filter_regions {Melissa} | R Documentation |
Fuctions for filter genomic regions due to (1) low CpG coverage, (2) low coverage across cells, or (3) low mean methylation variability.
filter_by_cpg_coverage(obj, min_cpgcov = 10) filter_by_coverage_across_cells(obj, min_cell_cov_prcg = 0.5) filter_by_variability(obj, min_var = 0.1)
obj |
Melissa data object. |
min_cpgcov |
Minimum CpG coverage for each genomic region. |
min_cell_cov_prcg |
Threshold on the proportion of cells that have coverage for each region. |
min_var |
Minimum variability of mean methylation across cells, measured in terms of standard deviation. |
The (1) 'filter_by_cpg_coverage' function does not actually remove the region, it only sets NA to those regions. The (2) 'filter_by_coverage_across_cells' function keeps regions from which we can share information across cells. The (3) 'filter_by_variability' function keeps variable regions which are informative for cell subtype identification.
The filtered Melissa data object
C.A.Kapourani C.A.Kapourani@ed.ac.uk
melissa
, create_melissa_data_obj
# Run on synthetic data from Melissa package filt_obj <- filter_by_cpg_coverage(melissa_encode_dt, min_cpgcov = 20) # Run on synthetic data from Melissa package filt_obj <- filter_by_coverage_across_cells(melissa_encode_dt, min_cell_cov_prcg = 0.7) # Run on synthetic data from Melissa package filt_obj <- filter_by_variability(melissa_encode_dt, min_var = 0.1)