Mercurial > repos > iuc > scanpy_normalize
view README.md @ 7:a407e7f8bdc1 draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 150c96596b94f9658c8b7c44814c420d38fbee0c"
author | iuc |
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date | Wed, 20 May 2020 16:09:36 -0400 |
parents | a9f14e2d1655 |
children | 5dada6f76047 |
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Scanpy ====== 1. Inspect & Manipulate (`inspect.xml`) Methods | Description --- | --- `pp.calculate_qc_metrics` | Calculate quality control metrics `pp.neighbors` | Compute a neighborhood graph of observations `tl.score_genes` | Score a set of genes `tl.score_genes_cell_cycle` | Score cell cycle gene `tl.rank_genes_groups` | Rank genes for characterizing groups `tl.marker_gene_overlap` | Calculate an overlap score between data-deriven marker genes and provided markers (**not working for now**) `pp.log1p` | Logarithmize the data matrix. `pp.scale` | Scale data to unit variance and zero mean `pp.sqrt` | Square root the data matrix 2. Filter (`filter.xml`) Methods | Description --- | --- `pp.filter_cells` | Filter cell outliers based on counts and numbers of genes expressed. `pp.filter_genes` | Filter genes based on number of cells or counts. `tl.filter_rank_genes_groups` | Filters out genes based on fold change and fraction of genes expressing the gene within and outside the groupby categories (**to fix**) `pp.highly_variable_genes` | Extract highly variable genes `pp.subsample` | Subsample to a fraction of the number of observations `pp.downsample_counts` | Downsample counts so that each cell has no more than target_counts 3. Normalize (`normalize.xml`) Methods | Description --- | --- `pp.normalize_total` | Normalize counts per cell `pp.recipe_zheng17` | Normalization and filtering as of [Zheng17] `pp.recipe_weinreb17` | Normalization and filtering as of [Weinreb17] `pp.recipe_seurat` | Normalization and filtering as of Seurat [Satija15] 4. Remove confounders (`remove_confounder.xml`) Methods | Description --- | --- `pp.regress_out` | Regress out unwanted sources of variation `pp.mnn_correct` | Correct batch effects by matching mutual nearest neighbors `pp.combat` | ComBat function for batch effect correction 5. Clustering, embedding and trajectory inference (`cluster_reduce_dimension.xml`) Methods | Description --- | --- `tl.louvain` | Cluster cells into subgroups `tl.leiden` | Cluster cells into subgroups `tl.pca` | Principal component analysis `pp.pca` | Principal component analysis (appears to be the same func...) `tl.diffmap` | Diffusion Maps `tl.tsne` | t-SNE `tl.umap` | Embed the neighborhood graph using UMAP `tl.draw_graph` | Force-directed graph drawing `tl.dpt` | Infer progression of cells through geodesic distance along the graph `tl.paga` | Mapping out the coarse-grained connectivity structures of complex manifolds 6. Plot (`plot.xml`) 1. Generic Methods | Description --- | --- `pl.scatter` | Scatter plot along observations or variables axes `pl.heatmap` | Heatmap of the expression values of set of genes `pl.dotplot` | Makes a dot plot of the expression values `pl.violin` | Violin plot `pl.stacked_violin` | Stacked violin plots `pl.matrixplot` | Heatmap of the mean expression values per cluster `pl.clustermap` | Hierarchically-clustered heatmap 2. Preprocessing Methods | Description --- | --- `pl.highest_expr_genes` | Plot the fraction of counts assigned to each gene over all cells `pl.highly_variable_genes` | Plot dispersions versus means for genes 3. PCA Methods | Description --- | --- `pl.pca` | Scatter plot in PCA coordinates `pl.pca_loadings` | Rank genes according to contributions to PCs `pl.pca_variance_ratio` | Scatter plot in PCA coordinates `pl.pca_overview` | Plot PCA results 4. Embeddings Methods | Description --- | --- `pl.tsne` | Scatter plot in tSNE basis `pl.umap` | Scatter plot in UMAP basis `pl.diffmap` | Scatter plot in Diffusion Map basis `pl.draw_graph` | Scatter plot in graph-drawing basis 5. Branching trajectories and pseudotime, clustering Methods | Description --- | --- `pl.dpt_groups_pseudotime` | Plot groups and pseudotime `pl.dpt_timeseries` | Heatmap of pseudotime series `pl.paga` | Plot the abstracted graph through thresholding low-connectivity edges `pl.paga_compare` | Scatter and PAGA graph side-by-side `pl.paga_path` | Gene expression and annotation changes along paths 6. Marker genes Methods | Description --- | --- `pl.rank_genes_groups` | Plot ranking of genes using dotplot plot `pl.rank_genes_groups_violin` | Plot ranking of genes for all tested comparisons