版本变化1.13.1 (2020-08-17)______________________________________ o在测试不同比例的0,如果贝叶斯逻辑回归不能收敛对于一个给定的基因(例如,如果有完美的分离条件),那么将返回NA(而不是抛出错误。1.3.4版本的变化(2018-03-26)______________________________________ o 0现在使用的测试不同比例瓦尔德测试假定值而不是似然比。这将给非常类似的结果,但瓦尔德测试稍微保守。v1.3.3变化(2018-03-23)______________________________________ o添加了一个选项跳过的分类步骤如果intereseted意义不同。这将加速计算。o和KS测试测试零一步并行加速计算。1.1.7版的变化(2017-10-23)_____________________________________ o参数“水平”添加到主“scDD”功能,允许用户控制的显著性水平作为截止考虑基因差异分布。以前是固定在0.05(现在是默认值)。o两列添加到结果对象,包含(1)全面结合假定值(通过费雪的方法)的非零和零差异,和(2)Benjamini-Hochberg调整(1)的版本。如果‘testZeroes’是假的啊,假定值的列微分辍学的测试不再是包括在内。以前他们举行了NA的价值观。 o If `testZeroes` is TRUE, all zero test p-values are included in the output. Previously, only the tests where the nonzero test was not significant were reported. Changes in Version 1.1.5 (2017-09-27) _____________________________________ o The input and output object of the main scDD function has been changed from SummarizedExperiment to SingleCellExperiment to increase interoperability among other Bioconductor packages o The simulateSet function now returns a SingleCellExperiment object (previously it returned an object in list format) o The preprocess function now takes as input a SingleCellExperiment object instead of a list of data frames Changes in Version 1.0.0 (2017-04-23) _____________________________________ o This is the Bioconductor 3.5 Release version o scDD is a package for identifying differentially distributed genes in single-cell RNA-seq data. It is designed to detect differences in expression that are more complex than a simple mean shift, including: - traditional differential expression (DE) - differential modality (DM) - differential proportion of cells in each state (DP) - both differential modality and differential proportion (DB) Changes in Version 0.99.0 (2016-12-07) ______________________________________ o Initial Bioconductor submission version.