NEWS.md

v1.11.2

• Remove the dependency on the harmony package. The maximum diversity clustering step that align_harmony relies on is now implemented natively in pure R (see init_max_diversity_clustering/run_max_diversity_clustering), avoiding breakage from upstream harmony changes. align_harmony's behavior and arguments are unchanged.

v1.3

• lemur now automatically inserts the variables from the design formula into the group_by argument for find_de_neighborhoods. (thanks Katha for pushing for this feature)
• The formula parsing automatically detects global variables and adds them to the colData. This avoids problems with the random test / training assignment.
• Duplicate column names in colData are now longer allowed.
• Require harmony version >= 1.2.0 (thanks Maija for reporting the problem)

v1.1

• Make predict function faster and less memory intensive for subset fits.
• Speed-up internal function get_groups
• Gracefully handle duplicated column names in colData(fit)
• Give better error message in test_de if cond(..) is used for a fit that was not specified with a design formula (thanks @MaximilianNuber for reporting)

v1.0

• Bug fix in subsetting logic affecting predict and test_de. The problem occured if a fit object was subsetted with indices or gene names and the order changed, and resulted in a wrong order of the predictions.

v0.99.1-0.99.8

• Submission to Bioconductor, thus the jump in version number.
• Adjusted internal code to handle breaking changes in harmony v1.0.0.
• Multiple small fixes to comply with Bioconductor guidelines (see Bioconductor/Contributions#3152)

v0.0.27

• Instead of include_complement, the find_de_neighborhoods function gains a add_diff_in_diff argument. If it is true, the function calculates the difference between the DE results inside the neighborhood vs. outside.
• Change indices columns to neighborhood and store list of cell name vectors in output of find_de_neighborhoods.
• Enforce unique column and row names.

v0.0.26

• Make the neighborhoods more consistent: (1) include cells which are connected to many cells inside the neighborhood, (2) exclude cells from the neighborhood which are not well connected to the other cells in the neighborhood.
• Add a control_parameters argument to find_de_neighborhoods.
• Add BiocNeighbor as a dependency.

v0.0.25

• Detect problematic neighborhoods and skip them.
• Replace test_data_cell_size_factors by size_factor_method, which is more flexibel. Setting size_factor_method = "ratio" uses the size factor method described in the original DESeq paper

v0.0.24

• Fix bug in find_de_neighborhoods that meant that accidentally additionally zeros where included in each neighborhood pseudobulk. The test should have more power now.
• Expose min_neighborhood_size argument in find_de_neighborhoods.
• Add test_data_cell_size_factors argument to find_de_neighborhoods which is useful if the function is called with a subsetted fit argument.

v0.0.23

• Improve alignment functions: simplify algorithm, find linear approximation to Harmony's steps, include an intercept.
• Avoid calling private methods from harmony.
• Convert character columns in colData to factors to avoid problems when dividing data into test and training data.
• Fix bug in find_de_neighborhoods where I didn't embrace an argument.
• Remove BiocNeighbors dependency.

v0.0.21

• Minor bug fix in find_de_neighborhoods. The function threw an error if alignment_design != design.
• Better error messages if find_de_neighborhoods is called without having called test_de before.

v0.0.20

• Change defaults for find_de_neighborhoods. Increase the ridge_penalty and add a min_neighborhood_size = 10 argument to avoid creation of very small neighborhoods.

v0.0.19

• Add new test_fraction argument to lemur() function. It automatically defines a hold-out datasets for the fitting step. These hold-out data is used to infer the differential expression of the neighborhoods in find_de_neighborhoods. This change addresses the double-dipping problem, where it was previously left to the user to provide an independent matrix for the find_de_neighborhoods function.
• As a consequence of these changes, the structure of lemur_fit objects has changed. They gain three new fields called fit$test_data, fit$training_data, and fit$is_test_data.
• The order and names of the arguments for find_de_neighborhoods has changed.

v0.0.18

• Remove alignment_method field from lemur_fit objects as it was not used for anything.

v0.0.17

• Rename argument name for align_by_template from alignment_template to template
• Tweak algorithm for alignment to take cluster sizes into account during optimization

v0.0.13-v0.0.16

• Change in the alignment model. Previously, the method tried to align cells using rotations and / or stretching, however, the method could not represent reflections! To fix this, I now allow arbitrary linear transformations where $R(x) = (I + sum_k x_k V_k)^{-1}$. The new alignment is more flexible and easier to infer. The downside is the term inside the parantheses can be singular which would lead to an error.
• Skip iteration step: first infer centering and then infer latent space. Previously, I iterated between these steps but that either didn't add anything or actually degraded the results.
• Set center = FALSE in find_base_point. Centering the data before fitting the base point caused problems and made the data look less integrated in some cases.
• Remove ambient PCA step. This was originally conceived as an performance optimization, however it had detrimental effects on the inference. Since a few version it was skipped per default, so removing it should not change the inference.
• Add linear_coefficient_estimator to give more flexibility how or if the conditions are centered.
• Reduce the minimum_cluster_membership default to 0.001 in align_harmony to make it more sensitive.
• Make test_global an internal function again until further more extensive testing.
• Remove base_point argument from lemur(). It wasn't used anyways.

pre v0.0.13

• Refactor find_de_neighborhoods: the function can now combine the results of different directions, selection criteria, and pseudobulk test (on counts or continuous values). To implement this, I changed the names of the arguments and added parameters.
• Remove many superfluous method generics and only provide the accession via $
• Fix documentation warnings
• Rename class from 'lemur_fit_obj' to 'lemur_fit'
• Store 'contrast' in lemur_fit after calling test_de
• Add option to fit count model in find_de_neighborhoods with edgeR