The Elements


Popular posts from this blog

Correlation

Image
Correlation.R # ============================================================ # Tutorial on drawing a correlation map using ggplot2 # by Umer Zeeshan Ijaz (http://userweb.eng.gla.ac.uk/umer.ijaz) # =============================================================   abund_table<- read.csv ( "SPE_pitlatrine.csv" , row.names = 1 , check.names= FALSE ) #Transpose the data to have sample names on rows abund_table<- t ( abund_table ) meta_table<- read.csv ( "ENV_pitlatrine.csv" , row.names = 1 , check.names= FALSE )   #Filter out samples with fewer counts abund_table<-abund_table [ rowSums ( abund_table ) > 200 , ]   #Extract the corresponding meta_table for the samples in abund_table meta_table<-meta_table [ rownames ( abund_table ) , ]   I changed the parameters #You can use sel_env to specify the variables you want to use and sel_env_label to specify the labes for the pannel sel_env<- c ( "pH" , "Temp" , "TS...
Read more

Simple GRaphs (Part II)

Image
After much eye squinting from all viewers, it was decided during the meeting with great panel judges that the graph needed a face lift.  The best Simple Graph tutorial that was perfect for my data derived from: http://www.harding.edu/fmccown/r/#autosdatafile So, the changes were as per below: # Graph autos with adjacent bars using rainbow colors barplot( as.matrix(Maludam_Mac2014) , main="Elemental Analysis", ylab= "Carbon Ratio", beside=TRUE, col=rainbow(5) ) # Place the legend at the top-left corner with no frame # using rainbow colors legend("topleft", c("S1","S4","S6","S8","S9"), cex=0.6, bty="n", fill=rainbow(5)); After much thinking and staring at my PC for one day, giving opportunity to bloodshot eyes, I've realized the data was the key. Therefore, I changed the raw data to C:N C:S H:C 0.40   1.81 1.13 2.42   17.66 0.33 0.67   4....
Read more

NMDS (Non-metric multidimensional scaling)

Image
So this works for my data! I had started with the commands under the section NMDS from http://userweb.eng.gla.ac.uk/umer.ijaz/bioinformatics/ecological.html the sample and data samples were prepared according to the above. and proceed with the following: library("vegan", lib.loc="~/R/win-library/3.2") library("lattice", lib.loc="C:/Program Files/R/R-3.2.5/library") set.seed(2) abund_table<-read.csv("Sample.csv",row.names=1,check.names=FALSE) #Transpose the data to have sample names on rows abund_table<-t(abund_table) abund_table<-t(abund_table) example_NMDS=metaMDS(abund_table, k=2) plot(example_NMDS) ordiplot(example_NMDS,type="n") orditorp(example_NMDS,display="species",col="red",air=0.01) orditorp(example_NMDS,display="sites",cex=1.25,air=0.01) And I changed "Treatment 1" and "Treatment 2" to: treat=c(rep("pH",5),rep("Cond...
Read more