Add generic constraint functions: get_downsamplings (), remove_coverage_outliers (), and filter_for_mu()
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gnomad/utils/filtering.py
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| ``` | ||
| gerp_data = ht.aggregate(gerp=hl.agg.hist(context_ht.gerp, -12.3, 6.17, 100)) | ||
| cumulative_data = np.cumsum(summary_hist.gerp.bin_freq) + summary_hist.gerp.n_smaller | ||
| np.append(cumulative_data, [cumulative_data[-1] + summary_hist.gerp.n_larger]) | ||
| list(zip(summary_hist.gerp.bin_edges, cumulative_data / max(cumulative_data))) | ||
| ``` |
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Does this need to be in a function of some sort?
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moved to constraint repo but still need to look into this more closely
jkgoodrich
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gnomad/utils/constraint.py
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| `freq_meta_expr`. Default is 'adj'. | ||
| """ | ||
| indices = hl.enumerate(freq_meta_expr).filter( | ||
| lambda f: (f[1].size() == 3) |
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actually, this doesn't seem to be needed, anything filtered to 'downsampling' already has a dict size of 3
Co-authored-by: jkgoodrich <33063077+jkgoodrich@users.noreply.github.com>
Co-authored-by: jkgoodrich <33063077+jkgoodrich@users.noreply.github.com>
| `freq_meta_expr`. Default is 'adj'. | ||
| """ | ||
| indices = hl.enumerate(freq_meta_expr).filter( | ||
| lambda f: (f[1].get("group") == variant_quality) |
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Just confirming lambda f: (f[1].size() == 3) is not needed. There is no case where there will be something like: {'downsampling': '5000', 'group': 'adj', 'pop': 'global'} and {'downsampling': '5000', 'group': 'adj', 'pop': 'global', 'other_strata':'some_val} and we only want {'downsampling': '5000', 'group': 'adj', 'pop': 'global'}?
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at least not in the existing datasets, but I could leave it in to be on the safe size
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I think it's fine for now and we can update if our downsampling frequencies get more complex
Co-authored-by: jkgoodrich <33063077+jkgoodrich@users.noreply.github.com>
Co-authored-by: jkgoodrich <33063077+jkgoodrich@users.noreply.github.com>
| `freq_meta_expr`. Default is 'adj'. | ||
| """ | ||
| indices = hl.enumerate(freq_meta_expr).filter( | ||
| lambda f: (f[1].get("group") == variant_quality) |
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I think it's fine for now and we can update if our downsampling frequencies get more complex
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