Adapt hl.de_novo function
#760
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| def transform_pl_to_pp(pl_expr: hl.expr.ArrayExpression) -> hl.expr.ArrayExpression: |
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naive question, is the pp here posterior probability?
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It's the conditional probabilities of each geneotype given the data calculated by HaplotypeCaller, we're transforming it back.
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| .when((p_de_novo > med_conf_p) & (proband_ab > high_med_conf_ab), "MEDIUM") | ||
| .when((p_de_novo > low_conf_p) & (proband_ab >= low_conf_ab), "LOW") |
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I didn't dig into Kaitlin's code, but her documentation uses > and not >= for AB
p_dn > 0.05 and child_AD > 0.2
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yeah I knew that, but <0.2 is failing, what. happens with AD = 0.2?
| de_novo_prior=de_novo_prior, | ||
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| # Determine genomic context |
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rather than running this in this function and in calculate_de_novo_post_prob, why not switch the order and run get_genomic_context first and pass in the three return values to calculate_de_novo_post_prob as function arguments?
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| parent_sum_ad_0 = ( |
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these aren't sums; should this be renamed parent_ad_0, parent_ad_0_check, or something else that's similar?
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great catch, it should be hl.sum()
| "min_dp_ratio": dp_ratio < min_dp_ratio, | ||
| "parent_sum_ad_0": parent_sum_ad_0, | ||
| "max_parent_ab": fail_max_parent_ab, | ||
| "min_proband_ab": proband_ab < min_proband_ab, |
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should this be <= instead of <?
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Okay, I will change it here.
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| is_de_novo = ( |
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the current setup means you're calculating this probability on all variants, right? could you filter to variants that are eligible for being de novos first and then calculate probabilities? or is there a reason you don't want to do this filter upfront?
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I also forgot to ask in my initial review -- could you add tests for the new functions? |
Co-authored-by: Katherine Chao <[email protected]>
These are smaller functions modified from Julia's work on combining hl.de_novo and Kaitlin’s code.