QCMI: Quantify Community-level Microbial Interactions

An R package for easy modeling, filtering, and quantifying putative biotic associations of microbes at the community level.

Overview

qcmi quantifies the strength of putative biotic associations of microbes at the community level and assesses the ecological consequences caused by biotic associations

qcmi provides some convenient verbs to make it easy to process data and results:

Pipeline

• Step 1. Construct ecological networks for microbial communities. 📜

• Step 2. Assign the ecological assembly processes to each significantly pair ASVs. 📈

• Step 3. Quantify the strength of putative biotic associations to each local site (at the community level). 📊

• Step 4. Calculate the effects of putative biotic associations on alpha and beta diversity of microbial communities. ❤️

Function

• trans_ps() converts the data to phyloseq format.

• filter_ps() filters OTU table by occurrence and abundance.

• cal_network() infers ecological networks.

• rmt() filters correlation coefficient.

• idirect() disentangles the direct relationships from indirect relationships in the networks

• test_link_env() classifies the ecological associations to environmental filtering

• test_link_dl() classifies the ecological associations to dispersal limitation

• assigned_process() identifies ecological associations as environmental filtering and dispersal limitation to dig out putative biotic associations from complex ecological networks

• qcmi() quantifies the strength of microbial biotic associations at the community level.

• cal_alphacon() calculates the contributions of microbial associations on alpha diversity

• cal_betacon() calculates the contributions of microbial associations on beta diversity

For a detailed introduction, please see https://joshualiuxu.github.io/.

Installation

to get the development version from GitHub:

# If devtools package is not installed, first install it
install.packages("devtools")
devtools::install_github("joshualiuxu/qcmi")

load the package:

library("qcmi")

If you find a bug, please file a minimal reproducible example in the issues

Usage

Please see the document of qcmi.tutorial.r or view the website https://joshualiuxu.github.io/

Contributing

I’m happy to receive bug reports, suggestions, questions, and (most of all) contributions to fix problems and add features. I personally prefer using the GitHub issues system over trying to reach out to me in other ways (personal e-mail, Twitter, etc.). Pull Requests for contributions are encouraged.

Here are some simple ways in which you can contribute (in the increasing order of commitment):

• Read and correct any inconsistencies in the documentation

• Raise issues about bugs or wanted features

• Review code

• Add new functionality (in the form of new plotting functions or helpers for preparing subtitles)

Citation 🌱🌱🌱

Xu Liu, Yu Shi, Teng Yang, Gui-Feng Gao, Haiyan Chu. 2023. QCMI: A method for quantifying putative biotic associations of microbes at the community level.

Article DOI: 10.1002/imt2.92

Article: QCMI: A method for quantifying putative biotic associations of microbes at the community level

Journal: iMeta