使用infercnvpy的genomic_position_from_gtf时遇Polars属性错误求解决

使用infercnvpy从单细胞转录组数据推断CNV时，调用cnv.io.genomic_position_from_gtf()注释基因组位置时触发以下错误：

AttributeError                            Traceback (most recent call last)
Cell In[28], line 2
1 gtf_file=r'G:\gencode.v38.annotation.gtf'
2 cnv.io.genomic_position_from_gtf(gtf_file, adata=adata, gtf_gene_id='gene_name', inplace=True)

File ~\Anaconda3\envs\spapros\lib\site-packages\infercnvpy\io_genepos.py:41, in genomic_position_from_gtf(gtf_file, adata, gtf_gene_id, adata_gene_id, inplace)
11 def genomic_position_from_gtf(
12     gtf_file: Union[Path, str],
13     adata: Union[AnnData, None] = None,
(...)
17     inplace: bool = True,
18 ) -> Union[pd.DataFrame, None]:
19     """Get genomic gene positions from a GTF file.
20
21     The GTF file needs to match the genome annotation used for your single cell dataset.
(...)
39         If True, add the annotations directly to adata, otherwise return a dataframe.
40     """
41     gtf = gtfparse.read_gtf(
42         gtf_file, usecols=["seqname", "feature", "start", "end", "gene_id", "gene_name"], result_type="pandas"
43     )
44     gtf = (
45         gtf.loc[
46             gtf["feature"] == "gene",
(...)
50         .rename(columns={"seqname": "chromosome"})
51     )
53     gene_ids_adata = (adata.var_names if adata_gene_id is None else adata.var[adata_gene_id]).values

File ~\Anaconda3\envs\spapros\lib\site-packages\gtfparse\read_gtf.py:254, in read_gtf(filepath_or_buffer, expand_attribute_column, infer_biotype_column, column_converters, usecols, features, result_type)
251     raise ValueError("GTF file does not exist: %s" % filepath_or_buffer)
253 if expand_attribute_column:
254     result_df = parse_gtf_and_expand_attributes(
255         filepath_or_buffer,
256         restrict_attribute_columns=usecols,
257         features=features)
258 else:
259     result_df = parse_gtf(result_df, features=features)

File ~\Anaconda3\envs\spapros\lib\site-packages\gtfparse\read_gtf.py:189, in parse_gtf_and_expand_attributes(filepath_or_buffer, restrict_attribute_columns, features)
166 def parse_gtf_and_expand_attributes(
167         filepath_or_buffer,
168         restrict_attribute_columns=None,
169         features=None):
170     """
171     Parse lines into column->values dictionary and then expand
172     the 'attribute' column into multiple columns. This expansion happens
(...)
187         Ignore entries which don't correspond to one of the supplied features
188     """
189     df = parse_gtf(
190         filepath_or_buffer=filepath_or_buffer,
191         features=features,
192         split_attributes=True)
193     if type(restrict_attribute_columns) is str:
194         restrict_attribute_columns = {restrict_attribute_columns}

File ~\Anaconda3\envs\spapros\lib\site-packages\gtfparse\read_gtf.py:155, in parse_gtf(filepath_or_buffer, split_attributes, features, fix_quotes_columns)
150 def parse_gtf(
151         filepath_or_buffer,
152         split_attributes=True,
153         features=None,
154         fix_quotes_columns=["attribute"]):
155     df_lazy = parse_with_polars_lazy(
156         filepath_or_buffer=filepath_or_buffer,
157         split_attributes=split_attributes,
158         features=features,
159         fix_quotes_columns=fix_quotes_columns)
160     return df_lazy.collect()

File ~\Anaconda3\envs\spapros\lib\site-packages\gtfparse\read_gtf.py:87, in parse_with_polars_lazy(filepath_or_buffer, split_attributes, features, fix_quotes_columns)
80 def parse_with_polars_lazy(
81         filepath_or_buffer,
82         split_attributes=True,
(...)
85     # use a global string cache so that all strings get intern'd into
86     # a single numbering system
87     polars.toggle_string_cache(True)
88     kwargs = dict(
89         has_header=False,
90         sep="	",
(...)
103             "frame": polars.UInt32,
104         })
105     try:

AttributeError: module 'polars' has no attribute 'toggle_string_cache'

运行代码如下（使用GENCODE v44注释文件）：

import infercnvpy as cnv
import scanpy as sc
import matplotlib.pyplot as plt
import pandas as pd

adata=sc.read(r'G:\data.h5ad')
sc.pp.log1p(adata)

gtf_file=r'G:\gencode.v44.annotation.gtf'
cnv.io.genomic_position_from_gtf(gtf_file, adata=adata, gtf_gene_id='gene_name', inplace=True)

目标是得到adata.var中包含ensg、chromosome、start、end字段的注释结果，示例输出：

ensg               chromosome      start        end
symbol              
AL645933.5  ENSG00000288587.1   chr6    31400702    31463705
AC010184.1  ENSG00000288585.1   chr3    141449745   141456434
AC023296.1  ENSG00000288580.1   chr8    2923568     2926689
AL117334.2  ENSG00000288577.1   chr20   3406380     3410036
AC107294.4  ENSG00000288576.1   chr3    184778723   184780720

这个错误源于polars版本不兼容：polars.toggle_string_cache()在polars 0.19.0及以后版本被移除，替换为polars.enable_string_cache()，但当前使用的gtfparse版本依赖旧的polars API。可通过以下方式解决：

方法1：降级polars到兼容版本 #

在conda环境中执行：

conda install polars=0.18.10 -c conda-forge

或使用pip：

pip install polars==0.18.10

方法2：升级gtfparse到适配新版polars的版本 #

若不想降级polars，直接更新gtfparse到修复该问题的版本：

pip install --upgrade gtfparse

注：需确保gtfparse最新版本已适配polars 0.19+的API。

方法3：手动解析GTF文件（备选方案） #

如果上述方法无效，可手动用pandas解析GTF文件后添加到adata.var中：

import pandas as pd

# 解析GTF，仅保留gene特征
gtf_df = pd.read_csv(
    gtf_file,
    sep="\t",
    comment="#",
    header=None,
    names=["chromosome", "source", "feature", "start", "end", "score", "strand", "frame", "attributes"]
)
gtf_df = gtf_df[gtf_df["feature"] == "gene"]

# 从attributes字段提取gene_name和gene_id
def extract_attr(attr_str, key):
    for item in attr_str.split(";"):
        item = item.strip()
        if item.startswith(key):
            return item.split(" ")[1].strip('"')
    return None

gtf_df["gene_name"] = gtf_df["attributes"].apply(lambda x: extract_attr(x, "gene_name"))
gtf_df["ensg"] = gtf_df["attributes"].apply(lambda x: extract_attr(x, "gene_id"))

# 筛选所需列并与adata的基因匹配
gtf_df = gtf_df[["gene_name", "chromosome", "start", "end", "ensg"]].set_index("gene_name")
# 假设adata.var_names为gene_name，合并注释到adata.var
adata.var = adata.var.join(gtf_df, how="left")

内容的提问来源于stack exchange，提问作者Starts13