[BioC] Pathview question
Luo Weijun
luo_weijun at yahoo.com
Thu Apr 24 19:23:05 CEST 2014
Demitry,
In pathview function, please look into the argument gene.idtype. Default gene.idtype="entrez",i.e. Entrez Gene, which are the primary KEGG gene ID for many common model organisms. For other species, gene.idtype should be set to "KEGG" as KEGG use other types of gene IDs. For more details check the help info:
?pathview
HTH,
Weijun
--------------------------------------------
On Wed, 4/23/14, Dmitry wrote:
Subject: Re: Pathview question
Date: Wednesday, April 23, 2014, 3:38 PM
Hi Weijun,
Thanks, this was dumb error. My biocLite was out
of date so even though I downloaded pathview recently I was
still getting old versions. I found the bug in version
1.1.4, but using the newer version everything also
works.
I have one question, why do you not accept the
native IDs that KEGG uses for some organisms. My specific
example is for Arabidopsis. KEGG uses TAIR ids, and this is
what pathview also returns as kegg.names. But to get the
genes to map I have to convert TAIR to entrez which is then
converted back to TAIR.
[[elided Yahoo spam]]
-Dmitry
On Wed, Apr 23, 2014 at
wrote:
Dmitry,
Thanks for your interest. you are working with the old
pathview_1.1.4. the package has been updated multiple times.
any version >=1.1.5 would work with you data. To make
full use of all functions, I would suggest you to install
the latest release version 1.4.0:
http://bioconductor.org/packages/release/bioc/html/pathview.html
Note that you don’t have to upgrade R or Bioconductor,
just manually download the package for your OS (windows
here):
install.packages("/your/local/directory/pathview_1.4.0.zip",
repos = NULL)
or you may try r-forge:
install.packages("pathview",repos="http://R-Forge.R-project.org")
HTH,
Weijun
--------------------------------------------
On Tue, 4/22/14, Dmitry
wrote:
Subject: Pathview question
Date: Tuesday, April 22, 2014, 2:39 PM
Dear Weijun,
Thank you for your excellent work on the R
package pathview. It is a very impressive an useful tool.
I've had good success reproducing all the tutorial
examples, but am running into issues using my own data
and
am wondering if you could point to my problem?
Here is example code to generate a network for
Arabidopsis. I can map compounds just fine, but not
genes.
I've specifically selected all the genes for
the pathway for my tests. Using Entrez IDs as input no
genes
are recognized. Using the native KEGG IDs all genes are
recognized but all the color mappings are set to =0.
#-----------------------------------------------------library(pathview)
#gene data as ENTREZ
IDsgene.data.entrez<-structure(list(comp1
= c(-1.33993867494585,
-0.874075185878206,
-0.815437861373184, 1.99784067931179,
-1.80615547306295,
2.87929513486298, 3.19461607237897,
0.156449901575116, -2.57802582052787,
1.68618727880872, -2.23921303962625,
1.60273066264584, 3.29143350796589,
0.674562473202573,
0.942955331710717)), .Names = "comp1",
row.names =
c("824798", "816781",
"837777", "828186",
"823737",
"841200", "843630",
"838927",
"837834", "821313",
"831938", "842023",
"824610",
"819837", "821171"), class =
"data.frame")
pv.out <- pathview(gene.data =
gene.data.entrez,pathway.id =
"00052", species =
"ath", out.suffix =
"test",keys.align = "y",
kegg.native = T, match.data=F,
key.pos =
"topright")
pv.out
and image
#Using native KEGG
Ids gene.data<-structure(list(comp1 =
c(-1.33993867494585,
-0.874075185878206, -0.815437861373184,
1.99784067931179, -1.80615547306295,
2.87929513486298,
3.19461607237897, 0.156449901575116, -2.57802582052787,
1.68618727880872, -2.23921303962625,
1.60273066264584, 3.29143350796589,
0.674562473202573, 0.942955331710717)), .Names =
"comp1", row.names =
c("AT3G56310",
"AT2G22480", "AT1G12240",
"AT4G01970", "AT3G45940",
"AT1G47840", "AT1G72990",
"AT1G23190", "AT1G12780",
"AT3G03250", "AT5G18200",
"AT1G55740", "AT3G54440",
"AT3G06580", "AT3G01260"), class =
"data.frame")
pv.out <- pathview(gene.data =
gene.data,
pathway.id =
"00052",
species = "ath", out.suffix =
"test",keys.align = "y",
kegg.native = T, match.data=F,
key.pos =
"topright")
pv.out
# and the image
#Now all the genes are recognized but set to
zero?#---------------------------------------------------------------------
Thank you in advance for any
guidance.
Best,Dmitry
sessionInfo()R version 3.0.1
(2013-05-16)
Platform: i386-w64-mingw32/i386 (32-bit)
locale:[1] LC_COLLATE=English_United
States.1252 LC_CTYPE=English_United States.1252
LC_MONETARY=English_United States.1252[4]
LC_NUMERIC=C
LC_TIME=English_United States.1252
attached base packages: [1] splines
grid compiler parallel stats
graphics
grDevices utils datasets methods base
other attached packages:
[1] CTSgetR_1.0
org.At.tair.db_2.9.0 iplots_1.1-6
rJava_0.9-4 FSelector_0.19
[6] qvalue_1.34.0
fastICA_1.1-16
ClassComparison_2.15.1
PreProcess_2.12.3 oompaBase_3.0.0
[11] IDPmisc_1.1.17 lattice_0.20-15
ICSNP_1.0-9
ICS_1.2-3 survey_3.29-4
[16] mvtnorm_0.9-9994
aroma.light_1.30.0 matrixStats_0.6.2
PerformanceAnalytics_1.1.0 xts_0.9-3
[21] zoo_1.7-9
splancs_2.01-32 sp_1.0-8
ellipse_0.3-7
geometry_0.3-2
[26] magic_1.5-4
abind_1.4-0 rgl_0.93.928
ROCR_1.0-4
car_2.0-16
[31] nnet_7.3-6 pls_2.3-0
nortest_1.0-2
pcaMethods_1.50.0 Rcpp_0.10.3
[36] pvclust_1.2-2
psych_1.3.2 pheatmap_0.7.4
gplots_2.11.0.1 MASS_7.3-26
[41] KernSmooth_2.23-10 caTools_1.14
gdata_2.12.0.1
gtools_2.7.1
outliers_0.14
[46] pathview_1.1.4
org.Hs.eg.db_2.9.0 RSQLite_0.11.3
DBI_0.2-7
AnnotationDbi_1.22.5
[51] Biobase_2.20.0
BiocGenerics_0.6.0 BiocInstaller_1.10.4
KEGGgraph_1.16.0 graph_1.38.0
[56] XML_3.96-1.1
KEGGREST_1.0.1 linkcomm_1.0-8
RColorBrewer_1.0-5 igraph_0.6.5-1
[61] rcom_2.2-5 rscproxy_2.0-5
RCurl_1.95-4.1
bitops_1.0-5
loaded via a namespace (and not
attached): [1] Biostrings_2.28.0 digest_0.6.3
dynamicTreeCut_1.21 httr_0.2
IRanges_1.18.0 png_0.1-6
R.methodsS3_1.4.2
[8] randomForest_4.6-7 Rgraphviz_2.4.0
RJSONIO_1.0-3 RWeka_0.4-17
RWekajars_3.7.9-1 stats4_3.0.1
stringr_0.6.2
[15] tcltk_3.0.1 tools_3.0.1
>
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