Metadata-Version: 2.1
Name: gtfparse-transcript-transformer
Version: 2.0.2
Summary: GTF Parsing
Home-page: https://github.com/jdcla/gtfparse
Author: Alex Rubinsteyn
License: http://www.apache.org/licenses/LICENSE-2.0.html
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: polars >0.19

Temporary fix for gtfparse to work with polars>0.16, based on https://github.com/y9c/gtfparse

gtfparse
========
Parsing tools for GTF (gene transfer format) files.

# Example usage

## Parsing all rows of a GTF file into a Pandas DataFrame

```python
from gtfparse import read_gtf

# 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("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"]
```


## Getting gene FPKM values from a StringTie GTF file

```python
from gtfparse import read_gtf

df = read_gtf(
    "Transcripts.gtf",
    column_converters={"FPKM": float})

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


