Hi,
I am trying to make a Manhattan plot using R ggplot following the example here (https://www.r-graph-gallery.com/101_Manhattan_plot.html).
I am using our own data produced from a GWAS and our results are in csv files; together, 23 csv files with each chromosome result in one csv file. Because these are summary statistics without personal identifiers, I have downloaded each cvs file and was planned to load them into R and then proceed with ggplot.
The problem is, each cvs file is huge, ~1.5 G each, so it's taking my computer a really long time to load just one single file. Any suggestions? I do have access to our university server but it's Unix-command based and I don't think I can run R interactively there.
0 answers
No answers yet.
Log in to answer this question.
-
Mutational Signatures, General Standard Refit, Cosine similarity
written by shakyaram079 •
-
Read bam/cram file with IGV from aws s3
written by quentin54520 •
-
Split multi-fasta file into smaller files using R
written by slushverte01 •
-
How to load 1000 genome vcf and tbi file into R
written by lxiao63 •
-
How to create table counts for Ballgown after performing StringTie for Estimateion transcript abund…
written by hirahameed222 •
-
How to perform Post Hoc test, Tukey in agricolae package?
written by WUSCHEL
-
VCF to R problems
written by BeetleCheers •
-
GD::Graph install 'make' failure in Cygwin
written by eb0906 •
-
Genome-wide cox regression in R
written by Caragh •
-
Snp Array Analysis Pipeline
written by yang.robert •
It's likely that R is installed on your university's cluster and that you can run it there (check using "module avail R"). I would just read the data, create your plot, save it to a png, and then scp it back to your local machine. Note: There are many different ways to read large csv files in R -- some much faster than others (see here for more details). I hope this helps!
Oh wow, vroom is A LOT faster. Thank you, Chris!