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NEWS

All notable changes will be documented in this file.

• Fixed citation orcid
• Fix for future_lapply when using a single core #201

• Fixed column name setting in fit_nb_offset

• Verbose messages when invoking v2: messages are only invoked if verbosity > 1.

• Add fit_nb_offset to support vst.flavor=‘v2’ by default

• Updated cpp utilities to adhere to C++17 standards (std::random_shuffle -> std::shuffle)
• Handling of extra variables in latent_var when vst.flavor="v2"

• Changed get_nz_median2 to support genes argument; thanks @boomanaiden154 and @ScreachingFire. #155
• Replaced get_nz_median with faster alternative get_nz_median2 across all calls
• Removed get_nz_median
• Updated make_cell_attr to be flexible for named vectors; thanks @moi-taga #171

• Specify required Matrix version to >= 1.5.0

• Add make.sparse to handle dgCMatrix coercsions

• Convert bitwise operators to boolean operators in utils.cpp

• vst.flavor argument to vst() to allow for invoking running updated regularization (sctransform v2, proposed in Satija and Choudhary, 2021. See paper for details.
• scale_factor to correct() to allow for a custom library size when correcting counts

• Add future.seed = TRUE to all future_lapply() calls

• Wrap MASS::theta.ml() in suppressWarnings()

• Fix logical comparison of vectors of length one in diff_mean_test()

• compare argument to the nonparametric differential expression test diff_mean_test() to allow for multiple comparisons and various ways to specify which groups to compare
• Input checking at various places in vst() and diff_mean_test()

• Major speed improvements for diff_mean_test()
• Changed the labels argument to group_labels in diff_mean_test()

• Fix bug where factors in cell attributes gave error when checking for NA, NaN, inf

• Ability to control the values of latent variables when calculating corrected counts
• Offset model as method, including the ability to use a single estimated theta for all genes
• Nonparametric differential expression test for sparse non-negative data

• Improve poor coefficient initialization in quasi poisson regression
• When plotting model, do not show density by default; change bandwidth to bw.nrd0
• Updates to C++ code to use sparse matrices as S4 objects
• Add check for NA, NaN, Inf values in cell attributes

• Remove biocViews from DESCRIPTION - not needed and was causing problems with deploying shiny apps
• Fix bug where a coefficient was given the wrong name when using glmGamPoi (only affected runs with a batch variable set)

• Add a qpoisson method for parameter estimation that uses fast Rcpp quasi poisson regression where possible (based on Rfast package); this adds RcppArmadillo dependency

• Remove poisson_fast method (replaced by qpoisson)
• Use matrixStats package and remove RcppEigen dependency
• Use quasi poisson regression where possible
• Define cell detection event as counts >= 0.01 (instead of > 0) - this only matters to people playing around with fractional counts (see issue #65)
• Internal code restructuring and improvements

• Fix inefficiency of using match.call() in vst() when called via do.call

• Add support for glmGamPoi as method to estimate the model parameters; thanks @yuhanH for his pull request
• Add option to use theta.mm ortheta.ml to estimate theta when method = 'poisson' or method = 'nb_fast'
• Add a poisson_fast method for parameter estimation that uses the speedglm package and theta.mm by default
• Add ability to plot overdispersion factor in plot_model_pars
• Add and return time stamps at various steps in the vst function
• Add functions to calculate grouped arithmetic and geometric mean per row for sparse matrices (dgCMatrix) - might come in handy some time

• Default theta regularization is now based on overdispersion factor (1 + m / theta where m is the geometric mean of the observed counts) not log10(theta); old behavior available via theta_regularization parameter
• Refactored model fitting code - is now more efficient when using parallel processing
• Changed how message and progress bar output is controlled; integer verbosity parameter controls all output: 0 for no output, 1 for only messages, 2 for messages and progress bars
• Increased default bin size (genes being processed simultaneously) from 256 to 500
• Better input checking for cell attributes; more efficient calculation of missing ones

• Some non-regularized model parameters were not plotted

• Add function to generate data given the output of a vst run
• Add cpp support for dense integer matrices
• Minimum variance parameter added to vst function

• Rcpp versions of utility functions
• Helper functions to get corrected UMI and variance of pearson residuals for large UMI matrices

• lots of things

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