sctransform_pancreas_hackathon.h5ad

The results of sctransfrom are stored in layers with the “SCT” prefix. SCT_normalized contains the residuals (normalized values), and is used directly as input to PCA. To assist with visualization and interpretation. we also convert Pearson residuals back to ‘corrected’ UMI counts. You can interpret these as the UMI counts we would expect to observe if all cells were sequenced to the same depth. The ‘corrected’ UMI counts are stored in <code>SCT_corrected_UMI</code>. We store log-normalized versions of these corrected counts in <code>SCT_lognorm_corrected_UMI</code>, which are very helpful for visualization.You can use the corrected log-normalized counts for differential expression and integration. However, in principle, it would be most optimal to perform these calculations directly on the residuals (stored in the <code>SCT_normalized</code> slot) themselves.sctransfrom分析结果存储于带有"SCT"前缀的数据层中。其中，<code>SCT_normalized</code>包含残差（归一化值），可直接作为主成分分析（Principal Component Analysis，PCA）的输入。为辅助可视化与结果解析，我们还将皮尔逊残差转换为“校正后的”唯一分子标识符（Unique Molecular Identifier，UMI）计数，可将其理解为：当所有细胞的测序深度均一致时，我们预期观测到的UMI计数。“校正后的”UMI计数存储于<code>SCT_corrected_UMI</code>中。我们将这些校正后计数的对数归一化版本存储于<code>SCT_lognorm_corrected_UMI</code>，该结果对可视化工作极具帮助。你可使用校正后的对数归一化计数进行差异表达分析与数据整合分析。不过原则上，直接对存储于<code>SCT_normalized</code>槽位中的残差执行此类计算才是最优方案。