Bump version number, update CRAN comments, readme and news

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: sctransform
 Type: Package
 Title: Variance Stabilizing Transformations for Single Cell UMI Data
-Version: 0.3.0.9004
+Version: 0.3.1
 Authors@R: person(given = 'Christoph', family = 'Hafemeister', email = '[email protected]', role = c('aut', 'cre'), comment = c(ORCID = '0000-0001-6365-8254'))
 Description: A normalization method for single-cell UMI count data using a 
   variance stabilizing transformation. The transformation is based on a 

NEWS.md

@@ -1,6 +1,20 @@
 # News
 All notable changes will be documented in this file.
 
+## [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](https://github.com/ChristophH/sctransform/issues/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

README.md

@@ -18,12 +18,20 @@ Available vignettes:
 [Using sctransform in Seurat](https://rawgit.com/ChristophH/sctransform/master/supplement/seurat.html)  
 
 ## News
+For a detailed change log have a look at the file [NEWS.md](https://github.com/ChristophH/sctransform/blob/master/NEWS.md)
+
+### v0.3.1
+This release fixes a performance regression when `sctransform::vst` was called via `do.call`, as is the case in the Seurat wrapper. 
+
+Additionally, model fitting is significantly faster now, because we use a fast Rcpp quasi poisson regression implementation (based on `Rfast` package). This applies to methods `poisson`, `qpoisson` and `nb_fast`.
+
+The `qpoisson` method is new and uses the dispersion parameter from the quasi poisson regression directly to estimate `theta` for the NB model. This can speed up the model fitting step considerably, while giving similar results to the other methods. [This vignette](https://rawgit.com/ChristophH/sctransform/master/supplement/method_comparison.html) compares the methods.
+
+### v0.3
 The latest version of `sctransform` now supports the [glmGamPoi](https://github.com/const-ae/glmGamPoi) package to speed up the model fitting step. You can see more about the different methods supported and how they compare in terms of results and speed [in this new vignette](https://rawgit.com/ChristophH/sctransform/master/supplement/method_comparison.html).
 
 Also note that 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)`. The old behavior is still available via `theta_regularization` parameter. You can see how this changes (or doesn't change) the results [in this new vignette](https://rawgit.com/ChristophH/sctransform/master/supplement/theta_regularization.html).
 
-For a detailed change log have a look at the file [NEWS.md](https://github.com/ChristophH/sctransform/blob/master/NEWS.md)
-
 
 ## Reference
 Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol 20, 296 (December 23, 2019). [https://doi.org/10.1186/s13059-019-1874-1](https://doi.org/10.1186/s13059-019-1874-1)

cran-comments.md

@@ -1,36 +1,28 @@
 ## Test environments
 * Local install x86_64-apple-darwin17.0 (64-bit), R 4.0.2
 * Winbuilder
-  * devtools::check_win_devel() - x86_64-w64-mingw32 (64-bit), R Under development (unstable) (2020-09-09 r79174)
+  * devtools::check_win_devel() - x86_64-w64-mingw32 (64-bit), R Under development (unstable) (2020-10-05 r79298)
   * devtools::check_win_release() - x86_64-w64-mingw32 (64-bit), R 4.0.2
 * rhub::check_for_cran(platforms = c('ubuntu-gcc-release', 'debian-gcc-devel', 'fedora-clang-devel'))
   * Ubuntu Linux 16.04 LTS, R-release, GCC - R 3.6.1
-  * Debian Linux, R-devel, GCC - R Under development (unstable) (2020-09-12 r79193)
-  * Fedora Linux, R-devel, clang, gfortran - R Under development (unstable) (2020-09-13 r79194)
+  * Debian Linux, R-devel, GCC - R Under development (unstable) (2020-10-02 r79291)
+  * Fedora Linux, R-devel, clang, gfortran - R Under development (unstable) (2020-10-02 r79291)
 
 ## R CMD check results
 
-0 ERRORs, 0 WARNINGs, 2 NOTEs
-
-```
-* checking CRAN incoming feasibility ... NOTE
-Maintainer: 'Christoph Hafemeister <[email protected]>'
-
-New maintainer:
-  Christoph Hafemeister <[email protected]>
-Old maintainer(s):
-  Christoph Hafemeister <[email protected]>
-```
-
-My New York Genome Center email address is no longer functioning. I have switched to my New York University one. This is also the email address listed in the publication associated with this package's description (doi:10.1186/s13059-019-1874-1).
+0 ERRORs, 0 WARNINGs, 1 NOTE
 
 ```
 * checking package dependencies ... NOTE
 Packages which this enhances but not available for checking: 'speedglm', 'glmGamPoi'
 ```
-`speedglm` is an optional package not required for core functionality. It has not been updated in more than three years, hence the choice to put it in Enhance rather than Suggest.
+
 `glmGamPoi` is an entirely optional package that is not required for core functionality, but only needed for alternative/faster implementations of the methods in this package. It is only available on Bioconductor. 
 
 ## Reverse dependencies
 
-There are currently two packages importing sctransform: muscat, Seurat. This update does not impact their functionality.
+There are 2 reverse dependencies (muscat, Seurat). We checked them comparing R CMD check results across CRAN and dev versions of this package.
+
+ * We saw 0 new problems
+
+