[R] Redundancy canonical analysis plot problem in 3D using VEGAN, RGL, SCATTERPLOT3D and SFSMISC
David L Carlson
dcarlson at tamu.edu
Wed Jul 19 04:11:17 CEST 2017
We need to keep the discussion on the list. When I run your code, there are several problems.
strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName ="strain", header = T, row.names = 1)
str(strain.data) # lists 9 columns at the end with all NAs
strain.data1 <- (strain.data, sqrt.dist = TRUE) # this is not a valid R line. I get
Error: unexpected ',' in "strain.data1 <- (strain.data,"
strain.cca1 <- cca(log1p(strain.data) ~ Ph + TotalN + Organicmatter + Ca + K + Na + P + Cu + Mn, env.data) # More errors resulting from all the NA values
Error in Math.data.frame(strain.data) :
non-numeric variable in data frame: NA..1NA..2NA..3NA..4NA..5NA..6NA..7NA..8NA..9
You have only 6 observations. In strain.data, since each column has a single 1 and the other 5 rows are 0's. Assuming that the columns are taxa, each taxon is found at only one site. I suspect there is a problem with your data or with the way you have coded the data.
David L Carlson
-----Original Message-----
From: Sanjay Kumar Jaiswal [mailto:JaiswalSK at tut.ac.za]
Sent: Tuesday, July 18, 2017 4:27 PM
To: David L Carlson <dcarlson at tamu.edu>
Subject: RE: [R] Redundancy canonical analysis plot problem in 3D using VEGAN, RGL, SCATTERPLOT3D and SFSMISC
Dear Sir
I am attaching herewith data which I used to analyse. Please correct the command if you find anything wrong with it. I am sending herewith command line too. Please see it and suggest me. I will be very grateful for the same.
getwd()
setwd("C:\\Users\\sanju\\Documents\\Dee")
library(xlsx)
strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName="strain", header = T, row.names = 1)
strain.data1 <- (strain.data, sqrt.dist = TRUE)
env.data <- read.xlsx("Dee rhiz.xlsx", sheetName="env", header = T, row.names = 1)
library(vegan)
strain.cca1 <- cca(log1p(strain.data) ~ Ph + TotalN + Organicmatter + Ca + K + Na + P + Cu + Mn, env.data)
strain.cca1
strain.cca1plot <- plot(strain.cca1, type = "n", scaling = 3)
text(strain.cca1, display = "cn")
points(strain.cca1, display = "sites", pch=21, col="black", bg="grey", cex=1.2)
text(strain.cca1, "species", col="black", cex=0.8)
summary(strain.cca1)
Regards
Sanjay
-----Original Message-----
From: David L Carlson [mailto:dcarlson at tamu.edu]
Sent: 18 July 2017 20:55
To: Sanjay Kumar Jaiswal; r-help at r-project.org
Subject: RE: [R] Redundancy canonical analysis plot problem in 3D using VEGAN, RGL, SCATTERPLOT3D and SFSMISC
We don't have enough information to replicate your results, but the warning in the output is suggestive: "Some constraints were aliased because they were collinear (redundant)".
Are some of your columns perfectly correlated with other columns? This could easily happen if there are more columns than rows.
-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352
-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Sanjay Kumar Jaiswal
Sent: Tuesday, July 18, 2017 4:08 AM
To: r-help at r-project.org
Subject: [R] Redundancy canonical analysis plot problem in 3D using VEGAN, RGL, SCATTERPLOT3D and SFSMISC
Hello Sir
I am getting problem in plotting in CCA . Could you please help me? I wrote the below command but I don't know why it is taking only first 5 env data rather than all 9.
> strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName="strain", header =
> T, row.names = 1) env.data <- read.xlsx("Dee rhiz.xlsx",
> sheetName="env", header = T, row.names = 1) strain.cca <-
> cca(strain.data ~ Ph+TotalN+Organicmatter+Ca+K+Na+P+Cu+Mn,
> data=env.data) strain.cca
Call: cca(formula = strain.data ~ Ph + TotalN + Organicmatter + Ca + K + Na + P
+ Cu + Mn, data = env.data)
Inertia Proportion Rank
Total 5 1
Constrained 5 1 5
Unconstrained 0 0 0
Inertia is mean squared contingency coefficient Some constraints were aliased because they were collinear (redundant)
Eigenvalues for constrained axes:
CCA1 CCA2 CCA3 CCA4 CCA5
1 1 1 1 1
> plot(strain.cca)
> summary (strain.cca)
Call:
cca(formula = strain.data ~ Ph + TotalN + Organicmatter + Ca + K + Na + P + Cu + Mn, data = env.data)
Partitioning of mean squared contingency coefficient:
Inertia Proportion
Total 5 1
Constrained 5 1
Unconstrained 0 0
Eigenvalues, and their contribution to the mean squared contingency coefficient
Importance of components:
CCA1 CCA2 CCA3 CCA4 CCA5
Eigenvalue 1.0 1.0 1.0 1.0 1.0 0
Proportion Explained 0.2 0.2 0.2 0.2 0.2 0
Cumulative Proportion 0.2 0.4 0.6 0.8 1.0 1
Accumulated constrained eigenvalues
Importance of components:
CCA1 CCA2 CCA3 CCA4 CCA5
Eigenvalue 1.0 1.0 1.0 1.0 1.0
Proportion Explained 0.2 0.2 0.2 0.2 0.2
Cumulative Proportion 0.2 0.4 0.6 0.8 1.0
Biplot scores for constraining variables
CCA1 CCA2 CCA3 CCA4 CCA5
Ph 0.29757 0.85775 -0.3364 0.2242 -0.11088
TotalN -0.01537 -0.67797 0.6132 0.2831 0.28985
Organicmatter 0.14618 0.06462 0.8320 0.3515 0.39827
Ca 0.08310 -0.41940 0.3858 0.8116 0.09834
K 0.37548 0.38360 0.6849 -0.4172 0.26222
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confidential. The full text of the Electronic Mail Disclaimer
can be seen on the TUT web site at
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or obtained by phoning (012) 382-5911
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Tshwane University of Technology
----------------------------------------------------------------------------------
This email is sent and received in terms of the Electronic
Communications Policy of Tshwane University of Technology.
In line with this policy, this email is private, privileged and
confidential. The full text of the Electronic Mail Disclaimer
can be seen on the TUT web site at
http://www.tut.ac.za/Other/disclaimer/Pages/default.aspx
or obtained by phoning (012) 382-5911
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