Question

Why Pathview shows just red color (up-regulated genes) on a pathway?

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Sara ▴ 20

@sara-9865

Last seen 23 months ago

Germany

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

Pathview pathway analysis differential gene expression • 3.3k views

ADD COMMENT • link updated 8.4 years ago by Luo Weijun ★ 1.6k • written 8.4 years ago by Sara ▴ 20

score 2 · Answer 1 · 2016-06-28

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Entering edit mode

Luo Weijun ★ 1.6k

@luo-weijun-1783

Last seen 17 months ago

United States

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 COMMENT • link 8.4 years ago Luo Weijun ★ 1.6k

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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 REPLY • link 8.4 years ago Sara ▴ 20