R package for Unifrac and Weighted Unifrac other than Phyloseq?
I've been googling, and I can't find an R package that calculates weighted and unweighted unifrac distances other than phyloseq. I'm doing all of my other analysis by hand from tables, so if possible I'd rather not have to convert to phyloseq objects just for this part of the analysis.
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
How to Get a Genetic Map, Given the Physical Position and Genotype Data of Markers
written by Daniyal •
-
method for querying gnomAD with long list of "uncharacterized" variants
written by Charles Murtaugh •
-
Going from Seurat object to DESeq2 analysis
written by learner-MD •
-
Program to plot 60,000 16S rRNA dataset for phylogenetic assessment?
written by prfsullivan •
-
How to automate the conversion of a large number of .sra files to .fastq?
written by Jeff M •
-
Weighted rank list comparison
written by Folder40g
-
Phyloseq Weighted Unifrac Ordination Error
written by mzmd4 •
-
Bamfile first step analysis
written by Morris_Chair
-
PredictABLE R package - HELP building a weight genetic risk score
written by Juliana •
-
How to plot UniFrac PCoA with 95% confidence Elipses in R
written by c.v.oflynn
If you can get the data into R, you can import it into phyloseq.
You are kidding, right?
I don't know of another R package that has this and if there isn't any either you can code it yourself or you can use the existing implementation. To help with the latter I gave you the link to the phyloseq tutorial part on how to convert various R data structures into phyloseq objects.
Thanks @Jean-Karim. I'm trying to get away from using Phyloseq in general which is why I asked for an alternative. I've been switching over to working directly from tables as I find I have more control, write tidier code, and reduce the size of r sessions.
Thanks @Jean-Karim. I'm trying to get away from using Phyloseq in general which is why I asked for an alternative. I've been switching over to working directly from tables as I find I have more control, write tidier code, and reduce the size of r sessions.