Table 4 Summary of in-depth review articles.

A collection of reviews for more in-depth coverage of each topic.

In-depth review areaReferences
Specific clustering algorithms, their trade-offs, and how they function(2, 3, 7173)
Analysis of the effects of different distance metrics on clustering gene expression data(74, 75)
Practical and mathematical implications of high dimensionality on clustering(15, 16)
A thorough review of validation metrics(35, 38, 62, 76)
The most common multiple hypothesis correction procedures including Bonferroni correction and FDR correction.(55, 58)
The effects of specific distances on data clustering for lower-dimensional spaces(77)
The effects of specific distances on data clustering for high-dimensional spaces(15, 78)
Ensembles of some algorithms incompatible with high-dimensional data can be useful on higher-dimensional data, even when a single clustering solution is uninformative.(23, 24)
A more in-depth analysis of ensembles, including evaluating the results of multiple clustering runs and determining consensus(60, 63)