Hi Yadav,

if you are going to use *ggbio* package, it require GRanges as input for
your Manhattan plot, you need to *rearrange* your results into a GRanges
object,  generally you have to parse chromosome names and region from your
original data and use GRanges constructor for saving them as a GRanges
object. like

library(GenomicRanges)
gr.snp <- GRanges(chrs,
                  IRanges(start = your_start_pos, end = your_end_pos),
                   pvalue =  your_pvalue))

## where chrs are your chromosome vectors, and your_start_pos, your_end_pos
defines your region, you put your p-value, as your extra elementMetadata
column.

## then
library(ggbio)
plotGrandLinear(gr.snp, y = pvalue, geom = "point") + theme_bw()

you can check example ?plotGrandLinear

FYI: this is going to be a separate transformation stage in the very near
future, it is undergoing some change,so if you came across any issues, you
could file a issue at https://github.com/tengfei/ggbio/issues, or email me
back.
This week I am renewing the website, I will put a example for Manhattan
plot as one of the case studies on the website. Will sent you an email
later.

HTH

Tengfei





On Tue, Apr 3, 2012 at 12:45 PM, Yadav Sapkota <ysapkota@ualberta.ca> wrote:

> Hello,
>
> I am trying to generate a Manhattan plot using the association results from
> CNVs. Following is the example data:
>
>  Regions P value =-LOG10(P value)  chr1:100132667-100143425 0.2238316
> 0.650078601  chr1:100274010-100276481 0.2766402 0.55808471
> chr1:100295062-100304021 0.3608504 0.442672809  chr1:100763109-100777987
> 0.8155034 0.088574224  chr1:100797078-100799030 1 0
> chr1:100910270-100930160 1 0  chr1:100943609-100975280 0.4864253
> 0.312983845
>
> I would appreciate if anyone knows any package or script for this.
>
>
> Regards,
> Yadav
>
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>
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>



-- 
Tengfei Yin
MCDB PhD student
1620 Howe Hall, 2274,
Iowa State University
Ames, IA,50011-2274
Homepage: www.tengfei.name

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