News
All notable changes will be documented in this file.
Unreleased
Fixed
- Fixed citation orcid
 
- Fix for future_lapply when using a single core #201
 
[0.4.1] - 2023-10-18
Fixed
- Fixed column name setting in 
fit_nb_offset 
Changed
- Verbose messages when invoking 
v2: messages are only
invoked if verbosity > 1. 
[0.4.0] - 2023-09-18
Added
- Add 
fit_nb_offset to support vst.flavor=‘v2’ by
default 
Fixed
- 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
- 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 
[0.3.5] - 2022-09-21
Fixed
- Specify required Matrix version to >= 1.5.0
 
[0.3.4] - 2022-08-19
Added
- Add 
make.sparse to handle dgCMatrix
coercsions 
Fixed
- Convert bitwise operators to boolean operators in utils.cpp
 
[0.3.3] - 2022-01-13
Added
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 
[0.3.2] - 2021-07-28
Added
- Add future.seed = TRUE to all 
future_lapply()
calls 
Changed
- Wrap MASS::theta.ml() in suppressWarnings()
 
Fixed
- Fix logical comparison of vectors of length one in
diff_mean_test() 
[0.3.2] - 2020-02-11
Added
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() 
Changed
- Major speed improvements for 
diff_mean_test() 
- Changed the 
labels argument to
group_labels in diff_mean_test() 
Fixed
- Fix bug where factors in cell attributes gave error when checking
for NA, NaN, inf
 
[0.3.2] - 2020-12-16
Added
- 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
 
Changed
- 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
 
Fixed
- 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) 
[0.3.1] - 2020-10-08
Added
- Add a 
qpoisson method for parameter estimation that
uses fast Rcpp quasi poisson regression where possible (based on
Rfast package); this adds RcppArmadillo
dependency 
Changed
- 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
 
Fixed
- Fix inefficiency of using 
match.call() in
vst() when called via do.call 
[0.3] - 2020-09-19
Added
- 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 
Changed
- 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
 
Fixed
- Some non-regularized model parameters were not plotted
 
[0.2.1] - 2019-12-17
Added
- 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
 
[0.2.0] - 2019-04-12
Added
- Rcpp versions of utility functions
 
- Helper functions to get corrected UMI and variance of pearson
residuals for large UMI matrices
 
Changed