Problems with the same gene names in R, any help?

Question

[ymervenuryavuz]

Hello everyone, I need to make a gene enrichment with clusterProfiler tool implemented in R. I have a gene list with only gene names in it. In the data I have now, there was some NAs and I eliminated them with na.omit() function. Now, I have a clear list but I need to make sure that my data doesn't have the same gene names more than one. Later, I need to reunite the truncated data. I couldn't find the right arguments and commands for those procedures. Sorry for inconvenience, and thank you very much for the help, Mervenur

[karl.stamm]

Why would your data have multiples of gene names? Maybe picking one at random is a bad idea because they represent different things.

[ymervenuryavuz]

They're all miRNA target genes, all I know is that I need to make sure my data only consists only one of different gene names

[cpad0112]

group by genes and collapse all the miRNAs (with , separation). That way you would not loose any information. Remove any remaining NAs.

Answer 1

[lessismore]

unique() function rom base R or distinct() from dplyr package

[ymervenuryavuz]

Thank you so much, that was really helpfull I used distinct () function from dplyr package. But after that for combining the truncated data I used unite() function from tidyr package but system gave me an error. Do you know why? Or what should I do instead?

[lessismore]

Hi, i've no idea what your data looks like. You should post what you start from and what you're trying to achieve. A small reproducible example will let people better understand your question

[ymervenuryavuz]

I am writing down the commands I used and what I am trying to achieve. genes <- read.table("dataname.txt", header = TRUE, sep = "\t") gene_list <- na.omit(genes) library(dplyr) gene_names <- distinct(gene_list, keep_all = TRUE) Now I have gene names and I want to unite truncated data. Later, with enrichGO() function from clusterProfiler I wanna make gene enrichment. Before that function I assume I need to find gene IDs. But don't have any idea how to either. Sorry for inconvenience and thank you so much