Diploid Copy Number Estimation

Computes per-sample diploid copy number by normalizing each sample’s read counts relative to its nearest neighbors, accounting for sample-specific sequencing depth.

grid.utils.compute_dipcn.compute_diploid_genotypes(config, console)

Replicate the awk normalization exactly:

norm_reads = reads[sample] / sample_scale

/ mean( reads[neighbor] / neighbor_scale )

where the mean is over the top n_nbr neighbors.

Parameters:

• config – configuration dictionary

• console – Rich console for logging

Return type:

None

grid.utils.compute_dipcn.load_neighbors(neighbors_file)

Parse the gzipped neighbors file.

Each line format:

sample_id sample_scale nbr1_id nbr1_scale nbr1_norm_dist nbr2_id …

norm_dist is present but unused — only neighbor_id and neighbor_scale are needed.

Returns:

{sample_id: [(neighbor_id, neighbor_scale), …]} sample_scales : {sample_id: sample_scale}

Return type:

neighbors

Parameters:

neighbors_file (Path)