Differential Accessibility for Single Cell

Differential Accessibility for Single Cell performs differential analysis from an input Peak Count Matrix (Image peak_count_matrix_16_n_p) and groupings provided by Cell Clusters (Image cell_clusters_16_n_p) or Cell Annotations (Image cell_annotations_16_n_p).

It is often most natural to run the tool from a Dimensionality Reduction Plot by right-clicking on the plot, see UMAP and tSNE plot functionality for details. However, it can also be found in the Toolbox here:

        Toolbox | Single Cell Analysis (Image sc_folder_closed_16_n_p) | Chromatin Accessibility (Image sc_atac_seq_folder_open_16_n_p) | Differential Accessibility for Single Cell (Image diff_accessibility_16_n_p)

The tool performs tests for differentially accessible peaks, nearby genes or transcription factors, as specified in the `Data type' options group. The tests are summarized in the output Statistical Comparison Tables (Image sc_stat_comp_16_n_p), see The output of Differential Expression for Single Cell for details.

The remaining options specify the type of test to be performed and how features can be filtered before testing, in a similar manner as done for Differential Expression for Single Cell, see Differential Expression for Single Cell for details.

Note that features that are present in few cells can lead to bands in the volcano plot, showing the relationship between the p-values and the log2 fold changes, see https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Volcano_plots.html for details. Such features can span a wide range of fold changes but often have high p-values. To remove these bands, the features that are not present in sufficient cells can be filtered before testing, as detailed above.



Subsections