The following steps were taken to minimize dependencies and ensure that diceR can still run on R 3.5:
Removed cli and RColorBrewer from Imports
Moved apcluster, blockcluster, cluster, dbscan, e1071, kernlab, and kohonen to Suggests, use their specific clustering algorithms conditionally. mclust needs to be in Imports because mclust::mclustBIC() needs to be imported
Moved sigclust to Suggests, use within sigclust() conditionally
Moved progress to Suggests, use within consensus_cluster() conditionally
Moved poLCA to Suggests, use within dice() conditionally
Moved Rtsne to Suggests, use within prepare_data() conditionally
Removed old dependency grDevices from Imports
Set minimum version to R (>= 3.5) for klaR dependency questionr
In ev_confmat(), use yardstick::conf_mat() instead of caret::confusionMatrix(). caret has many dependencies, so best to avoid using it
In graph_heatmap(), use NMF::aheatmap() instead of gplots::heatmap.2(). gplots depends on caTools, which now relies on R (>= 3.6)
In consensus_cluster(), use stringr::str_to_title() instead of Hmisc::capitalize(). Hmisc depends on latticeExtra, which now relies on R (>= 3.6)
In graph_delta_area(), use base solution instead of flux::auc(). flux also depends on caTools
In prepare_data(), use own implementation of quantable::robustscale() with all of the former function’s defaults. quantable also depends on caTools
Specify Bioconductor installation on Travis and AppVeyor since NMF now Imports Biobase
Remove suppressWarnings(RNGversion("3.5.0")) after updating R version
Run LCA() unit test on imputed clustering object
Remove internal validity measures with any Inf entries for consensus_reweigh()
Use a cleaner, more robust method of removing Rplots.pdf after running test-graphs.R
Ensure column binding with purrr::map_dfc() in consensus_rank()
Replaced dplyr::bind_cols() with purrr::flatten_dfc() to suppress warning “Outer names are only allowed for unnamed scalar” in get_cdf()
update roxygen and docs
Remove deprecated dplyr functions and use .data pronoun
k-means clustering should not support distance matrices as input (@jerryji1993, #139)
Add LCA as a consensus function (@philstraforelli, #137)
Fix length > 1 in coercion to logical error in consensus_evaluate() due to comparisons using || operator
Add suppressWarnings(RNGversion("3.5.0")) before call to set.seed() in examples, tests, and vignette to use old RNG sampling
Use .covrignore to exclude zzz.R from being considered in code coverage
Use dplyr version >= 0.7.5 to ensure bind_rows() works
Fixed bug where scaled matrix using the “robust” method in prepare_data() was nested in the data element (@AlineTalhouk, #134)
Add parameter hc.method in dice and consensus_cluster to pass to method parameter in stats::hclust (@JakeNel28, #130)
Remove dependencies on largeVis: package will be archived
Revert back to using NMF since NNLM has been archived and NMF is back in active maintenance.
Choose fuzzifier m in cmeans using Equation 5 from https://academic.oup.com/bioinformatics/article/26/22/2841/227572 (thanks @Asduveneck)
Replace all code that depended on NMF with NNLM and pheatmap: CRAN notified that NMF will be archived because of inactive maintenance
Update .yml files default templates
Fix bug in consensus_cluster() when custom algorithms were excluded from output (thanks @phiala)
Use markdown language for documentation
Various performance improvements and code simplifications
Suppress success/fail message printout and fix input data to be matrix for block clustering
Fix bug in algii_heatmap() when k.method = "all" in dice()
Fix bug in calculating internal indices when data has categorical variables (thanks Kurt Salmela)
Updated object output names in consensus_evaluate()
Fix unit test in test-dice.R for R-devel
Add internal function: ranked algorithms vs internal validity indices heatmap graph
Fix bugs in graph_cdf(), graph_tracking() when only one k selected
Progress messages in dice()
Fix bug in consensus_evaluate() when algorithm has NA for all PAC values
New dimension reduction methods: t-SNE, largeVis (@dustin21)
Better annotated progress bar using progress package
Speed up the operation that transforms a matrix to become “NMF-ready”
Simplify saving mechanism in consensus_cluster() such that only file.name needs to be specified, and the save parameter has been removed
New algorithms: SOM, Fuzzy C-Means, DBSCAN (@dustin21, #118)
Added significance testing section to vignette
Fixed direction of optimization: compactness and connectivity should be minimized