Can not use QC_RLSC remove batch effect

MetaboAnalyst
,
1

i use MetaboAnalyst rmove batch effect，and my command is:
mSet ← PerformBatchCorrection(mSet,“QC_RLSC”,Method=“QC_RLSC”)
.
And issue says : Error in instrument_base_errors(loc ← eval_tidy(enquo(var), set_names(seq_along(vars), :
could not find function “instrument_base_errors”

how to fix it

2

Hi BaylorLyu,
Thanks for posting your questions. Can you please show me a reproducible example?
Cheers,
Zhiqiang Pang

3

Thanks for you reply. I use example data to learn how to remove batch effect, here is my code:

library(googledrive)
temp ← tempfile(fileext = “.csv”)
dl1 ← drive_download(
as_id(“1wEh2P81J_xFWJs5y4mq98-FsjxJ5wmBO”), path = temp, overwrite = TRUE)
library(googledrive);
temp ← tempfile(fileext = “.csv”)
dl2 ← drive_download(
as_id(“1KaBnSNRrirVPvpRxIubGCqpjX8asNeVA”), path = temp, overwrite = TRUE)
MetaboAna_Data ← t(read.csv(dl1$local_path,header = T));
colnames(MetaboAna_Data) ← MetaboAna_Data[1,];
MetaboAna_Data ← MetaboAna_Data[-1,];
MetaboAna_Data ← MetaboAna_Data[order(rownames(MetaboAna_Data)),];

meta_data ← read.csv(dl2$local_path);
meta_data ← meta_data[order(meta_data[,1]),c(1,2,4)];

Prepared_Data ← cbind(meta_data,MetaboAna_Data)[,-4];
write.csv(Prepared_Data,file = “IBD_BC_correction.csv”,row.names = F)
datapath ← paste0(getwd(),“/IBD_BC_correction.csv”)
library(“MetaboAnalystR”)
mSet<-InitDataObjects(“pktable”, “stat”, FALSE)
mSet<-Read.TextData(mSet, dl1$local_path, “col”, “disc”)
mSet<-SanityCheckData(mSet)
mSet<-ReplaceMin(mSet);
mSet<-FilterVariable(mSet, “iqr”, “F”, 25)
mSet<-PreparePrenormData(mSet)
mSet<-Normalization(mSet, “MedianNorm”, “LogNorm”, “NULL”, ratio=FALSE, ratioNum=20)
normalized_set ← mSet[[“dataSet”]][[“norm”]]
ordered_normalized_set ← normalized_set[order(row.names(normalized_set)), ]
meta_data ← read.csv(dl2$local_path)
new_normalized_set ← cbind(meta_data[,2:4], ordered_normalized_set)
write.csv(new_normalized_set,file = “new_normalized_set.csv”)
rm(mSet)
mSet ← InitDataObjects(“pktable”, “utils”, FALSE)
mSet ← Read.BatchDataTB(mSet, “new_normalized_set.csv”, “row”,missingEstimate = “rmean”)
mSet ← PerformBatchCorrection(mSet,“QC_RLSC”,Method=“QC_RLSC”)
[1] “Correcting using the QC_RLSC method !”
Error in instrument_base_errors(loc ← eval_tidy(enquo(var), set_names(seq_along(vars), :
could not find function “instrument_base_errors”
[1] “Your data or format is not valid! Please double check!”

This code can show issue again.

4

Hi BaylorLyu,

Thanks for sharing the code. The issue is related with the dependency on updated version of tidyselect package. I have fixed it. Please try it!

Cheers,
Zhiqiang Pang

5

Hello Zhiqiang,

Is there any way to remove batch effect through the website based MetaboAnalyst?

Many thanks

Zang

7

Hi Zhiqiang,

I run into a similar issue as BaylorLyu using the example data provided online.
[1] “Correcting with WaveICA…”
Error in log10(nrow(data), 2) :
2 arguments passed to ‘log10’ which requires 1
[1] “Your data or format is not valid! Please double check!”

Could you please tell me how to fix this issue?

Best,
Lisa

8

Hi Zang,Please find the Other Utilities Module from the Module select page, and then select “Batch Effect Correction” option from the dialog.
image

9

Hi Lisa, please give a reproduciable example for further checking. Read this post for troubleshooting.

Zhiqiang

10

Hi Lisa, I got your example from your email. I just fixed the issue. Now, you can try to reinstall the R pacakge and rerun it.
Here is the example code. I am post them just in case anyone else need it.

# Use Google API for data downloading peak feature data generated by FormatPeakList here.
# Please "install.packages('googledrive')" and "install.packages('httpuv')"first.
library(googledrive);
temp <- tempfile(fileext = ".csv")
# Please authorize your google account to access the data
dl1 <- drive_download(
  as_id("1wEh2P81J_xFWJs5y4mq98-FsjxJ5wmBO"), path = temp, overwrite =
    TRUE)

# Use Google API for data downloading meta data here.
# Please "install.packages('googledrive')" and "install.packages('httpuv')"first.
library(googledrive);
temp <- tempfile(fileext = ".csv")
# Please authorize your google account to access the data
dl2 <- drive_download(
  as_id("1KaBnSNRrirVPvpRxIubGCqpjX8asNeVA"), path = temp, overwrite =
    TRUE)

# Data preparation - read data in & transpose.
# This is a reference example for user to prepare their data.
# Please prepare your data table according to your data format.
MetaboAna_Data <- t(read.csv(dl1$local_path,header = T));
colnames(MetaboAna_Data) <- MetaboAna_Data[1,];
MetaboAna_Data <- MetaboAna_Data[-1,];
MetaboAna_Data <- MetaboAna_Data[order(rownames(MetaboAna_Data)),];

meta_data <- read.csv(dl2$local_path);
meta_data <- meta_data[order(meta_data[,1]),c(1,2,4)];

Prepared_Data <- cbind(meta_data,MetaboAna_Data)[,-4];
write.csv(Prepared_Data,file = "IBD_BC_correction.csv",row.names = F)
datapath <- paste0(getwd(),"/IBD_BC_correction.csv")

# Load the MetaboAnalystR package
library("MetaboAnalystR")

mSet<-InitDataObjects("pktable", "stat", FALSE)

mSet<-Read.TextData(mSet, dl1$local_path, "col", "disc")

mSet<-SanityCheckData(mSet)
mSet<-ReplaceMin(mSet);
mSet<-FilterVariable(mSet, "iqr", "F", 25)
mSet<-PreparePrenormData(mSet)
mSet<-Normalization(mSet, "MedianNorm", "LogNorm", "NULL", ratio=FALSE,
                    ratioNum=20)

### Data Orgnization
normalized_set <- mSet[["dataSet"]][["norm"]]
ordered_normalized_set <-
  normalized_set[order(row.names(normalized_set)), ]
### import metadata
meta_data <- read.csv(dl2$local_path)
new_normalized_set <- cbind(meta_data[,2:4], ordered_normalized_set);
write.csv(new_normalized_set,file =
            "NEW_new_normalized_set.csv") #changed it to my directory and read it in from there

#perform PCA
mSet <- PCA.Anal(mSet)
mSet <- PlotPCAPairSummary(mSet, "pca_pair_0_", "png", 72, width=NA, 5)
mSet <- PlotPCAScree(mSet, "pca_scree_0_", "png", 72, width=NA, 5)
mSet <- PlotPCA2DScore(mSet, "pca_score2d_0_", "png", 72, width=NA,
                       1,2,0.95,0,0)
rm(mSet)

mSet <- InitDataObjects("pktable", "utils", FALSE)

## we set samples in "row" according to the table format. If your samples are in column, set it as "col".
mSet <- Read.BatchDataTB(mSet,
                         "NEW_new_normalized_set.csv", "row",
                         missingEstimate = "lod") #read the file in from my directory and had to place a missingEstimate

mSet <- PerformBatchCorrection(mSet)
11

Hi Zhiqiang,

thank you for taking care of my problem. I’ve uninstalled and reinstalled MetaboAnalystR but still run into the same issue.
Do I have to reinstall any other packages as well?

Best,
Lisa

12

How did you re-install MetaboAnalystR? Did you try this command?
devtools::install_github("xia-lab/MetaboAnalystR", build = TRUE, build_vignettes = FALSE)

13

Hi Zhiqiang,

yes that’s what I did, but it seems like I also needed to reinstall “rlang”. Thank you for your support!

Best,
Lisa

14

Hi Lisa, Please carefully check if you have re-installed MetaboAnalystR successfully. The lastest commit of MetaboAnalystR has already been made to fix the issue.
image

15

Hi Zhiqiang,
thank you, the reinstallation worked fine, I just had to update “rlang” as well.
Thank you for your great support!