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Course material for OPEN & REPRODUCIBLE MICROBIOME DATA ANALYSIS SPRING SCHOOL

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microbiome microbiota teaching-materials wageningen-university

microbial-bioinformatics-introductory-course-material-2018's Introduction

OPEN & REPRODUCIBLE MICROBIOME DATA ANALYSIS SPRING SCHOOL 2018

SPRING SCHOOL 2018

Three day spring school on basics of high throughput 16S rRNA gene sequencing data analysis. This spring school is organised in collaboration with VLAG graduate school, Laboratory of Microbiology, Laboratory of Systems and Synthetic Biology, Wageningen University & Research, the Netherlands and Department of Mathematics and Statistics University of Turku, Finland. This year it will be held at Wageningen University & Research. We will cover topics related to basics of sequencing and microbial community analysis. We will use NG-Tax and R based tools like Phyloseq, microbiome and ggplot2 for downstream data analysis and visualization.

For more information check the course website

Before starting please install

A bookdown book covering Day2 and Day3 topics can be found at this weblink: https://goo.gl/CPChhd

We welcome community contributions to this resource
These can be improvements to existing tutorials or additional topics such as:

  • Classifiers Random Forest, SVM, etc.
  • Advanced multivariate statistics.
  • Any other analysis related to microbial ecology.
    Create a pull request or send an email to Sudarshan Shetty at [email protected]

Citation
If you found this book useful, please cite: Shetty Sudarshan A, Lahti Leo, Hermes Gerben DA, & Hauke Smidt. (2018, September 27). Microbial bioinformatics introductory course material 2018 (Version 0.01). Zenodo. http://doi.org/10.5281/zenodo.1436630

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microbial-bioinformatics-introductory-course-material-2018's Issues

Input files update

We need to test a dataset used with the current latest version of NG-Tax.
Wasin might be able to provide with such a set?

Can NG-Tax 2.0 still be accessed through Galaxy?

Having a user interface during the course was pretty convenient. I was wondering if NG-Tax can still be accessed through Galaxy, and if so, on what web address? I searched through all of the course material and did a fair shair of Googling, but I haven't been able to find the Galaxy-version of NG-Tax anymore. Does it still exist?
(I could only find https://galaxy.wur.nl/galaxy_production/ but that does not include NG-Tax in its tools.)

error when making a pairwise list that we want to compare

dear Sir,

i've encounter the following error code

Error in combn(seq_along(lev), 2, simplify = FALSE, FUN = function(i) lev[i]) :
n < m

when i run the following code:

L.pairs <- combn(seq_along(lev), 2, simplify = FALSE, FUN = function(i) lev[i])

it was all ok until this step.

would you kindly help?

thank you.

error in modularity of network

under 07-MAW-PV1.Rmd, Interference for microbial network using SpiecEasi, i having some issue with the modularity in network (starting on line 264).

net.c
Pulsar-selected refit of sparseiCov
Path length: 20
Graph dim: 679
Criterion:
stars... sparsity 0.016

mod.net <- net.c$refit

when i trying to run this line at 272,

colnames(mod.net) <- rownames(mod.net) <- colnames(otu.c)#you can remove this
it prompt me an error message, Error in rownames<-(*tmp*, value = c("OTU-9410491526:Bacteroides", : attempt to set 'rownames' on an object with no dimensions

I check on the mod.net, realised 2 of my Dimnames are in NULL type, as shown below

mod.net[["stars"]]@Dimnames[[1]]
NULL
mod.net[["stars"]]@Dimnames[[2]]
NULL

if i skip the rowname, proceed until line 276, No matter the add.rownmanes is TRUE or FALSE also the same error message.

stool.ig.mod <- graph.adjacency(mod.net, mode='undirected', add.rownames = TRUE)
Error in mde(x) : (list) object cannot be coerced to type 'double'

May i know how to fix this? Thank you

network analysis SPIEC-EASI code?

Hello

Thanks very much for sharing this course workflow for analysing microbiome studies.
Is there any possibility to let me know how to work with SPIEC-EASI code used for network analysis after deprecating some parts of the function?
net.c <- spiec.easi(otu.c, method='mb', icov.select.params=list(rep.num=50))

Many Thanks
Marwa

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