Meta-CART integrates classification and regression trees (CART) into meta-analysis. Meta-CART is a flexible approach to identify interaction effects between moderators in meta-analysis. The method is described in Dusseldorp et al. (2014) <doi:10.1037/hea0000018> and Li et al. (2017) <doi:10.1111/bmsp.12088>.

Clustering in metagenomics is the process of grouping of microbial contigs in species specific bins. This package contains functions that extract genomic features from metagenome data, find the number of clusters for that given data and find the best clustering algorithm for binning.

Functions to analyze coherence, boundary clumping, and turnover
    following the pattern-based metacommunity analysis of Leibold and Mikkelson
    2002  <doi:10.1034/j.1600-0706.2002.970210.x>. The package also includes 
		functions to visualize ecological networks, and to calculate modularity 
		as a replacement to boundary clumping.

Implements routines for metagenome sample taxonomy assignments collection, 
    aggregation, and visualization. Accepts the EDGE-formatted output from GOTTCHA/GOTTCHA2, 
    BWA, Kraken, MetaPhlAn, DIAMOND, and Pangia. Produces SVG and PDF heatmap-like plots 
    comparing taxa abundances across projects.

Visualize 'confounder' control in meta-analysis.
    'metaconfoundr' is an approach to evaluating bias in studies used in
    meta-analyses based on the causal inference framework. Study groups
    create a causal diagram displaying their assumptions about the
    scientific question. From this, they develop a list of important
    'confounders'. Then, they evaluate whether studies controlled for
    these variables well. 'metaconfoundr' is a toolkit to facilitate this
    process and visualize the results as heat maps, traffic light plots,
    and more.

Automatically estimate 11 effect size measures from a well-formatted dataset. Various other functions can help, for example, removing dependency between several effect sizes, or identifying differences between two datasets.
    This package is mainly designed to assist in conducting a systematic review with a meta-analysis but can be useful to any researcher interested in estimating an effect size.