版本1.5(开发版)+选择更合理的规模为全球overdispersion估计+使代码更健壮的意外内部NA +添加回退机制以防费舍尔得分无法收敛。而不是杀敌NA,再试一次使用蓄热的算法。+更好的错误消息,如果设计包含NA的版本1.4(2021-05-19)+岭正则化框架。glmGamPoi现在支持使用二次罚函数正则化系数估计。而且,更高级的正规化方案,如正则化对一个特定值和充分实现Tikhonov正则化。+新预测()函数。还支持估计平均数标准误差估计。+确保费舍尔得分不收敛于不切实际的大值μ+修复小虫test_de()有关的计算自由度+修复小虫在工作和皮尔森残差计算,用于返回NaN如果μ是0。现在,他们都是0。+提高装饰图案/自述:添加部分差异表达分析与康et al .(2018)示例数据+“glm_gp”返回test_de的偏移矩阵和故障修复()如果一个抵消指定+添加引用文件+确保剩余工资原始(当输入是DelayedArray) +集dimnames剩余工资+改善错误消息如果输入是一个稀疏矩阵版本1.2(2020-11-09)+消除双重overdispersion似然函数估计。 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