from gtfparse import read_gtf_as_dataframe

# returns GTF with essential columns such as "feature", "seqname", "start", "end"
# alongside the names of any optional keys which appeared in the attribute column
df = read_gtf_as_dataframe("gene_annotations.gtf")

# filter DataFrame to gene entries on chrY
df_genes = df[df["feature"] == "gene"]
df_genes_chrY = df_genes[df_genes["seqname"] == "Y"]

from gtfparse import read_gtf_as_dict

gtf_dict = read_gtf_as_dict(
    "stringtie-output.gtf",
    column_converters={"FPKM": float})

gene_fpkms = {
    gene_name: fpkm
    for (gene_name, fpkm, feature)
    in zip(gtf_dict["gene_name"], gtf_dict["FPKM"], gtf_dict["feature"])
    if feature == "gene"
}