, min.features= 500, resolution= 0.2, dims_Neighbors= 1:20, dims_TSNE= 1:20, dims_UMAP= 1:20,verbose=TRUE)

TCGA <- read.table('TCGA_status_ConsensusClass.txt', header = TRUE, sep = '\t',row.names = 1) TCGA <- TCGA[-c(1,2),] TCGA <- TCGA %>% mutate_all(as.numeric) metadata <- read.table('Subtype_info.csv', header = TRUE, sep = ',') all(colnames(TCGA) == metadata$Sample)

TRUE

table(metadata$genotype)

NULL PRESENT

247 156

Execute Scissor to select the informative cells

phenotype <-metadata$genotype tag <- as.list(phenotype) infos <- Scissor(as.matrix(TCGA), sc_data, phenotype,tag=tag, alpha = 0.2, family = "binomial")

but now I am getting the following error:

Error in Scissor(as.matrix(TCGA), sc_data, phenotype, tag = tag, : The length differs between tags and phenotypes. Please check Scissor inputs and selected regression type. In addition: Warning messages: 1: In asMethod(object) : sparse->dense coercion: allocating vector of size 17.8 GiB 2: In asMethod(object) : sparse->dense coercion: allocating vector of size 66.0 GiB 3: In Scissor(as.matrix(TCGA), sc_data, phenotype, tag = tag, : NAs introduced by coercion

Any help would be appreciated !

[sunduanchen]

try tag=c('NULL','PRESENT') ?

On Tue, 30 May 2023 at 18:54, jmzvillarreal @.***> wrote:

I was able to fix the error by doing:

sc_data <- @.*** https://github.com/CountS sc_data <- Seurat_preprocessing(sc_data, min.cells= 1, min.features= 500, resolution= 0.2, dims_Neighbors= 1:20, dims_TSNE= 1:20, dims_UMAP= 1:20,verbose=TRUE)

TCGA <- read.table('TCGA_status_ConsensusClass.txt', header = TRUE, sep = '\t',row.names = 1) TCGA <- TCGA[-c(1,2),] TCGA <- TCGA %>% mutate_all(as.numeric) metadata <- read.table('Subtype_info.csv', header = TRUE, sep = ',') all(colnames(TCGA) == metadata$Sample) TRUE

table(metadata$genotype) NULL PRESENT 247 156 Execute Scissor to select the informative cells

phenotype <-metadata$genotype tag <- as.list(phenotype) infos <- Scissor(as.matrix(TCGA), sc_data, phenotype,tag=tag, alpha = 0.2, family = "binomial")

but now I am getting the following error:

Error in Scissor(as.matrix(TCGA), sc_data, phenotype, tag = tag, : The length differs between tags and phenotypes. Please check Scissor inputs and selected regression type. In addition: Warning messages: 1: In asMethod(object) : sparse->dense coercion: allocating vector of size 17.8 GiB 2: In asMethod(object) : sparse->dense coercion: allocating vector of size 66.0 GiB 3: In Scissor(as.matrix(TCGA), sc_data, phenotype, tag = tag, : NAs introduced by coercion

Any help would be appreciated !

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[jmzvillarreal]

Hi again, Thanks for the quick reply ... What you suggest was my first option, since it is how it appears in the tutorial... But the error is exactly the same ...