I recently stumbled upon the GOPlot R package, developed by Wencke Walter and colleagues. The package provides some great tools for visualizing omics data. My favourite is the chord diagram, which captures the complex relationship between differential gene expression (shown on the left) and enriched functional categories (shown on the right)- here’s one I made for my ARVO conference poster this year:
The package is easy to use and provides a range of other plot options (bar plot, bubble plot, circle plot, cluster plot). I highly recommend you check it out!
Hi Nina,
ReplyDeletehow did you change the font? GOChord doesn't have and attribute for this
Hi Sergetto,
ReplyDeleteI exported the vector image from R and edited the font and labels in Adobe Illustrator.
Cheers,
Nina
Hi Nina,
ReplyDeleteI am using GOplot for visualizing my data. I am using an excel file that contains Genes and pathway along with fold change. But, I am getting error while ploting using GOchord function -
Error - Error in `$<-.data.frame`(`*tmp*`, "x.start", value = c(0, 0.126527368920428, :
replacement has 53 rows, data has 58
How do you change the color of the plot? I prefer your data settings.
ReplyDeleteThere is an argument inside GOChord called 'ribbon.col' where you can provide your own colors. The number of colors must be the same as the number of terms (GO terms). Code looks like this GOChord(data, ... , ribbon.col = 'your colors')
DeleteHi Nina
ReplyDeleteYour chord graph looks really nice and has no black border, do you know how to remove the black border?
Would you please share you GOChord if it is possible?
Many thanks