View source: R/gset_feat_select.r
mcell_gset_filter_multi | R Documentation |
Select/filter gene features from using multiple statistics from the gstat table. All genes passing the selected thresholds are included
mcell_gset_filter_multi(
gstat_id,
gset_id,
T_tot,
T_top3,
T_szcor = NULL,
T_vm = NULL,
T_niche = NULL,
force_new = F,
blacklist = c()
)
gstat_id |
the ID of the gstat object to use |
gset_id |
if this exists, the function will restrict the current genes in the set with genes matching the selected thresholds, if not, it will generate a new gene sets object with one set including all selected genes |
T_tot |
total down sampled coverage thresholds (genes with tot UMIs < T_tot are filtered out) |
T_top3 |
threshold value for the third highest umi count for the gene (genes with top3<T_top3 are filtered out) |
T_szcor |
threshold value for the normalized size correlation statistic (only genes with sz_cor < T_szcor are selected). If you use this, consider values around -0.1 - but evaluate carefully your decision using the gstat empirical data |
T_vm |
the threshold value for the normalized var/mean (only genes with varmean > T_vm are selected) Recommended values are usually around 0.2, but this may vary with the data. Not recommended for datasets with hihgly heterogeneous cell sizes (e.g. in whole-organisms datasets) |
T_niche |
threshold value for the normalized niche score statistic (only genes with niche_norm > T_niche are selected). Recommended to use in combination with szcor to add genes with strongly restricted expression patterns. Consider using values around 0.05 |
force_new |
will overwrite existing gene set object (gset_id) in the database if it exists |
blacklist |
option list of gene IDs to be excluded |
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