Infer trajectory motifs using a pre-trained trajectory model
infer_trajectory_motifs.RdThis function infers the motif energies for a set of peaks using a pre-trained trajectory model.
Usage
infer_trajectory_motifs(
traj_model,
peak_intervals,
atac_scores = NULL,
bin_start = 1,
bin_end = ncol(atac_scores),
additional_features = NULL,
test_energies = NULL,
diff_score = NULL,
sequences = NULL,
norm_sequences = NULL
)Arguments
- traj_model
A trajectory model object, as returned by
regress_trajectory_motifs- peak_intervals
A data frame, indicating the genomic positions ('chrom', 'start', 'end') of each peak.
- atac_scores
Optional. A numeric matrix, representing mean ATAC score per bin per peak. Rows: peaks, columns: bins. By default iceqream would regress the last column minus the first column. If you want to regress something else, please either change bin_start or bin_end, or provide
atac_diffinstead. Ifnormalize_binsis TRUE, the scores will be normalized to be between 0 and 1.- bin_start
the start of the trajectory. Default: 1
- bin_end
the end of the trajectory. Default: the last bin (only used when atac_scores is provided)
- additional_features
A data frame, representing additional genomic features (e.g. CpG content, distance to TSS, etc.) for each peak. Note that NA values would be replaced with 0.
- test_energies
An already computed matrix of motif energies for the test peaks. An advanced option to provide the energies directly.
- diff_score
The difference in ATAC-seq scores between the end and start of the peak. If provided, the function will ignore the atac_scores parameter.
- sequences
A vector of strings containing the sequences of the peaks. If not provided, the sequences will be extracted from the genome using the peak intervals.
- norm_sequences
A vector of strings containing the sequences of the normalization intervals. If not provided, the sequences will be extracted from the genome using the normalization intervals.