[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 My biocLite was out
 of date so even though I downloaded pathview recently I was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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