Hi
it looks as if the largest proportion of the genome have a coverage of
0. This is of course to expect, but it means that you will have to
play with the ylim parameter too, because otherwise the frequency for
the first bins will dominate the plot, that's why you just see one
bar. see ?hist
In such a setting I just try something like:
hist(lane1, ylim=c(0, 2000), breaks=seq(1, max(c1)+100, 100))
for bins of width 100 starting from 1
In addition the package GenomeGraphs provides additional methods to
plot the coverage over the chromosome
which is maybe of interest, too. see the examples in the vignette.
Michael
Am 17.08.2009 um 21:07 schrieb Abhishek Pratap:
Hi
I dont have a lot of experience with plotting large amount of data
points and clearly my question reflects that. :)
summary(lane1)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.000 0.040 0.180 5.186 0.620 39730.000 2264.000
Thanks for your help.
-Abhi
On Mon, Aug 17, 2009 at 3:05 PM, Sean Davis<[email protected]> wrote:
On Mon, Aug 17, 2009 at 3:01 PM, Abhishek Pratap <[email protected]
>
wrote:
Hi Sean
Thanks for your suggestion on both the mailing lists. I am now
reading
the coverage values from a file and storing them as a data.frame and
then creating a new numeric vector for each lane. Each vector may
have
15000-45000 entries. The values are integers with a significant
difference in values, some could be between 0-1 eg (0.45,0.89) and
then I also have values in range like (4000, 44000). I am just
taking
random examples to explain the bias in the data.
When I plot a histogram I just see one big bar. I feel the bins are
not created effectively. I also tried couple of different options in
the R hist function but with same result.
hist(lane2, freq=TRUE, breaks=10);
hist(lane2, freq=TRUE, include.lowest=TRUE);
What does summary(lane2) show? You may need to transform the data
to make
it more presentable (log?).
Sean
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Michael Dondrup, Ph.D.
Bergen Center for Computational Science
Computational Biology Unit
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