JunqiangZheng

banocc

BAnOCC is a package designed for compositional data, where each sample sums to one. It infers the approximate covariance of the unconstrained data using a Bayesian model coded with `rstan`

equSA

HerbivoreDetritivoreInteractions

A repository for experimental data and code associated with the manuscript: Interactions between herbivores and detritivores develop slowly and conspicuously into feedbacks

med_qiime_tutorial

a tutorial for using MED & QIIME to create an OTU table

microbe-networks

Roxanne's thesis project, studying microbe co-occurrence in corn seed

microbiome

microbiome-1

microbiome R package

Mycorrhizal-symbiosis-modulates-the-rhizosphere-microbiota-to-promote-rhizobia-legume-symbiosis

Plants establish symbioses with mutualistic fungi, such as arbuscular mycorrhizal (AM) fungi, and bacteria, such as rhizobia, to exchange key nutrients and thrive. The plants and symbionts have coevolved and represent vital components of terrestrial ecosystems. Plants employ an ancestral AM signaling pathway to establish intracellular symbioses, including the legume-rhizobia symbiosis, in their roots. Nevertheless, the relationship between the AM and rhizobial symbioses in native soil is poorly understood. Here, we examined how these distinct symbioses affect root-associated bacterial communities in Medicago truncatula, by quantitative microbiota profiling (QMP) of 16S rRNA genes. We found that M. truncatula mutants that cannot establish AM or rhizobia symbiosis have an altered microbial load (quantitative abundance) in rhizosphere and roots, and in particular that AM symbiosis is required to assemble a normal quantitative root-associated microbiota in native soil. Moreover, quantitative microbial co-abundance network analyses revealed that the AM symbiosis impacts Rhizobiales-hubs among the plant microbiota and benefit the plant holobiont. Through QMP of rhizobial rpoB and AM fungal SSU rRNA genes, we revealed a new layer of interaction, whereby AM symbiosis promotes rhizobia accumulation in the rhizosphere of M. truncatula. We further showed that AM symbiosis-conditioned microbial communities within the M. truncatula rhizosphere could promote nodulation in different legume plants in native soil. Given that the AM and rhizobial symbioses are critical for crop growth, our findings might inform strategies to improve agricultural management. Moreover, our work sheds light on the co-evolution of these intracellular symbioses during plant adaptation to native soil conditions.

NWT_MovingUphill2

Analysis of Niwot 2015 18S, 16S, ITS data

R

R - learning

JunqiangZheng/microbiome-1

microbiome R package

JunqiangZheng/16S_bayes_co-occurrence

for 16S bayesian co-occurrence project

JunqiangZheng/16sNetworks

JunqiangZheng/ankspon

Files for recapitulating microbiome analysis

JunqiangZheng/co-occurrence

R scripts for performing co-occurrence analyses

JunqiangZheng/co-occurrence_networks

Scripts for null model analysis of plant-mycorrhiza co-occurrence networks described in Encinas-Viso et al (2016)

JunqiangZheng/EasyNetwork

R scripts to construct co-occurrence network

JunqiangZheng/Ecological-SEMs-in-lavaan

Recreating SEM analyses from papers using the R lavaan package

JunqiangZheng/Elevation_cooccurance_study

Elevational changes in co-occurrence-inferred fungal interactions across seasons

JunqiangZheng/genspe

Calculates co-occurrence based species habitat specialization.

JunqiangZheng/Gephi-0.9-Tutorial

Network visualization with Gephi: tutorial and example data files

JunqiangZheng/ITS_soil_landuse_aggregate

Contains code for data analysis of Bach et al. (in submission), Grassland plant communities and nitrogen fertilization affect soil fungal communities at micro- and macroscale

JunqiangZheng/k-analysis-old

k-analysis of bipartite networks

JunqiangZheng/mice8992-2016

Code used in MiCE 8992 Spring 2016

JunqiangZheng/microbiome_network

Automatic generation of colored networks, stacked bar plots, and zc-plots based on input parameters

JunqiangZheng/Mondrian

Display the relative occurrence and co-occurrence of events in a sample

JunqiangZheng/Network_Analysis_R_Examples

R scripts from USC COMM 645 2012

JunqiangZheng/Phylo-SDMs

R functions to combine phylogenetic and co-occurrence information, compute a phylogenetic predictor that can be utilized in conventional Species Distribution Models. From Morales-Castilla et al. (2017)

JunqiangZheng/Plant_Co-occurrence_Patterns

JunqiangZheng/Protocols

JunqiangZheng/R-igraph-Network-Workshop-NetSciX

NetSciX 2016 workshop on network analysis and visualization with R and igraph

JunqiangZheng/R-Network-Visualization-Basics-to-Advanced

Basic and advanced network visualization with R - code and tutorial from my Sunbelt 2016 workshop.