Update README.md

README.md

@@ -10,7 +10,7 @@ Missense variants considered "Pathogenic" by human labelers.
 Regulatory variants considered "Pathogenic" by human labelers, curated in [this paper](https://doi.org/10.1016/j.ajhg.2016.07.005).
 
 **gnomAD**:
-A subset of rare (MAC=1) and common (MAF > 1%) variants from different categories (missense, synonymous, ncRNA, intronic, upstream, etc.).
+A subset of rare (MAC=1) and common (MAF > 5%) variants from different categories (missense, synonymous, ncRNA, intronic, upstream, etc.).
 
 ## Usage
 ```python
@@ -19,18 +19,18 @@ from datasets import load_dataset
 dataset = load_dataset("songlab/human_variants", split="test")
 ```
 
-Subset for comparing ClinVar Pathogenic missense vs. gnomAD common (MAF > 5%) missense (can specify `num_proc` to speed up):
+Subset - ClinVar Pathogenic vs. gnomAD common (missense) (can specify `num_proc` to speed up):
 ```python
-dataset = dataset.filter(lambda v: v["source"]=="ClinVar" or (v["source"]=="gnomAD" and "missense" in v["consequence"] and v["MAF"] > 5/100))
+dataset = dataset.filter(lambda v: v["source"]=="ClinVar" or (v["label"]=="Common" and "missense" in v["consequence"]))
 ```
 
-Subset for comparing OMIM Pathogenic regulatory vs. gnomAD common (MAF > 5%) regulatory:
+Subset - OMIM Pathogenic vs. gnomAD common (regulatory):
 ```python
 cs = ["5_prime_UTR", "upstream_gene", "intergenic", "3_prime_UTR", "non_coding_transcript_exon"]
-dataset = dataset.filter(lambda v: v["source"]=="OMIM" or (v["source"]=="gnomAD" and "missense" not in v["consequence"] and any([c in v["consequence"] for c in cs]) and  v["MAF"] > 5/100))
+dataset = dataset.filter(lambda v: v["source"]=="OMIM" or (v["label"]=="Common" and "missense" not in v["consequence"] and any([c in v["consequence"] for c in cs])))
 ```
 
-Subset for comparing gnomAD rare vs. gnomAD common (MAF > 1%):
+Subset - gnomAD rare vs. gnomAD common:
 ```python
 dataset = dataset.filter(lambda v: v["source"]=="gnomAD")
 ```