Quality control

Summary

Task ✗✗ ✗✗✗
cell cell communication ligand target 109
cell cell communication source target 109
denoising 84 1 1
dimensionality reduction 553 26 6 1
matching modalities 66
spatial decomposition 77 1 1
task batch integration 701 19 11 15
task label projection 186 3 8 9
task perturbation prediction 160 3
task predict modality 182 5 6 1
task spatially variable genes 102 17 4 1

Detailed

Tip

The tooltip contains some more details on the QC check.

Task Category Name Value Condition Severity
task batch integration Scaling Best score bbknn ilisi 35.0348000 best_score <= 2 ✗✗✗
denoising Scaling Worst score knn_smoothing poisson -10.2983151 worst_score >= -1 ✗✗✗
task label projection Raw results Method ‘geneformer’ %missing 1.0000000 pct_missing <= .1 ✗✗✗
task batch integration Raw results Method ‘scgpt_finetuned’ %missing 1.0000000 pct_missing <= .1 ✗✗✗
task label projection Raw results Method ‘scgpt_finetuned’ %missing 1.0000000 pct_missing <= .1 ✗✗✗
task batch integration Raw results Method ‘scprint’ %missing 1.0000000 pct_missing <= .1 ✗✗✗
task label projection Raw results Method ‘scprint’ %missing 1.0000000 pct_missing <= .1 ✗✗✗
task batch integration Raw results Method ‘batchelor_mnn_correct’ %missing 0.8589744 pct_missing <= .1 ✗✗✗
task batch integration Raw results Method ‘mnnpy’ %missing 0.8589744 pct_missing <= .1 ✗✗✗
task spatially variable genes Raw results Method ‘boostgp’ %missing 0.7800000 pct_missing <= .1 ✗✗✗
task batch integration Raw results Metric ‘hvg_overlap’ %missing 0.7564103 pct_missing <= .1 ✗✗✗
dimensionality reduction Raw results Dataset ‘zebrafish_labs’ %missing 0.6000000 pct_missing <= .1 ✗✗✗
task batch integration Raw results Method ‘bbknn’ %missing 0.5512821 pct_missing <= .1 ✗✗✗
spatial decomposition Scaling Worst score seuratv3 r2 -4.8476947 worst_score >= -1 ✗✗✗
task batch integration Raw results Method ‘geneformer’ %missing 0.4102564 pct_missing <= .1 ✗✗✗
task batch integration Raw results Method ‘scgpt_zeroshot’ %missing 0.4102564 pct_missing <= .1 ✗✗✗
task batch integration Raw results Method ‘scimilarity’ %missing 0.4102564 pct_missing <= .1 ✗✗✗
task batch integration Raw results Metric ‘kbet’ %missing 0.4038462 pct_missing <= .1 ✗✗✗
task batch integration Raw results Dataset ‘cellxgene_census/hypomap’ %missing 0.3786982 pct_missing <= .1 ✗✗✗
task label projection Raw results Dataset ‘cellxgene_census/mouse_pancreas_atlas’ %missing 0.3684211 pct_missing <= .1 ✗✗✗
task batch integration Raw results Metric ‘isolated_label_asw’ %missing 0.3653846 pct_missing <= .1 ✗✗✗
task predict modality Raw results Dataset ‘openproblems_neurips2022/pbmc_multiome/swap’ %missing 0.3611111 pct_missing <= .1 ✗✗✗
task batch integration Raw results Dataset ‘cellxgene_census/mouse_pancreas_atlas’ %missing 0.3579882 pct_missing <= .1 ✗✗✗
task label projection Raw results Method ‘scgpt_zeroshot’ %missing 0.3333333 pct_missing <= .1 ✗✗✗
task label projection Raw results Method ‘scimilarity’ %missing 0.3333333 pct_missing <= .1 ✗✗✗
task label projection Raw results Method ‘scimilarity_knn’ %missing 0.3333333 pct_missing <= .1 ✗✗✗
task label projection Raw results Method ‘singler’ %missing 0.3333333 pct_missing <= .1 ✗✗✗
task batch integration Raw results Metric ‘isolated_label_f1’ %missing 0.3333333 pct_missing <= .1 ✗✗✗
task label projection Raw results Dataset ‘cellxgene_census/hypomap’ %missing 0.3157895 pct_missing <= .1 ✗✗✗
task batch integration Dataset info Pct ‘task_id’ missing 1.0000000 percent_missing(dataset_info, field) ✗✗
task label projection Dataset info Pct ‘task_id’ missing 1.0000000 percent_missing(dataset_info, field) ✗✗
task perturbation prediction Dataset info Pct ‘task_id’ missing 1.0000000 percent_missing(dataset_info, field) ✗✗
task predict modality Dataset info Pct ‘task_id’ missing 1.0000000 percent_missing(dataset_info, field) ✗✗
task spatially variable genes Dataset info Pct ‘task_id’ missing 1.0000000 percent_missing(dataset_info, field) ✗✗
task batch integration Method info Pct ‘paper_reference’ missing 0.7307692 percent_missing(method_info, field) ✗✗
task label projection Method info Pct ‘paper_reference’ missing 0.8421053 percent_missing(method_info, field) ✗✗
task perturbation prediction Method info Pct ‘paper_reference’ missing 0.5000000 percent_missing(method_info, field) ✗✗
task predict modality Method info Pct ‘paper_reference’ missing 0.5555556 percent_missing(method_info, field) ✗✗
task spatially variable genes Method info Pct ‘paper_reference’ missing 0.8750000 percent_missing(method_info, field) ✗✗
task batch integration Metric info Pct ‘paper_reference’ missing 1.0000000 percent_missing(metric_info, field) ✗✗
task label projection Metric info Pct ‘paper_reference’ missing 1.0000000 percent_missing(metric_info, field) ✗✗
task perturbation prediction Metric info Pct ‘paper_reference’ missing 1.0000000 percent_missing(metric_info, field) ✗✗
task predict modality Metric info Pct ‘paper_reference’ missing 1.0000000 percent_missing(metric_info, field) ✗✗
task spatially variable genes Metric info Pct ‘paper_reference’ missing 1.0000000 percent_missing(metric_info, field) ✗✗
task batch integration Raw results Dataset ‘cellxgene_census/dkd’ %missing 0.2810651 pct_missing <= .1 ✗✗
spatial decomposition Scaling Worst score tangram r2 -2.6383322 worst_score >= -1 ✗✗
task spatially variable genes Raw results Dataset ‘zenodo_spatial/merfish/mouse_cortex’ %missing 0.2500000 pct_missing <= .1 ✗✗
task predict modality Raw results Method ‘guanlab_dengkw_pm’ %missing 0.2500000 pct_missing <= .1 ✗✗
task predict modality Raw results Method ‘zeros’ %missing 0.2500000 pct_missing <= .1 ✗✗
dimensionality reduction Raw results Metric ‘continuity’ %missing 0.2500000 pct_missing <= .1 ✗✗
dimensionality reduction Raw results Metric ‘lcmc’ %missing 0.2500000 pct_missing <= .1 ✗✗
dimensionality reduction Raw results Metric ‘qglobal’ %missing 0.2500000 pct_missing <= .1 ✗✗
dimensionality reduction Raw results Metric ‘qlocal’ %missing 0.2500000 pct_missing <= .1 ✗✗
dimensionality reduction Raw results Metric ‘qnn’ %missing 0.2500000 pct_missing <= .1 ✗✗
dimensionality reduction Raw results Metric ‘qnn_auc’ %missing 0.2500000 pct_missing <= .1 ✗✗
task predict modality Scaling Worst score lmds_irlba_rf overall_pearson -2.4102000 worst_score >= -1 ✗✗
denoising Scaling Worst score alra_sqrt poisson -2.3012026 worst_score >= -1 ✗✗
task label projection Raw results Metric ‘accuracy’ %missing 0.2280702 pct_missing <= .1 ✗✗
task label projection Raw results Metric ‘f1_macro’ %missing 0.2280702 pct_missing <= .1 ✗✗
task label projection Raw results Metric ‘f1_micro’ %missing 0.2280702 pct_missing <= .1 ✗✗
task label projection Raw results Metric ‘f1_weighted’ %missing 0.2280702 pct_missing <= .1 ✗✗
task batch integration Raw results Metric ‘asw_label’ %missing 0.2243590 pct_missing <= .1 ✗✗
task batch integration Raw results Dataset ‘cellxgene_census/tabula_sapiens’ %missing 0.2218935 pct_missing <= .1 ✗✗
task batch integration Raw results Dataset ‘cellxgene_census/gtex_v9’ %missing 0.2189349 pct_missing <= .1 ✗✗
task batch integration Raw results Dataset ‘cellxgene_census/immune_cell_atlas’ %missing 0.2189349 pct_missing <= .1 ✗✗
task batch integration Raw results Metric ‘asw_batch’ %missing 0.2179487 pct_missing <= .1 ✗✗
task batch integration Raw results Metric ‘cell_cycle_conservation’ %missing 0.2179487 pct_missing <= .1 ✗✗
task batch integration Raw results Metric ‘pcr’ %missing 0.2179487 pct_missing <= .1 ✗✗
task label projection Raw results Dataset ‘cellxgene_census/immune_cell_atlas’ %missing 0.2105263 pct_missing <= .1 ✗✗
task spatially variable genes Raw results Dataset ‘zenodo_spatial/seqfish/mouse_organogenesis_seqfish’ %missing 0.1875000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/slideseqv2/mouse_cortex’ %missing 0.1875000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/stereoseq/drosophila_embryo_e6_3’ %missing 0.1875000 pct_missing <= .1
task batch integration Raw results Metric ‘ari’ %missing 0.1794872 pct_missing <= .1
task batch integration Raw results Metric ‘clisi’ %missing 0.1794872 pct_missing <= .1
task batch integration Raw results Metric ‘graph_connectivity’ %missing 0.1794872 pct_missing <= .1
task batch integration Raw results Metric ‘ilisi’ %missing 0.1794872 pct_missing <= .1
task batch integration Raw results Metric ‘nmi’ %missing 0.1794872 pct_missing <= .1
task predict modality Raw results Metric ‘overall_pearson’ %missing 0.1666667 pct_missing <= .1
task predict modality Raw results Metric ‘overall_spearman’ %missing 0.1666667 pct_missing <= .1
task spatially variable genes Raw results Method ‘spark’ %missing 0.1600000 pct_missing <= .1
task label projection Raw results Dataset ‘cellxgene_census/dkd’ %missing 0.1578947 pct_missing <= .1
task label projection Raw results Dataset ‘cellxgene_census/gtex_v9’ %missing 0.1578947 pct_missing <= .1
task label projection Raw results Dataset ‘cellxgene_census/tabula_sapiens’ %missing 0.1578947 pct_missing <= .1
task batch integration Scaling Worst score scanorama hvg_overlap -1.5279000 worst_score >= -1
dimensionality reduction Raw results Method ‘densmap_logCP10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘densmap_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘densmap_pca_logCP10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘densmap_pca_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘diffusion_map’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘neuralee_default’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘neuralee_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘pca_logCP10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘pca_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘phate_default’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘phate_logCP10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘phate_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘phate_sqrt’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘pymde_distances_log_cp10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘pymde_distances_log_cp10k_hvg’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘pymde_neighbors_log_cp10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘pymde_neighbors_log_cp10k_hvg’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘random_features’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘spectral_features’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘true_features’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘tsne_logCP10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘tsne_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘umap_logCP10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘umap_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘umap_pca_logCP10k’ %missing 0.1500000 pct_missing <= .1
dimensionality reduction Raw results Method ‘umap_pca_logCP10k_1kHVG’ %missing 0.1500000 pct_missing <= .1
task batch integration Raw results Method ‘uce’ %missing 0.1410256 pct_missing <= .1
task predict modality Raw results Dataset ‘openproblems_neurips2022/pbmc_multiome/normal’ %missing 0.1388889 pct_missing <= .1
task batch integration Raw results Method ‘batchelor_fastmnn’ %missing 0.1282051 pct_missing <= .1
task batch integration Raw results Method ‘harmony’ %missing 0.1282051 pct_missing <= .1
task batch integration Raw results Method ‘harmonypy’ %missing 0.1282051 pct_missing <= .1
task batch integration Raw results Method ‘liger’ %missing 0.1282051 pct_missing <= .1
task batch integration Raw results Method ‘pyliger’ %missing 0.1282051 pct_missing <= .1
task batch integration Raw results Method ‘scanvi’ %missing 0.1282051 pct_missing <= .1
task batch integration Raw results Method ‘scvi’ %missing 0.1282051 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘tenx_visium/visium/human_brain_cancer’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘tenx_visium/visium/human_normal_prostate’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/slideseqv2/mouse_cerebellum’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/slideseqv2/mouse_hippocampus_puck’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/slideseqv2/mouse_olfactory_bulb_puck’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/slideseqv2/mouse_somatosensory_cortex_puck’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/starmap/mouse_brain_2d_zstep10_0’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/starmap/mouse_brain_2d_zstep15_0’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/stereoseq/drosophila_embryo_e10’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/stereoseq/drosophila_embryo_e5_6’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/stereoseq/drosophila_embryo_e7’ %missing 0.1250000 pct_missing <= .1
task spatially variable genes Raw results Dataset ‘zenodo_spatial/stereoseq/drosophila_embryo_e9_1’ %missing 0.1250000 pct_missing <= .1
task predict modality Raw results Method ‘knnr_py’ %missing 0.1250000 pct_missing <= .1
task predict modality Raw results Method ‘lm’ %missing 0.1250000 pct_missing <= .1
task batch integration Scaling Worst score scalex hvg_overlap -1.2449000 worst_score >= -1
task spatially variable genes Raw results Method ‘somde’ %missing 0.1200000 pct_missing <= .1
task batch integration Raw results Method ‘embed_cell_types’ %missing 0.1153846 pct_missing <= .1
task batch integration Raw results Method ‘embed_cell_types_jittered’ %missing 0.1153846 pct_missing <= .1
task batch integration Raw results Method ‘no_integration’ %missing 0.1153846 pct_missing <= .1
task batch integration Raw results Method ‘no_integration_batch’ %missing 0.1153846 pct_missing <= .1