Can anyone help me trouble shoot how to fix this error message?
> dataNorm <- TCGAanalyze_Normalization(KIRC_preprocessed1, geneInfo = geneInfo,
+ method = "geneLength")
I Need about 0 seconds for this Complete Normalization Upper Quantile [Processing 80k elements /s]
Step 1 of 4: newSeqExpressionSet ...
Step 2 of 4: withinLaneNormalization ...
Error in names(y) <- 1:length(y) :
'names' attribute [2] must be the same length as the vector [0]
Timing stopped at: 0 0 0
Here's the code that produced the output above, thanks in advance:
devtools::install_github("Bioconductor-mirror/biomaRt", force = TRUE)
devtools::install_github(repo = "BioinformaticsFMRP/TCGAbiolinks", force = TRUE)
library(TCGAbiolinks)
library(biomaRt)
library(data.table)
library(dplyr)
library(DT)
query <- GDCquery(project = "TCGA-KIRC",
data.category = "Transcriptome Profiling",
data.type = "Gene Expression Quantification",
workflow.type = "HTSeq - Counts")
GDCdownload(query, chunks.per.download = 10)
KIRC_data1 <- GDCprepare(query,directory = "GDCdata",summarizedExperiment = T)
KIRC_preprocessed1<-TCGAanalyze_Preprocessing(KIRC_data1,cor.cut=0.6,
datatype="HTSeq - Counts")
dataNorm <- TCGAanalyze_Normalization(KIRC_preprocessed1, geneInfo = geneInfo,
method = "geneLength")
> dataNorm <- TCGAanalyze_Normalization(KIRC_preprocessed1, geneInfo = geneInfo,
+ method = "geneLength")
I Need about 0 seconds for this Complete Normalization Upper Quantile [Processing 80k elements /s]
Step 1 of 4: newSeqExpressionSet ...
Step 2 of 4: withinLaneNormalization ...
Error in names(y) <- 1:length(y) :
'names' attribute [2] must be the same length as the vector [0]
Timing stopped at: 0 0 0
Here's the code that produced the output above, thanks in advance:
devtools::install_github("Bioconductor-mirror/biomaRt", force = TRUE)
devtools::install_github(repo = "BioinformaticsFMRP/TCGAbiolinks", force = TRUE)
library(TCGAbiolinks)
library(biomaRt)
library(data.table)
library(dplyr)
library(DT)
query <- GDCquery(project = "TCGA-KIRC",
data.category = "Transcriptome Profiling",
data.type = "Gene Expression Quantification",
workflow.type = "HTSeq - Counts")
GDCdownload(query, chunks.per.download = 10)
KIRC_data1 <- GDCprepare(query,directory = "GDCdata",summarizedExperiment = T)
KIRC_preprocessed1<-TCGAanalyze_Preprocessing(KIRC_data1,cor.cut=0.6,
datatype="HTSeq - Counts")
dataNorm <- TCGAanalyze_Normalization(KIRC_preprocessed1, geneInfo = geneInfo,
method = "geneLength")