Additional file 1 of scSemiAE: a deep model with semi-supervised learning for single-cell transcriptomics

Additional file 1. Results for the first experiment Change of ARI (Louvain & K-means) and ACC (kNN) values with the increasing labeled proportion for six　methods　(AE, netAE, PCA, scSemiAE, scANVI and scVI) and four datasets(Cortex, Heart, Limb Muscle and　Embryos). In addition, mean and std is the mean and standard deviation.

附加文件1. 首次实验结果：针对六种方法（自动编码器（AutoEncoder，AE）、netAE、主成分分析（Principal Component Analysis，PCA）、scSemiAE、scANVI及scVI）与四个数据集（Cortex、Heart、Limb Muscle及Embryos），展示基于卢万（Louvain）社区检测算法与K-means聚类得到的调整兰德指数（Adjusted Rand Index，ARI），以及基于k近邻（k-Nearest Neighbor，kNN）算法得到的准确率（Accuracy，ACC）值随标记样本比例升高的变化情况。此外，文中所用的mean与std分别指代平均值与标准差。