openvax / openvax/gtfparse

gtfparse.parsing_error.ParsingError: Integer column has NA values in column 3

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Description

Hi,
I used the following GTF file from Scallop:

chr01_pilon_pilon       scallop transcript      168145  169166  1000    .       .       gene_id "gene.1.0"; transcript_id "gene.1.0.0"; RPKM "9.8016"; cov "27.2554";
chr01_pilon_pilon       scallop exon    168145  169166  1000    .       .       gene_id "gene.1.0"; transcript_id "gene.1.0.0"; exon "1";
chr01_pilon_pilon       scallop transcript      410672  444190  1000    +       .       gene_id "gene.3.0"; transcript_id "gene.3.0.1"; RPKM "0.5936"; cov "1.6506";
chr01_pilon_pilon       scallop exon    410672  411205  1000    +       .       gene_id "gene.3.0"; transcript_id "gene.3.0.1"; exon "1";
chr01_pilon_pilon       scallop exon    411326  411482  1000    +       .       gene_id "gene.3.0"; transcript_id "gene.3.0.1"; exon "2";
chr01_pilon_pilon       scallop exon    444085  444190  1000    +       .       gene_id "gene.3.0"; transcript_id "gene.3.0.1"; exon "3";
chr01_pilon_pilon       scallop transcript      678431  681781  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.1"; RPKM "0.4733"; cov "1.3162";
chr01_pilon_pilon       scallop exon    678431  678822  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.1"; exon "1";
chr01_pilon_pilon       scallop exon    678917  679068  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.1"; exon "2";
chr01_pilon_pilon       scallop exon    680616  681781  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.1"; exon "3";
chr01_pilon_pilon       scallop transcript      678431  685851  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; RPKM "7.9200"; cov "22.0230";
chr01_pilon_pilon       scallop exon    678431  678822  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "1";
chr01_pilon_pilon       scallop exon    678917  679068  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "2";
chr01_pilon_pilon       scallop exon    680616  681627  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "3";
chr01_pilon_pilon       scallop exon    681874  681965  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "4";
chr01_pilon_pilon       scallop exon    683200  683274  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "5";
chr01_pilon_pilon       scallop exon    683744  683805  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "6";
chr01_pilon_pilon       scallop exon    684640  684709  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "7";
chr01_pilon_pilon       scallop exon    684842  685851  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.2"; exon "8";
chr01_pilon_pilon       scallop transcript      681834  685851  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.3"; RPKM "1.1177"; cov "3.1080";
chr01_pilon_pilon       scallop exon    681834  681965  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.3"; exon "1";
chr01_pilon_pilon       scallop exon    683200  683274  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.3"; exon "2";
chr01_pilon_pilon       scallop exon    683744  683805  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.3"; exon "3";
chr01_pilon_pilon       scallop exon    684640  684709  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.3"; exon "4";
chr01_pilon_pilon       scallop exon    684842  685851  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.3"; exon "5";
chr01_pilon_pilon       scallop transcript      683032  685851  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.0"; RPKM "0.6001"; cov "1.6686";
chr01_pilon_pilon       scallop exon    683032  683274  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.0"; exon "1";
chr01_pilon_pilon       scallop exon    683744  683805  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.0"; exon "2";
chr01_pilon_pilon       scallop exon    684640  684709  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.0"; exon "3";
chr01_pilon_pilon       scallop exon    684842  685851  1000    +       .       gene_id "gene.6.0"; transcript_id "gene.6.0.0"; exon "4";

However, the belowe code caused the following errors:

Traceback (most recent call last):
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/gtfparse/read_gtf.py", line 103, in parse_gtf
    for df in chunk_iterator:
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/pandas/io/parsers.py", line 1128, in __next__
    return self.get_chunk()
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/pandas/io/parsers.py", line 1188, in get_chunk
    return self.read(nrows=size)
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/pandas/io/parsers.py", line 1154, in read
    ret = self._engine.read(nrows)
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/pandas/io/parsers.py", line 2059, in read
    data = self._reader.read(nrows)
  File "pandas/_libs/parsers.pyx", line 881, in pandas._libs.parsers.TextReader.read
  File "pandas/_libs/parsers.pyx", line 908, in pandas._libs.parsers.TextReader._read_low_memory
  File "pandas/_libs/parsers.pyx", line 973, in pandas._libs.parsers.TextReader._read_rows
  File "pandas/_libs/parsers.pyx", line 1105, in pandas._libs.parsers.TextReader._convert_column_data
  File "pandas/_libs/parsers.pyx", line 1136, in pandas._libs.parsers.TextReader._convert_tokens
  File "pandas/_libs/parsers.pyx", line 1232, in pandas._libs.parsers.TextReader._convert_with_dtype
ValueError: Integer column has NA values in column 3

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/lorencm/projects/bioinf-scripts/reduceIsoforms.py", line 24, in <module>
    df = read_gtf("data/hybrid.gtf")
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/gtfparse/read_gtf.py", line 211, in read_gtf
    restrict_attribute_columns=usecols)
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/gtfparse/read_gtf.py", line 154, in parse_gtf_and_expand_attributes
    features=features)
  File "/anaconda/envs/bioinf-scripts/lib/python3.7/site-packages/gtfparse/read_gtf.py", line 122, in parse_gtf
    raise ParsingError(str(e))
gtfparse.parsing_error.ParsingError: Integer column has NA values in column 3

This is the code:

df = read_gtf("data/hybrid.gtf")
df_genes = df[df["feature"] == "gene"]
print(df_genes)

What did I miss?

Thank you in advance,

Michal

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Research direction

Reproduce read_gtf("data/hybrid.gtf") from reduceIsoforms.py and inspect the parsing path in gtfparse/read_gtf.py, especially the reported integer conversion for column 3. Compare the input rows with the parser's expected columns; done means the example file parses successfully and the requested gene rows can be printed.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

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