Mercurial > repos > iuc > scanpy_remove_confounders
comparison README.md @ 17:b70219da4a96 draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 91121b1e72696f17478dae383badaa71e9f96dbb
| author | iuc |
|---|---|
| date | Sat, 14 Sep 2024 12:43:38 +0000 |
| parents | a89ee42625ad |
| children |
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| 16:a39040ae0a38 | 17:b70219da4a96 |
|---|---|
| 23 `pp.filter_genes` | Filter genes based on number of cells or counts. | 23 `pp.filter_genes` | Filter genes based on number of cells or counts. |
| 24 `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**) | 24 `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**) |
| 25 `pp.highly_variable_genes` | Extract highly variable genes | 25 `pp.highly_variable_genes` | Extract highly variable genes |
| 26 `pp.subsample` | Subsample to a fraction of the number of observations | 26 `pp.subsample` | Subsample to a fraction of the number of observations |
| 27 `pp.downsample_counts` | Downsample counts so that each cell has no more than target_counts | 27 `pp.downsample_counts` | Downsample counts so that each cell has no more than target_counts |
| 28 `pp.scrublet` | Predict doublets | |
| 28 | 29 |
| 29 3. Normalize (`normalize.xml`) | 30 3. Normalize (`normalize.xml`) |
| 30 | 31 |
| 31 Methods | Description | 32 Methods | Description |
| 32 --- | --- | 33 --- | --- |
| 33 `pp.normalize_total` | Normalize counts per cell | 34 `pp.normalize_total` | Normalize counts per cell |
| 34 `pp.recipe_zheng17` | Normalization and filtering as of [Zheng17] | 35 `pp.recipe_zheng17` | Normalization and filtering as of [Zheng17] |
| 35 `pp.recipe_weinreb17` | Normalization and filtering as of [Weinreb17] | 36 `pp.recipe_weinreb17` | Normalization and filtering as of [Weinreb17] |
| 36 `pp.recipe_seurat` | Normalization and filtering as of Seurat [Satija15] | 37 `pp.recipe_seurat` | Normalization and filtering as of Seurat [Satija15] |
| 38 `external.pp.magic` | Denoising using Markov Affinity-based Graph Imputation of Cells (MAGIC) API | |
| 37 | 39 |
| 38 4. Remove confounders (`remove_confounder.xml`) | 40 4. Remove confounders (`remove_confounder.xml`) |
| 39 | 41 |
| 40 Methods | Description | 42 Methods | Description |
| 41 --- | --- | 43 --- | --- |
| 42 `pp.regress_out` | Regress out unwanted sources of variation | 44 `pp.regress_out` | Regress out unwanted sources of variation |
| 43 `pp.mnn_correct` | Correct batch effects by matching mutual nearest neighbors | 45 <!-- `pp.mnn_correct` | Correct batch effects by matching mutual nearest neighbors --> |
| 44 `pp.combat` | ComBat function for batch effect correction | 46 `pp.combat` | ComBat function for batch effect correction |
| 47 `external.pp.bbknn` | Batch effect removal with Batch balanced KNN (BBKNN) | |
| 48 `external.pp.harmony_integrate` | Integrate multiple single-cell experiments with Harmony | |
| 49 `external.pp.scanorama_integrate` | Integrate multiple single-cell experiments with Scanorama | |
| 45 | 50 |
| 46 5. Clustering, embedding and trajectory inference (`cluster_reduce_dimension.xml`) | 51 5. Clustering, embedding and trajectory inference (`cluster_reduce_dimension.xml`) |
| 47 | 52 |
| 48 Methods | Description | 53 Methods | Description |
| 49 --- | --- | 54 --- | --- |
| 50 `tl.louvain` | Cluster cells into subgroups | 55 `tl.louvain` | Cluster cells into subgroups |
| 51 `tl.leiden` | Cluster cells into subgroups | 56 `tl.leiden` | Cluster cells into subgroups |
| 52 `tl.pca` | Principal component analysis | 57 `pp.pca` | Principal component analysis |
| 53 `pp.pca` | Principal component analysis (appears to be the same func...) | |
| 54 `tl.diffmap` | Diffusion Maps | 58 `tl.diffmap` | Diffusion Maps |
| 55 `tl.tsne` | t-SNE | 59 `tl.tsne` | t-SNE |
| 56 `tl.umap` | Embed the neighborhood graph using UMAP | 60 `tl.umap` | Embed the neighborhood graph using UMAP |
| 57 `tl.draw_graph` | Force-directed graph drawing | 61 `tl.draw_graph` | Force-directed graph drawing |
| 58 `tl.dpt` | Infer progression of cells through geodesic distance along the graph | 62 `tl.dpt` | Infer progression of cells through geodesic distance along the graph |
| 59 `tl.paga` | Mapping out the coarse-grained connectivity structures of complex manifolds | 63 `tl.paga` | Mapping out the coarse-grained connectivity structures of complex manifolds |
| 64 `tl.embedding_density` | Calculate the density of cells in an embedding (per condition) | |
| 60 | 65 |
| 61 6. Plot (`plot.xml`) | 66 6. Plot (`plot.xml`) |
| 62 | 67 |
| 63 1. Generic | 68 1. Generic |
| 64 | 69 |
| 65 Methods | Description | 70 Methods | Description |
| 66 --- | --- | 71 --- | --- |
| 67 `pl.scatter` | Scatter plot along observations or variables axes | 72 `pl.scatter` | Scatter plot along observations or variables axes |
| 68 `pl.heatmap` | Heatmap of the expression values of set of genes | 73 `pl.heatmap` | Heatmap of the expression values of set of genes |
| 74 `pl.tracksplot` | Tracks plot of the expression values per cell | |
| 69 `pl.dotplot` | Makes a dot plot of the expression values | 75 `pl.dotplot` | Makes a dot plot of the expression values |
| 70 `pl.violin` | Violin plot | 76 `pl.violin` | Violin plot |
| 71 `pl.stacked_violin` | Stacked violin plots | 77 `pl.stacked_violin` | Stacked violin plots |
| 72 `pl.matrixplot` | Heatmap of the mean expression values per cluster | 78 `pl.matrixplot` | Heatmap of the mean expression values per cluster |
| 73 `pl.clustermap` | Hierarchically-clustered heatmap | 79 `pl.clustermap` | Hierarchically-clustered heatmap |
| 74 | 80 |
| 75 2. Preprocessing | 81 2. Preprocessing |
| 76 | 82 |
| 77 Methods | Description | 83 Methods | Description |
| 78 --- | --- | 84 --- | --- |
| 79 `pl.highest_expr_genes` | Plot the fraction of counts assigned to each gene over all cells | 85 `pl.highest_expr_genes` | Plot the fraction of counts assigned to each gene over all cells |
| 80 `pl.highly_variable_genes` | Plot dispersions versus means for genes | 86 `pl.highly_variable_genes` | Plot dispersions versus means for genes |
| 87 `pl.scrublet_score_distribution` | Histogram of doublet scores | |
| 81 | 88 |
| 82 3. PCA | 89 3. PCA |
| 83 | 90 |
| 84 Methods | Description | 91 Methods | Description |
| 85 --- | --- | 92 --- | --- |
| 94 --- | --- | 101 --- | --- |
| 95 `pl.tsne` | Scatter plot in tSNE basis | 102 `pl.tsne` | Scatter plot in tSNE basis |
| 96 `pl.umap` | Scatter plot in UMAP basis | 103 `pl.umap` | Scatter plot in UMAP basis |
| 97 `pl.diffmap` | Scatter plot in Diffusion Map basis | 104 `pl.diffmap` | Scatter plot in Diffusion Map basis |
| 98 `pl.draw_graph` | Scatter plot in graph-drawing basis | 105 `pl.draw_graph` | Scatter plot in graph-drawing basis |
| 106 `pl.embedding_density` | Density of cells in an embedding (per condition) | |
| 99 | 107 |
| 100 5. Branching trajectories and pseudotime, clustering | 108 5. Branching trajectories and pseudotime, clustering |
| 101 | 109 |
| 102 Methods | Description | 110 Methods | Description |
| 103 --- | --- | 111 --- | --- |
| 104 `pl.dpt_groups_pseudotime` | Plot groups and pseudotime | 112 <!-- `pl.dpt_groups_pseudotime` | Plot groups and pseudotime --> |
| 105 `pl.dpt_timeseries` | Heatmap of pseudotime series | 113 `pl.dpt_timeseries` | Heatmap of pseudotime series |
| 106 `pl.paga` | Plot the abstracted graph through thresholding low-connectivity edges | 114 `pl.paga` | Plot the abstracted graph through thresholding low-connectivity edges |
| 107 `pl.paga_compare` | Scatter and PAGA graph side-by-side | 115 `pl.paga_compare` | Scatter and PAGA graph side-by-side |
| 108 `pl.paga_path` | Gene expression and annotation changes along paths | 116 `pl.paga_path` | Gene expression and annotation changes along paths |
| 109 | 117 |
| 111 | 119 |
| 112 Methods | Description | 120 Methods | Description |
| 113 --- | --- | 121 --- | --- |
| 114 `pl.rank_genes_groups` | Plot ranking of genes using dotplot plot | 122 `pl.rank_genes_groups` | Plot ranking of genes using dotplot plot |
| 115 `pl.rank_genes_groups_violin` | Plot ranking of genes for all tested comparisons | 123 `pl.rank_genes_groups_violin` | Plot ranking of genes for all tested comparisons |
| 124 `pl.rank_genes_groups_stacked_violin` | Plot ranking of genes as stacked violin plot | |
| 125 `pl.rank_genes_groups_heatmap` | Plot ranking of genes as heatmap plot | |
| 126 `pl.rank_genes_groups_dotplot` | Plot ranking of genes as dotplot plot | |
| 127 `pl.rank_genes_groups_matrixplot` | Plot ranking of genes as matrixplot plot | |
| 128 `pl.rank_genes_groups_tracksplot` | Plot ranking of genes as tracksplot plot |