On 02/21/2014 02:01 PM, Michael Lawrence wrote:
This function seems to solve the problem:
helpwith <- function(expr) {
env <- IRanges:::top_prenv(expr)
expr <- substitute(expr)
fun <- eval(expr[[1L]], env)
fun.name <http://fun.name> <- deparse(expr[[1L]])
if (!isGeneric(fun.name <http://fun.name>, env)) {
stop("'expr' must be a call to a generic")
}
args <- formals(fun)
mc <- match.call(fun, expr, expand.dots=FALSE)
args[names(mc[-1L])] <- mc[-1L]
args <- args[fun@signature]
args$... <- args$...[[1L]]
target.sig <- vapply(args, function(arg) {
.arg <- arg # nice trick
if (missing(.arg)) {
"missing"
} else {
class(eval(arg, env))[1L]
}
}, character(1))
defined.sig <- selectMethod(fun, target.sig)@defined
help(paste0(fun.name <http://fun.name>, ",", paste(defined.sig,
collapse=","), "-method"))
}
path_to_gff <- "my.gff"
helpwith(import(path_to_gff))
helpwith(rbind(DataFrame(mtcars), DataFrame(mtcars)))
But where should it go?
Nice fix. It's a bug in ? so it would need to go into ? itself.
The man page for ? (accessible with ?`?`) says:
S4 Method Documentation:
[...]
There are two different ways to look for documentation on a
particular method. The first is to supply the ‘topic’ argument in
the form of a function call, omitting the ‘type’ argument. The
effect is to look for documentation on the method that would be
used if this function call were actually evaluated. See the
examples below. If the function is not a generic (no S4 methods
are defined for it), the help reverts to documentation on the
function name.
Thanks,
H.
On Fri, Feb 21, 2014 at 11:17 AM, Hervé Pagès <hpa...@fhcrc.org
<mailto:hpa...@fhcrc.org>> wrote:
Hi Gabriel,
On 02/20/2014 05:03 PM, Gabriel Becker wrote:
Herve,
The help is correct (though possibly a bit pedantic), there is no
method for that signature.
But the dispatch mechanism is able to find one because
'import(path_to_gff)' *does* work. So the help maybe is correct
but that doesn't really help the naive user.
H.
?import("", "")
works for me though
~G
On Thu, Feb 20, 2014 at 4:51 PM, Hervé Pagès <hpa...@fhcrc.org
<mailto:hpa...@fhcrc.org>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>>> wrote:
On 02/20/2014 04:16 PM, Michael Lawrence wrote:
There's also "?coverage(ga)", so the user can see what
happens
specifically for their object, without worrying about
typing out
the class.
I was never lucky with this:
> library(rtracklayer)
> path_to_gff <- system.file("tests", "v1.gff", package =
"rtracklayer")
> ?import(path_to_gff)
Error in .helpForCall(topicExpr, parent.frame()) :
no documentation for function ‘import’ and signature
‘con =
"character", format = "ANY", text = "ANY"’
In addition: Warning message:
In .helpForCall(topicExpr, parent.frame()) :
no method defined for function ‘import’ and signature
‘con =
"character", format = "ANY", text = "ANY"’
H.
At some point it would be neat to generate S4
documentation at
run-time.
Just popup a browser and see every method that might be
dispatched with
a given object. In theory, the R help server would
support this.
On Thu, Feb 20, 2014 at 3:13 PM, Hervé Pagès
<hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>>>> wrote:
On 02/20/2014 02:55 PM, Martin Morgan wrote:
On 02/20/2014 02:32 PM, Hervé Pagès wrote:
Hi Jesper,
On 02/20/2014 02:13 PM, Jesper Gådin wrote:
Very true that it is quite difficult
to find the
documentation when one
is not aware of its existence :P
Yeah, this has been a source of
frustration for
many people. And
always a source of embarrassment (for us) when
teaching our
software
to beginners.
I've started to change this. In the upcoming
version of BioC
(2.14,
scheduled for mid-April), when you'll do
?coverage,
you'll
get to
choose between the 3 man pages that
document coverage
methods (there
is one in IRanges, one in GenomicRanges,
and one in
GenomicAlignments).
I want to generalize this to other
generics that have
methods spread
across several packages (e.g.
findOverlaps, the
intra- and
inter-range
methods, etc...).
Having to choose between several man pages
every
time you do
e.g.
?findOverlaps is a minor annoyance
compared to not
being able to
find the man page at all. (Note that if
you already
know
where is
your favorite man page, you'll be able to
direct
access it with
e.g. ?GenomicRanges::findOverlaps). Nobody
will
ever need to use
the insane
?`findOverlaps,GenomicRanges,______GenomicRanges-method` to
tab completion helps, so that you don't need
to be totally
insane, just
insane enough to know to start with
?"cover<tab>
and also insane enough to know which method you
need to
pick up amongst
the 30+ methods listed by ?"findOverlaps<tab>
Overwhelming!
H.
Martin
open that man page again. Ever! (it will
still work
though...)
Cheers,
H.
coverage() is fast and beautiful. Thanks!
/Jesper
On Wed, Feb 19, 2014 at 9:21 PM, Hervé
Pagès
<hpa...@fhcrc.org
<mailto:hpa...@fhcrc.org> <mailto:hpa...@fhcrc.org
<mailto:hpa...@fhcrc.org>>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>>>
<mailto:hpa...@fhcrc.org
<mailto:hpa...@fhcrc.org>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>
<mailto:hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>>>>>
wrote:
Hi Jesper,
On 02/19/2014 08:44 AM, Michael
Lawrence
wrote:
On Wed, Feb 19, 2014 at 8:39 AM,
Jesper Gådin
<jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>__>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>__>__>>wrote:
Hi Michael,
Herves suggestion will
probably
work for my
use case, but if
there are any
smoother ways it would be
preferable.
The use case is as follows:
1) calculate strand specific
coverage over
a region from
GAlignments object (or file)
At the moment I read a
file using
readGAlignmentsFromBam()
with tag="XS",
then filter it on "flag" and
"mapq". Then I
subset the
resulting GAlignments in
a minus
and a plus
-strand object.
Then I calculate coverage
by my own
coverage function which
uses the cigar
information in the
GAlignments
object. This
function is the
one using
cigarToRleList() at the
moment. As I
understand the
coverage() function
from the
GenomicAlignments/IRanges
package
does not take
into account
cigars, or does it?
It does take the coverage
into account;
specifically to exclude
the introns
from coverage. I think
there's also an
option
to exclude
deletions.
Unfortunately the man page is not
easy to
access
(you need to do
?`coverage,GAlignments-method`________), but
it says:
The methods for GAlignments and
GAlignmentPairs
objects do:
coverage(grglist(x), ...)
And if you do grglist() on a
GAlignments or
GAlignmentPairs
objects, the
ranges you get in the returned
GRangesList
object
are calculated
based
on the CIGAR.
Trust but verify. Here is how you
can actually
verify that
coverage()
does take the CIGAR into account:
library(RNAseqData.HNRNPC.bam.________chr14)
gal <-
readGAlignments(RNAseqData.________HNRNPC.bam.chr14_BAMFILES[__1])
cig_op_table <-
cigarOpTable(cigar(gal))
First we pick up an alignment
with an N in its
CIGAR and do
coverage()
on it:
> gal_with_N <-
gal[which(cig_op_table[
, "N"]
!= 0)[1]]
> gal_with_N
GAlignments with 1 alignment and 0
metadata columns:
seqnames strand
cigar qwidth
start end
width
<Rle> <Rle>
<character> <integer>
<integer> <integer>
<integer>
[1] chr14 +
55M2117N17M 72
19650072 19652260
2189
ngap
<integer>
[1] 1
---
seqlengths:
chr1
chr10 ...
chrY
249250621
135534747 ...
59373566
> coverage(gal_with_N)$chr14
integer-Rle of length
107349540 with 5 runs
Lengths: 19650071 55
2117
17
87697280
Values : 0 1
0
1
0
Same thing with an alignment with
an I in
its CIGAR:
> gal_with_I <-
gal[which(cig_op_table[
, "I"]
!= 0)[1]]
> gal_with_I
GAlignments with 1 alignment and 0
metadata columns:
seqnames strand
cigar qwidth
start end
width
<Rle> <Rle>
<character> <integer>
<integer> <integer>
<integer>
[1] chr14 -
64M1I7M 72
19411677 19411747
71
ngap
<integer>
[1] 0
---
seqlengths:
chr1
chr10 ...
chrY
249250621
135534747 ...
59373566
> coverage(gal_with_I)$chr14
integer-Rle of length
107349540 with 3 runs
Lengths: 19411676 71 87937793
<tel:71%2087937793>
Values : 0 1
0
Same thing with an alignment with
a D in
its CIGAR:
> gal_with_D <-
gal[which(cig_op_table[
, "D"]
!= 0)[1]]
> gal_with_D
GAlignments with 1 alignment and 0
metadata columns:
seqnames strand
cigar qwidth
start end
width
<Rle> <Rle>
<character> <integer>
<integer> <integer>
<integer>
[1] chr14 +
38M1D34M 72
19659063 19659135
73
ngap
<integer>
[1] 0
---
seqlengths:
chr1
chr10 ...
chrY
249250621
135534747 ...
59373566
> coverage(gal_with_D)$chr14
integer-Rle of length
107349540 with 3 runs
Lengths: 19659062 73
87690405
Values : 0 1
0
Seeing is believing,
Cheers,
H.
I started to look at the
applyPileups() in
Rsamtools which I
can get to
calculate coverage using
cigars,
but not
using the strand or
flag
information for
filtering. That
solution
would start from a
bam-file
instead of a GAlignments
object,
and sure I
can do the
filtering outside R.
But it would be very
convenient to
do it
all from within R.
If there are nice solutions
starting from
both a GAlignments
and a
bam-file it would be
great! =)
/Jesper
On Tue, Feb 18, 2014 at
10:52 PM,
Michael
Lawrence <
lawrence.mich...@gene.com <mailto:lawrence.mich...@gene.com>
<mailto:lawrence.michael@gene.__com
<mailto:lawrence.mich...@gene.com>>
<mailto:lawrence.michael@gene.
<mailto:lawrence.michael@gene.>____com
<mailto:lawrence.michael@gene.__com
<mailto:lawrence.mich...@gene.com>>>
<mailto:lawrence.michael@gene <mailto:lawrence.michael@gene>.
<mailto:lawrence.michael@gene
<mailto:lawrence.michael@gene>.__>____com
<mailto:lawrence.michael@gene.
<mailto:lawrence.michael@gene.>____com
<mailto:lawrence.michael@gene.__com
<mailto:lawrence.mich...@gene.com>>>>> wrote:
Hi Jesper,
Would you be willing to
volunteer your
use case? As
Herve hinted,
cigarToRleList and
friends are
low-level helpers. There
may be an easier
way to achieve what
you want,
or an
opportunity to
improve things.
Michael
On Mon, Feb 17, 2014
at 1:10
AM, Jesper
Gådin
<jesper.ga...@gmail.com <mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>__>
<mailto:jesper.ga...@gmail.com <mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>
<mailto:jesper.ga...@gmail.com
<mailto:jesper.ga...@gmail.com>__>__>__>>wrote:
Hi,
Have come across a
cigar-vector
that is problematic
to process.
#load package
library(GenomicAlignments)
#load data (see
attached file)
load("2014-02-17-cigarExample.________rdata")
#run function
cigarToRleList
cigarRle <-
cigarToRleList(cigarExample)
Error in
.Call2("Rle_constructor",
values, lengths,
check, 0L, PACKAGE =
"IRanges") :
integer
overflow while
summing
elements in
'lengths'
sessionInfo()
R Under
development (unstable)
(2013-11-13 r64209)
Platform:
x86_64-unknown-linux-gnu
(64-bit)
locale:
[1]
LC_CTYPE=en_US.UTF-8
LC_NUMERIC=C
[3]
LC_TIME=en_US.UTF-8
LC_COLLATE=en_US.UTF-8
[5]
LC_MONETARY=en_US.UTF-8
LC_MESSAGES=en_US.UTF-8
[7]
LC_PAPER=en_US.UTF-8
LC_NAME=C
[9] LC_ADDRESS=C
LC_TELEPHONE=C
[11]
LC_MEASUREMENT=en_US.UTF-8
LC_IDENTIFICATION=C
attached base
packages:
[1] parallel stats
graphics
grDevices utils
datasets methods
[8] base
other attached
packages:
[1]
GenomicAlignments_0.99.18
Rsamtools_1.15.26
[3]
Biostrings_2.31.12
XVector_0.3.6
[5]
GenomicRanges_1.15.26
IRanges_1.21.23
[7]
BiocGenerics_0.9.3
loaded via a
namespace
(and not
attached):
[1]
BatchJobs_1.1-1135
BBmisc_1.5
BiocParallel_0.5.8
bitops_1.0-6
[5] brew_1.0-6
codetools_0.2-8
DBI_0.2-7
digest_0.6.4
[9] fail_1.2
foreach_1.4.1
iterators_1.0.6
plyr_1.8
[13] RSQLite_0.11.4
sendmailR_1.1-2
stats4_3.1.0
tools_3.1.0
[17] zlibbioc_1.9.0
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--
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Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research
Center
1100 Fairview Ave. N, M1-B514
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E-mail: hpa...@fhcrc.org
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Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024
E-mail: hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>
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Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024
E-mail: hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>
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--
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Graduate Student
Statistics Department
University of California, Davis
--
Hervé Pagès
Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
1100 Fairview Ave. N, M1-B514
P.O. Box 19024
Seattle, WA 98109-1024
E-mail: hpa...@fhcrc.org <mailto:hpa...@fhcrc.org>
Phone: (206) 667-5791 <tel:%28206%29%20667-5791>
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Program in Computational Biology
Division of Public Health Sciences
Fred Hutchinson Cancer Research Center
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P.O. Box 19024
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E-mail: hpa...@fhcrc.org
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