snipar.correlate module

snipar.correlate.compute_corr(z1, z2, v1, v2, r, l)

snipar.correlate.estimate_cov(z1, z2, v1, v2, r, w)

snipar.correlate.estimate_cov_weights(v1, v2, r, var_1, var_2, c, l)

snipar.correlate.estimate_var(z, v, w)

snipar.correlate.estimate_weights(v_est, v, l)

snipar.correlate.jacknife(z1, z2, v1, v2, r, l, n_blocks, block_size)

snipar.correlate.jacknife_est(z1, z2, v1, v2, r, l, n_blocks)

snipar.correlate.read_sumstats_file(sumstats_file, chrom)

snipar.correlate.read_sumstats_files(sumstats_files, chroms)

snipar.correlate.reweighted_estimate_cov(z1, z2, v1, v2, r, l, var_1, var_2, tol=1e-08, max_iter=1000)

snipar.correlate.reweighted_estimate_var(z, v, l, tol=1e-08, max_iter=1000)

class snipar.correlate.sumstats(chrom, sid, pos, A1, A2, freqs, direct, direct_SE, avg_NTC, avg_NTC_SE, population, population_SE, r_direct_avg_NTC, r_direct_pop, ldscores=None, map=None)

Bases: object

compute_ld_scores(bedfiles, chroms, ld_wind, ld_out=None)

concatenate(s2)

cor_direct_avg_NTC(n_blocks)

cor_direct_pop(n_blocks)

filter(filter_pass)

filter_NAs()

filter_corrs(max_Z)

filter_maf(min_maf)

scores_from_ldsc(ld_files)