Public Interface

Utils

geno_sugar.utils.is_in(bim, geno_range)
Parameters:
  • bim (pandas.DataFrame) – Variant annotation
  • geno_range (tuple) – (chrom, pos_start, pos_end)
Returns:

Isnp – Variant filter
Return type:

bool array
geno_sugar.utils.snp_query(G, bim, Isnp)
Parameters:
  • G ((n_snps, n_inds) array) – Genetic data
  • bim (pandas.DataFrame) – Variant annotation
  • Isnp (bool array) – Variant filter
Returns:

  • G_out ((n_snps, n_inds) array) – filtered genetic data
  • bim_out (dataframe) – filtered variant annotation
geno_sugar.utils.standardize_snps(G)

Standardize variantes.

Parameters:G ((n_inds, n_snps) array) – Genetic data
Returns:G_out
Return type:standardized array
geno_sugar.utils.unique_variants(G)

Filters out variants with the same genetic profile.

Parameters:G ((n_inds, n_snps) array) – Genetic data
Returns:
  • G_out ((n_inds, n_unique_snps) array) – filtered genetic data
  • idxs (int array) – indexes of the the unique variants

Geno Queue

Iterator class facilitating genome-wide analyses by (i) loading the genetic data in batches of snps, and (ii) applying user-specified functions for preprocessing and filtering.

class geno_sugar.geno_queue.GenoQueue(G, bim, batch_size=1000, preprocess=None, verbose=True)

Util class for genome wide analysis

Parameters:
  • G ((snps, inds) array) – Genetic data
  • bim (pandas.DataFrame) – Variant annotation
  • batch_size (int) – number of snps in the batch
  • preprocess (function) – preprocess function
  • verbose (bool) – verbose flag (default True)

Preprocess

Preprocess functions return functions that take as only argument the array-like genetic matrix

geno_sugar.preprocess.compose(func_list)

composion of preprocessing functions

geno_sugar.preprocess.filter_by_maf(min_maf=0.01)

return function that filters by maf (takes minimum maf, default is 0.01)

geno_sugar.preprocess.filter_by_missing(max_miss=0.01)

return function that filters by missing values (takes maximum fraction of missing values, default is 0.01)

geno_sugar.preprocess.impute(imputer)

return impute function

geno_sugar.preprocess.standardize()

return variant standarize function