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import pandas as pd | |
file = "input.bed" | |
df = pd.read_csv(file, sep="\t", names=["chr", "start", "end", "interval", "score", "strand"]) | |
df[["gene", "extra"]] = df["interval"].str.split("_", 1, expand=True) | |
df.drop(["interval", "score", "strand", "extra"], axis=1, inplace=True) | |
new_df = df.groupby("gene").agg({"chr":"unique", "start":min, "end":max}) | |
new_df.reset_index(inplace=True) | |
new_df["chr"] = new_df["chr"].apply(lambda chr: chr[0]) | |
new_df["start"] = new_df["start"].astype("str") |
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- [2019 Using long-read sequencing to detect imprinted DNA
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