asking how to make chromosome name become easy to distinguish

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amira ndi

Sep 9, 2021, 11:59:42 AMSep 9
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Dear all,
I need some advice and suggestion due to my problem, I am sorry if this question seems easy but I am beginner here to use r/qtl packages in R software. I have around 1000 markers (genotype) and 1 phenotype (100 data). I tried to run it used scannone with methode "mr"
However the data showed like this,


Here is my scripts,
data_mr <- read.csv("trial2.csv")
data_mr <- read.cross("csvr", file="trial2.csv",

data_mr <- jittermap(data_mr, amount= .0001)
data_mr <- calc.genoprob(data_mr, step=0,eror.prob=0.01)
data.scanone <- scanone(data_mr, pheno.col = 1)
permulation.test <- scanone(data_mr, method = "em", 
                            pheno.col = 1, n.perm=10)

I only have genotype data like "AA/BB" and do not have position of marker in cM. Are there any ways to make the chromosome name could be easy to distinguish? or do I have a mistake to input the data?

Thank you so much before.

Karl Broman

Sep 9, 2021, 12:09:19 PMSep 9
to R/qtl discussion
R/qtl assumes a set of chromosome IDs for the markers, and really needs marker order and cM locations to handle missing data properly. If you just want to do GWAS with the observed SNPs, you may be better off with more general software like PLINK.

The input file expects that the second row (or 2nd column if you're using the "csvr" format) contain the chromosome IDs.
See chapter 2 of the R/qtl book ( and the sample data files at


amira ndi

Sep 9, 2021, 12:26:36 PMSep 9
Dear Karl, 
Thank you for answering.
Yes, my data does not have "cM location". Does it mean that I can not use QTL in Rstudio to estimate the genomic regions in my data?
Because, I want to estimate the location here. Any other suggestion that could be used to still analyze my data in R?


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Karl Broman

Sep 9, 2021, 1:48:32 PMSep 9
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If you have a physical map with bp locations, I would start with that, though using Mbp positions.
Otherwise, you could try to estimate a genetic map. See


amira ndi

Sep 18, 2021, 1:42:13 PMSep 18
to R/qtl discussion
Dear Karl,

Thank you for your suggestion.
I would like to make the visual of my data like this,
I am still struggling to look for how to group the data in Excel  so that it can be visualized per-chromosome like the picture above and what is the packages to analyze.
Do you have recommendation? My data consist of 1 phenotype (around 100 data) with 1000 markers (5 chromosomes). 
Please give me your suggestion.

Thank you!


Karl Broman

Sep 18, 2021, 3:45:33 PMSep 18
to R/qtl discussion
I don't have anything to add over what I said below. Chapter 2 of the R/qtl book talks about data file format, and it's available online at

There are example data files online at

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