This function performs variant calling on indels from a given BAM file using a predefined list of mutations. It processes the mutations data, batch processes the genomic positions, and calls mutations using a specific model.
dreams_vc_indels(
mutations_df,
bam_file_path,
reference_path,
model,
model_indels,
alpha = 0.05,
use_turboem = TRUE,
calculate_confidence_intervals = FALSE,
batch_size = NULL
)A dataframe containing the list of mutations to be analyzed.
Path to the BAM file containing sequencing data.
Path to the reference genome file, typically in FASTA format.
The model to be used for calling mutations for SNVs.
The model to be used for calling mutations for indels.
Significance level for statistical testing, default is 0.05.
Logical flag indicating whether to use the turboEM algorithm, default is TRUE.
Logical flag indicating whether to calculate confidence intervals, default is FALSE.
Number of positions to process in each batch; if NULL, it's determined based on the data.
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.