debugging r code

[alex5]

Can someone help me debug this code to generate a normalization graph based on the data "GSE233767_mRNA_Expression_Profiling.xlsx" (download link: GEO Accession viewer )

This is my code to generate a normalization graph but it keeps giving me the same errors " Error in mutate():
In argument: across(all_of(cols), ~./sum(.)).
Caused by error in across():
! Can't compute column ...10.
Caused by error in sum():
! invalid 'type' (character) of argument"

library(tidyverse)
library(readxl)
library(ggplot2)

#load data 
data <- read_excel("file-path-to-data")

# Select columns for normalization
cols <- colnames(data)[10:17]

# Convert columns to character type
for (col in cols) {
  data[[col]] <- as.character(data[[col]])
}

# Define  gene_id variable
gene_id <- data$gene_id

# Normalize  selected columns
normalized_data <- data %>%
  mutate(across(all_of(cols), ~ ./sum(.)))

#  normalization plot
ggplot(normalized_data, aes(x = gene_id, y = value)) +
  geom_bar(stat = "identity", fill = "steelblue") +
  labs(x = "Gene ID", y = "Normalized Value", title = "Normalization Graph") +
  theme_minimal()

[williaml]

@alex5

Caused by error in across():
! Can't compute column ...10.
Caused by error in sum():
! invalid 'type' (character) of argument"

Hi, the tenth column is a character and can't be summed. Maybe this could be converted to a numeric column first if it is a column that you want to sum.

Otherwise, next time please provide a reproducible example of your dataset (a few rows of sample data).

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[technocrat]

@alex5

# Convert columns to character type
for (col in cols) {
  data[[col]] <- as.character(data[[col]])
}

This explains the error.