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Hi,
I am trying to use vegan bioconducter package for beta diversity and permutation analysis for amplicon data but it is giving distance according to ASV instead of sample names, please help me with it.
> werra_sp <- read.table("convent.fert.root.count.txt",header=T,sep='\t',check.names=F,row.names=1)
> werra_env <- read.table("werra.env.txt",header=T,sep='\t',check.names=F,row.names=1)
> str(werra_sp)
'data.frame': 1327 obs. of 18 variables:
$ Root-19.S46.L001: int 44 0 52 16 13 0 0 32 7 0 ...
$ Root-22.S56.L001: int 0 0 114 0 0 0 0 40 7 0 ...
$ Root-24.S66.L001: int 43 0 484 24 0 6 0 17 0 0 ...
$ Root-25.S76.L001: int 22 0 82 19 0 0 0 31 0 22 ...
$ Root-26.S6.L001 : int 0 14 0 0 0 0 0 10 0 0 ...
> str(werra_env)
'data.frame': 18 obs. of 2 variables:
$ Treatment: Factor w/ 1 level "convent.fert.": 1 1 1 1 1 1 1 1 1 1 ...
$ Region : Factor w/ 2 levels "Mymensingh","Rajshahi": 1 1 1 1 1 1 1 1 1 2
> dist_werra <- vegdist(werra_sp^0.25, method= 'bray')
> dis
> dist_werra
270d52396ceaab2f1506f5a6c6100c10
d644684b08ae9b136307d9d2ce8975c0 0.89217116
aed34f36d535976c247278bec289fd12 0.36933629
731354d360c13253dfe2ad2d2b0cd971 0.41469186
030329dbd6777daa2f0a75400b60b583 0.59543568
Thanks
thanks, it is resolved, I just need to transpose the count data.