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Question: Why Pathview shows just red color (up-regulated genes) on a pathway?
0
gravatar for Sara
16 months ago by
Sara0
Sara0 wrote:

Hi friends,

I'm trying to use Pathview for pathway analysis of my differentially expressed genes. I used the below command 

 pv.out <- pathview(gene.data =DE, gene.idtype = "kegg", pathway.id = "00480", species = "ath", out.suffix = "DE.glu", kegg.native = T)

While my input file was the combination of up and down regulated genes, indicated by log FC, Pathview returned just up-regulated genes (red color) on the pathway. Please kindly tell me how I should fix this problem to see both, red and green (down-regulated genes), on the pathway?

Here is sessionInfo()

R version 3.3.1 (2016-06-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
[1] pathview_1.10.1      org.Hs.eg.db_3.2.3   RSQLite_1.0.0       
[4] DBI_0.4-1            AnnotationDbi_1.32.3 IRanges_2.4.8       
[7] S4Vectors_0.8.11     Biobase_2.30.0       BiocGenerics_0.16.1 

loaded via a namespace (and not attached):
 [1] KEGGgraph_1.28.0  XML_3.98-1.4      Biostrings_2.38.4 png_0.1-7        
 [5] R6_2.1.2          grid_3.3.1        httr_1.2.0        graph_1.48.0     
 [9] zlibbioc_1.16.0   curl_0.9.7        XVector_0.10.0    Rgraphviz_2.14.0 
[13] tools_3.3.1       KEGGREST_1.10.1

 

Thank you

ADD COMMENTlink modified 16 months ago by Luo Weijun1.4k • written 16 months ago by Sara0
1
gravatar for Luo Weijun
16 months ago by
Luo Weijun1.4k
United States
Luo Weijun1.4k wrote:
Sarah, Based on your last question: Please help with pathway analysis using Pathview your input DE above is a character vector of gene IDs. There is no expression data there. You need to do something like gdata= df[,2] names(gdata)= as.character(df[,1]) pv.out <- pathview(gene.data =gdata, pathway.id = "00906", species = "ath", out.suffix = "df", kegg.native = T) however, this will only give you the red color too, because your gene data is absolute expression level (all positive values) not differential expression like fold change ot t-statistics.
ADD COMMENTlink written 16 months ago by Luo Weijun1.4k

Thank you, Luo for your help. Now, everything is OK. However, I have some questions:

In my gene list, maximum and minimum values of fold change (logFC) were 8 and -7, respectively. But, the color key of Pathview output showed the range of FC between 1 and -1, could you please explain to me how Pathview calculates it?

I’m aware of that in native kegg view, a gene node may represent multiple genes/proteins with similar or redundant functional role, however, it’s required to know which of similar input genes located in each node. Please kindly tell me if there is any way to get such information from the pathview output? 

Your responses would be highly appreciated.

ADD REPLYlink written 16 months ago by Sara0
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