surh / pbi

Microbiome analysis for phosphate-defense interaction

pbi

Microbiome analysis for phosphate-defense interaction

The code in this repository was used to analyze the microbial community assembled on roots of plants growing in a wild soil (census) or on plates with a synthetic community (SynCom).

Directories

The census directory contains code used to analyze the microbial community composition of plants gorwing in wild Mason Farm soil.

The syncom directory contains code used to analyze the microbial community composition, and the plant phenotypes, of plants growing on agar plates with a well-defined but complex synthetic bacterial community, under different phosphate conditions.

The misc directory contains intermediate files that have been made available after publication upon request. The misc/unifrac subdirectory contains UniFrac distance matrices as calculated in QIIME/1.5.0 (described in Castrillo et al. 2017).

Data

The raw sequencing reads that underlie the data in these analysis are publicly available in the European Nucleotide Archive's Short Read Archive under study accession: PRJEB15671.

Functions files

Most scripts load one or two different functions.r files. Those two files are located at the main directory.

The file that is referenced as "~/rhizogenomics/src/trunk/phosphate_code/functions.r" is simply named functions.r.

The file that is referenced as "~/rhizogenomics/src/trunk/immune_code/PRR_propep/functions.r" is named functions_prrpropep.r.

Referencing

If you use this code or the data associated with it please cite:

Castrillo G, Teixeira PJPL, Herrera Paredes S, Law TF, de Lorenzo L, Feltcher ME, et al. "Root microbiota drive direct integration of phosphate stress and immunity" (2017). Nature 543(7646):513–8. Available from: http://www.nature.com/doifinder/10.1038/nature21417

A BibTex entry for this publication is:

@article{Castrillo2017,
author = {Castrillo, Gabriel and Teixeira, Paulo Jos{\'{e}} Pereira Lima and {Herrera Paredes}, Sur and Law, Theresa F. and de Lorenzo, Laura and Feltcher, Meghan E. and Finkel, Omri M. and Breakfield, Natalie W. and Mieczkowski, Piotr and Jones, Corbin D. and Paz-Ares, Javier and Dangl, Jeffery L},
doi = {10.1038/nature21417},
issn = {0028-0836},
journal = {Nature},
month = {mar},
title = {{Root microbiota drive direct integration of phosphate stress and immunity}},
url = {http://www.nature.com/doifinder/10.1038/nature21417},
year = {2017}
}

Copyright

(C) Copyright 2016 Sur Herrera Paredes

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.

pbi's Issues

Input data directly for visualization in the nature paper

hi, I have downloaded data from the paper website, which was origin data. I want to reproduce your figures in the paper. Is that ok you upload data preprocessed directly for data visualization? For example data you mentioned in the code "~/rhizogenomics/data/phosphate/census/data/otu_table.txt" cannot be found in the supplemental data.

Data availability

Hi, I am currently reproduce your figure in the Nature paper. What I found confused is that not all the data your mentioned in the r code were available. For example, the "weighted_unifrac_otu_table_filter_rar1000.txt" cannot be found anywhere in the repository or calculated in other code .Is that ok you check all of your code and data availability and upload a full data list?

Thank you very much

Unclear use of the Monte Carlo test for enrichment/depletion profiles

It is not easily gleaned from the 'census/6.4models.r' script how to apply the monte_carlo_test function.

Examples of the different input parameters are needed.

montecarlo test issue

Hi Sur,

I tried to use your montecarlo function and the results are confusing.

If I used the relative abundance table as input to your function, all of my pair-wise p-values are 1: 

If I used enrichment/depletion status as input table: 1 as enriched => if mutant has significant higher abundance than WT, -1 as depleted => if mutant has significant lower abundance than WT, 0 as no significant change. And I made all of the value for WT as 0. The results showed that all p-value are 0.

Suggestions?

Thanks!