Dear All,

I am trying to plot manhattan plot , I first tried with qqplot , it looked like a scatter plot and very funny> plotGrandLinear(MPB, aes(y = P), color = c("#7fc97f", "#fdc086"))

Error: Objects of type data.frame not supported by autoplot.  Please use qplot() or ggplot() instead

> str(MPB)

'data.frame': 63 obs. of  4 variables:

 $ CHR: num  1 1 1 1 1 1 1 1 1 1 ...

 $ SNP: chr  "rsID0" "rsID1" "rsID2" "rsID3" ...

 $ BP : num  1310924 16840541 16840567 16840575 17231444 ...

 $ P  : num  1 0.822 0.001 0.807 0 0.357 0.148 0.95 1 0.22 ..

> makeGRangesFromDataFrame(MPB,keep.extra.columns=FALSE,ignore.strand=FALSE,seqinfo=NULL,seqnames.field=c("CHR","SNP","BP","P"),start.field=c("start","CHR"),end.field=c("end","P"))

Error in .find_seqnames_col(df_colnames0, seqnames.field0, prefix) : 

  cannnot determine seqnames column unambiguously

> gr1 <- makeGRangesFromDataFrame(MPB, keep.extra.columns=TRUE,

+                                 starts.in.df.are.0based=TRUE, start=1, end=23)

Error in .normarg_field(start.field, "start") : 

  'start.field' must be a character vector with no NAs

> gr1 <- makeGRangesFromDataFrame(MPB, keep.extra.columns=TRUE,

+                                 starts.in.df.are.0based=TRUE)

Error in .find_start_end_cols(df_colnames0, start.field0, end.field0) : 

  cannnot determine start/end columns

It is still giving me error 

as I attached my data( This is how my data looks) , Thanks so much again. 

Does this work for you?

library(BiocInstaller)

 biocLite("FDb.UCSC.snp137common.hg19")

library(FDb.UCSC.snp137common.hg19)

snps <- features(FDb.UCSC.snp137common.hg19)

snps2 <-  snps[paste0("rs", as.numeric(gsub("rsID", "", as.character(data[,2])))),]li

Ugh. Hit enter by accident.

You need a GRanges object for plotGrandLinear(). You can get one by doing what I show in my previous post. You then need to add your p-values to the metadata slot (after converting to -log10), naming the column pvalues. Something like

mcols(snps2)$pvalue <- -log10(data[,3])

Where I am assuming you have called your data.frame 'data'. There are lots of examples you can then use, here.