Mercurial > repos > iuc > scanpy_inspect

comparison inspect.xml @ 5:6db0499e178b draft

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"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/scanpy/ commit 6b5d0d6f038ebd0fae5dbca02ada51555518ed85"
author iuc
date Mon, 10 Feb 2020 10:19:04 +0000
parents aa453ed171ef
children 530e300424d1
comparison
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4:63f4a966816a 5:6db0499e178b
802 - mean_{expr_type} (e.g. "mean counts", mean expression over all cells) 802 - mean_{expr_type} (e.g. "mean counts", mean expression over all cells)
803 - n_cells_by_{expr_type} (e.g. "n_cells_by_counts", number of cells this expression is measured in) 803 - n_cells_by_{expr_type} (e.g. "n_cells_by_counts", number of cells this expression is measured in)
804 - pct_dropout_by_{expr_type} (e.g. "pct_dropout_by_counts", percentage of cells this feature does not appear in) 804 - pct_dropout_by_{expr_type} (e.g. "pct_dropout_by_counts", percentage of cells this feature does not appear in)
805 805
806 More details on the `scanpy documentation 806 More details on the `scanpy documentation
807 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.calculate_qc_metrics.html>`__ 807 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.pp.calculate_qc_metrics.html>`__
808 808
809 Compute a neighborhood graph of observations, using `pp.neighbors` 809 Compute a neighborhood graph of observations, using `pp.neighbors`
810 ================================================================== 810 ==================================================================
811 811
812 The neighbor search efficiency of this heavily relies on UMAP (McInnes et al, 2018), 812 The neighbor search efficiency of this heavily relies on UMAP (McInnes et al, 2018),
821 - Distances for each pair of neighbors (distances) 821 - Distances for each pair of neighbors (distances)
822 822
823 This data are stored in the unstructured annotation (uns) and can be accessed using the inspect tool for AnnData objects 823 This data are stored in the unstructured annotation (uns) and can be accessed using the inspect tool for AnnData objects
824 824
825 More details on the `scanpy documentation 825 More details on the `scanpy documentation
826 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.neighbors.html>`__ 826 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.pp.neighbors.html>`__
827 827
828 Score a set of genes, using `tl.score_genes` 828 Score a set of genes, using `tl.score_genes`
829 ============================================ 829 ============================================
830 830
831 The score is the average expression of a set of genes subtracted with the 831 The score is the average expression of a set of genes subtracted with the
834 834
835 This reproduces the approach in Seurat (Satija et al, 2015) and has been implemented 835 This reproduces the approach in Seurat (Satija et al, 2015) and has been implemented
836 for Scanpy by Davide Cittaro. 836 for Scanpy by Davide Cittaro.
837 837
838 More details on the `scanpy documentation 838 More details on the `scanpy documentation
839 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.score_genes.html>`__ 839 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.score_genes.html>`__
840 840
841 Score cell cycle genes, using `tl.score_genes_cell_cycle` 841 Score cell cycle genes, using `tl.score_genes_cell_cycle`
842 ========================================================= 842 =========================================================
843 843
844 Given two lists of genes associated to S phase and G2M phase, calculates 844 Given two lists of genes associated to S phase and G2M phase, calculates
845 scores and assigns a cell cycle phase (G1, S or G2M). See 845 scores and assigns a cell cycle phase (G1, S or G2M). See
846 `score_genes` for more explanation. 846 `score_genes` for more explanation.
847 847
848 More details on the `scanpy documentation 848 More details on the `scanpy documentation
849 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.score_genes_cell_cycle.html>`__ 849 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.score_genes_cell_cycle.html>`__
850 850
851 Rank genes for characterizing groups, using `tl.rank_genes_groups` 851 Rank genes for characterizing groups, using `tl.rank_genes_groups`
852 ================================================================== 852 ==================================================================
853 853
854 The returned AnnData object contains: 854 The returned AnnData object contains:
860 - Ajusted p-values 860 - Ajusted p-values
861 861
862 This data are stored in the unstructured annotation (uns) and can be accessed using the inspect tool for AnnData objects 862 This data are stored in the unstructured annotation (uns) and can be accessed using the inspect tool for AnnData objects
863 863
864 More details on the `scanpy documentation 864 More details on the `scanpy documentation
865 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.tl.rank_genes_groups.html>`__ 865 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.tl.rank_genes_groups.html>`__
866 866
867 867
868 Calculate an overlap score between data-deriven marker genes and provided markers (`tl.marker_gene_overlap`) 868 Calculate an overlap score between data-deriven marker genes and provided markers (`tl.marker_gene_overlap`)
869 ============================================================================================================ 869 ============================================================================================================
870 870
873 873
874 Logarithmize the data matrix (`pp.log1p`) 874 Logarithmize the data matrix (`pp.log1p`)
875 ========================================= 875 =========================================
876 876
877 More details on the `scanpy documentation 877 More details on the `scanpy documentation
878 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.log1p.html>`__ 878 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.pp.log1p.html>`__
879 879
880 Scale data to unit variance and zero mean (`pp.scale`) 880 Scale data to unit variance and zero mean (`pp.scale`)
881 ====================================================== 881 ======================================================
882 882
883 More details on the `scanpy documentation 883 More details on the `scanpy documentation
884 <https://icb-scanpy.readthedocs-hosted.com/en/stable/api/scanpy.pp.scale.html>`__ 884 <https://icb-scanpy.readthedocs-hosted.com/en/@version@/api/scanpy.pp.scale.html>`__
885 885
886 Computes the square root the data matrix (`pp.sqrt`) 886 Computes the square root the data matrix (`pp.sqrt`)
887 ==================================================== 887 ====================================================
888 888
889 `X = sqrt(X)` 889 `X = sqrt(X)`