This function evaluate the presence (calls) of individual mutations from a predefined list.
call_mutations(
mutations_df,
read_positions_df,
model,
beta,
alpha = 0.05,
use_turboem = TRUE,
calculate_confidence_intervals = FALSE,
batch_size = NULL
)A data.frame() with candidate mutations (SNVs) (chromosome, positions, reference and alternative)
A data.frame() with read-positions. See get_read_positions_from_BAM()
A dreams model. See train_dreams_model().
Down sampling parameter from get_training_data() for correcting the error-rates from the DREAMS model.
Alpha-level used for testing and confidence intervals. Default is 0.05.
Logical. Should turboEM::turboem() be used for EM algorithm? Default is TRUE.
Logical. Should confidence intervals be calculated? Default is FALSE.
Number of positions to process at a time
A data.frame() with information about the individual mutation calls, including:
The genomic position of the mutation.
The reference and alternative allele.
If the EM algorithm converged.
Number of steps and function evaluations by the EM algorithm.
The estiamted tumor fraction (allele fraction).
The confidence interval of tf_est.
The expected count of the alternative allele under the error (null) model.
The count of the alternative allele.
The coverage used by the model (only referenceredas with and alternative allele).
The total coverage of the position (for reference).
The observed frequency of the alternative allele.
The value of the log-likelihood function under the null (tf=0) and alternative (tf>0) hypothesis.
The chisq test statistic, degrees of freedom and p-value of the statistical test.
Whether the mutation was detected at the supplied alpha level.