LD data from CEU hg18, based on ftp://ftp.ncbi.nlm.nih.gov/hapmap/ld_data/latest Algo for computing: import pandas as pd rule ld_blocks: input: expand("blocks/{chromosome}_blocks.gz", chromosome=["chr{}".format(c) for c in list(range(1, 23)) + ["X"]]) rule get_blocks: output: "blocks/{chromosome}_blocks.gz" run: c = wildcards.chromosome f = r"ftp://ftp.ncbi.nlm.nih.gov/hapmap/ld_data/latest/ld_{}_CEU.txt.gz".format(c) print(f) df = pd.read_csv(f, sep=" ", header=None, usecols=[0, 1, 8]) print(df.head()) df.columns = "Start End Block".split() ls = df.groupby("Block").agg({"Start": "first", "End": "last", "Block": ["first", "count"]}).reset_index(drop=True) ls.columns = "Start End LDBlock Count".split() lengths = ls["End"] - ls["Start"] ls.insert(ls.shape[1], "Length", lengths) ls.insert(0, "Chromosome", c) ls.to_csv(output[0], sep="\t", index=None)