Version 1.5 (Development Version) + Choose a more reasonable scale for global overdispersion estimate + Make code more robust accidental internal NA's + Add fallback mechanism in case the Fisher scoring fails to converge. Instead of returing NA, try again using the BFGS algorithm. + Better error message if the design contains NA's Version 1.4 (2021-05-19) + Ridge regularization framework. glmGamPoi now supports regularizing the coefficient estimates using a quadratic penalty function. Furthmore, more advanced regularization schemes, such as regularizing towards a specific value and full Tikhonov regularization are implemented. + New predict() function. Also supports estimating the standard error of the mean estimate. + Make sure that Fisher scoring does not converge to unrealistically large values of mu + Fix minor bug in test_de() concerning the calculation of the degree of freedom + Fix minor bug in calculation of working and Pearson residuals, which used to return NaN if mu was 0. Now, they are 0. + Improve vignette/Readme: add section on differential expression analysis with Kang et al. (2018) as example data + `glm_gp` returns the Offset matrix and bug fix for test_de() if a offset was specified + Add CITATION file + Make sure that residuals are pristine (when the input was a DelayedArray) + Set dimnames of residuals + Improve error message if input is a sparse matrix Version 1.2 (2020-11-09) + Remove dual likelihood functions for overdispersion estimation. Instead merge functionality into conventional_***. This should cause no user facing changes, however should make it easier to maintain the package + Make conventional_score_function_fast() more robust to extreme inputs. Avoid numerically imprecise subtractions and employ bounds based on series expansions for very small input + If dispersion estimate quits because there is no maximum or all y are 0, return iterations = 0 + Add limits (1e-16 / 1e16) for nlminb estimates of the dispersion. This protects against errors due to NA's in the conventional_likelihood_fast + Automatically set 'size_factors = FALSE' for input with 0 or 1 row. This will change the estimated beta, but not the mu's + Rename gampoi_overdispersion_mle() -> overdispersion_mle() + Store data in the object returned by glm_gp() + Remove Y from the interface of residuals.glmGamPoi, because I can just get it directly from fit$data + Add function test_de() that does a quasi-likelihood ratio test to detect differentially expressed genes + Add functionality to make a pseudobulk test directly from test_de() by aggregating the data around one column + In group-wise beta estimation, fall back to optimize() if the Newton method fails + Change the default size factor estimation method from "poscounts" to "normed_sum" and provide an easy way to call scran::calculateSumFactors() + New "global" mode for dispersion estimation Changes in version 0.0.99 (2020-03-23) + Submitted to Bioconductor