v0.99.0： - 生物导体。v1.1.2： - 生物导体接受的Devel版本。v1.1.3： - 新功能：i）自动计算温度级别。ii）在SQTL分析中调整P值的排列方法。V1.1.4： - 创建DMDSDATA和DMSQTLDATA对象时，请使用计数和基因型的数据帧。v1.3.1： - 等于v1.1.4。v1.3.2： - 两阶段测试dmtwostagetest（）的实现。v1.3.3： - 回归框架和功能级分析的实施。另外：i）从dmfilter中删除max_features参数。ii）仅保留估计标签分散的网格方法。 iii) Allow to use only a subset of genes (disp_subset parameter) in common dispersion estimation to speed up the calculations; if disp_subset < 1, use set.seed() to make the analysis reproducible. iv) Always use tagwise dispersion for fitting full and null models. v) In one group fitting, return NA for tags having the last feature with zero counts in all samples. We always use the q-th feature as a denominator in logit calculation. In such a case all the logits are anyways Inf. vi) Use plotPValues instead of plotTest vii) Use 'prop' instead of 'pi' and 'disp' instead of 'gamma0'. viii) Use only 'constrOptim' (old 'constrOptimG') to estimate proportions and 'optim' to estimate coefficients in the regression model. ix) Use plotProportions instead of plotFit. x) No 'out_dir' parameter in plotting functions. All plotting functions return a ggplot object. xi) Use term "precision" instead of "dispersion" as in DRIMSeq we directly estimate the precision parameter. Dispersion can be calculated with formula: dispersion = 1 / (1 + precision).