scprep 0.12.2

安装

预处理在pip上可用。在终端中运行以下命令进行安装：

pip install --user scprep

或者，可以使用Conda（最容易通过Miniconda Python distribution获得）安装scprep：

conda install -c bioconda scprep

快速启动

您可以对单个单元格数据使用scprep，如下所示：

import scprep
# Load data
data_path = "~/mydata/my_10X_data"
data = scprep.io.load_10X(data_path)
# Remove empty columns and rows
data = scprep.filter.remove_empty_cells(data)
data = scprep.filter.remove_empty_genes(data)
# Filter by library size to remove background
scprep.plot.plot_library_size(data, cutoff=500)
data = scprep.filter.filter_library_size(data, cutoff=500)
# Filter by mitochondrial expression to remove dead cells
mt_genes = scprep.select.get_gene_set(data, starts_with="MT")
scprep.plot.plot_gene_set_expression(data, genes=mt_genes, percentile=90)
data = scprep.filter.filter_gene_set_expression(data, genes=mt_genes,
                                                percentile=90)
# Library size normalize
data = scprep.normalize.library_size_normalize(data)
# Square root transform
data = scprep.transform.sqrt(data)

示例

• Scatter plots
• Jitter plots

帮助

如果您有任何问题或需要使用scprep的帮助，请阅读https://scprep.readthedocs.io/上的文档或通过https://krishnaswamylab.org/get-help与我们联系