mkatari-bioinformatics-august-2013-loadingphytozome
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mkatari-bioinformatics-august-2013-loadingphytozome [2013/12/17 14:46] – mkatari | mkatari-bioinformatics-august-2013-loadingphytozome [2015/06/18 09:05] – mkatari | ||
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===== Read Phytozome annotation file. ===== | ===== Read Phytozome annotation file. ===== | ||
- | This step was tricky because there were characters such as quotes and hash marks. We need to reset the default values to allow the file to load without a problem. | + | This step was tricky because there were characters such as quotes and hash marks. We need to reset the default values to allow the file to load without a problem. |
< | < | ||
- | anno< | + | anno< |
| | ||
| | ||
Line 25: | Line 25: | ||
===== Run Fisher Exact Test ===== | ===== Run Fisher Exact Test ===== | ||
- | If you do not have a sample gene list to work with, simply create a random one. | + | Let's use the significant genes identified from Deseq as our example. [[https:// |
< | < | ||
- | gene.list< | + | |
+ | gene.list< | ||
</ | </ | ||
- | Start by sourcing the [[https://docs.google.com/ | + | Start by sourcing the [[https://drive.google.com/ |
To run the function: | To run the function: | ||
< | < | ||
source(" | source(" | ||
- | goterm_annot< | + | goterm_annot< |
- | goresults=doFisherTest(gene.list, | + | |
- | write.table(goresults, | + | goresults=doFisherTest(as.character(gene.list[,1]), goAnnot=goterm_annot) |
+ | write.table(goresults, | ||
</ | </ | ||
+ | |||
+ | Visualizing your results in the GO-term graph. Use the RamiGO package. Simply provide the GO terms that are enriched and the corresponding p-value for the go-terms. By default it will save a file to your working directory called RamiGO.png | ||
+ | |||
+ | < | ||
+ | source(" | ||
+ | biocLite(" | ||
+ | library(RamiGO) | ||
+ | getAmigoTree(rownames(gotermresults)[1: | ||
+ | </ | ||
+ |
mkatari-bioinformatics-august-2013-loadingphytozome.txt · Last modified: 2015/06/18 09:05 by mkatari