MbioAssy1.0

This folder contains R scripts for microbial community assembly analyses, including NST calculation, neutral model analysis, C-score variance analysis, co-occurrence network analysis, and generation of random newtorks.

input includes a) abundance table of microbial entities (e.g., OTUs, ASVs), each row is a sample, each column is an OTU. b) a one-column matrix indicating the group of each sample (only used in NST calculation)

Note: a minimum number of 20 samples is suggested for meaningful network topoloigcal analyses and co-occurrence pattern statistics; Time-series data or local scale samples are also recommended for the analyses, but samples with large spatial scale or heterogeneities may lead to bias.

Functions:

1_NST.R

This script uses a developed R package NST (Reference doi:10.1073/pnas.1904623116) to calculate NST (normalized stochasticity ratio), which range from 0 to 100% and provides quantitative assessment of ecological stochasticity based on null model. A larger NST represents the community is more affected by stochasticity.

Reference to cite:

1. Zhang L, Yin W, Wang C, Zhang AJ, Zhang H, Ju F. 2021. Untangling Microbiota Diversity and Assembly Patterns in the World's Largest Water Diversion Canal. Water Research. 117617. https://www.sciencedirect.com/science/article/pii/S0043135421008125

2_Neutral_model.R

This script was modified from (Reference doi:10.1038/ismej.2015.142) and used to compare observed community composition with that predicted by a neutral assembly model(Reference doi:10.1111/j.1462-2920.2005.00956.x),which assumes that community assembly is only driven by chance and dispersal.The results were output as a visualized figure and a detailed table which contains information of observed and predicted community composition.

Reference to cite:

1. Zhang L, Yin W, Wang C, Zhang AJ, Zhang H, Ju F. 2021. Untangling Microbiota Diversity and Assembly Patterns in the World's Largest Water Diversion Canal. Water Research. 117617. https://www.sciencedirect.com/science/article/pii/S0043135421008125
2. Niederdorfer R, Fragner L, Yuan L, Hausherr D, Wei J, Magyar P, Joss A, Lehmann MF, Ju F, Helmut Bürgmann. 2021. Distinct growth stages controlled by the interplay of deterministic and stochastic processes in functional anammox biofilms. Water Research. 200:117225

3_C-score-var.R

This script was for the checkerboard score variance(C-score-var) analysis of non-random species co-occurrence patterns. Cite:

Reference to cite:

1. Niederdorfer R, Fragner L, Yuan L, Hausherr D, Wei J, Magyar P, Joss A, Lehmann MF, Ju F, Helmut Bürgmann. 2021. Distinct growth stages controlled by the interplay of deterministic and stochastic processes in functional anammox biofilms. Water Research. 200:117225 https://www.sciencedirect.com/science/article/pii/S0043135421004231

4_Co-occurrence_network.R

This script first defines the function "co_occurrence_network" to generate a filtered gml-formatted network file based on all pairwise Spearman's correlations and FDR-adjusted P-value calculation and filtration, and then uses input abundance table to generate co-occurrence network which can be further visulized and explored in Gephi (https://gephi.org/) or Cytoscape (https://cytoscape.org/).

Reference to cite:

1. Ju F, Zhang T. 2015. Bacterial assembly and temporal dynamics in activated sludge of a full-scale municipal wastewater treatment plant. The ISME Journal. 9: 683-695
2. Ju F, Xia Y, Guo F, Wang ZP, Zhang T*.2014. Taxonomic relatedness shapes bacterial assembly in activated sludge ofglobally distributed wastewater treatment plants. Environmental Microbiology.16(8):2421-2432

5_Random_network.R

This script was for generating 10000 or other numbers of random network to topologically compared against an observed network

Reference to cite:

1. Ju F, Xia Y, Guo F, Wang ZP, Zhang T*.2014. Taxonomic relatedness shapes bacterial assembly in activated sludge ofglobally distributed wastewater treatment plants. Environmental Microbiology.16(8):2421-2432 https://onlinelibrary.wiley.com/doi/10.1111/1462-2920.12355

MbioAssy1.0

This script integrates the above modules which use the same abundance table of microbial entities as input. Pls cite the link and corresponding papers if you find the scripts useful. Pls cite the package as:

MbioAssy1.0: https://github.com/emblab-westlake/MbioAssy1.0/