ncbi_gene.pubmed_links

Python

In [1]:

import bedrock_bio as bb

rel = bb.load_table('ncbi_gene.pubmed_links')

df = rel.limit(5).pl()  # Polars
df = rel.limit(5).df()  # Pandas
df.head()

Out[1]:

	sources	taxon_id	gene_id	pubmed_id
0	[{'url': 'https://ftp.ncbi.nlm.nih.gov/gene/DA...	23	313740179	8041738
1	[{'url': 'https://ftp.ncbi.nlm.nih.gov/gene/DA...	23	313740182	20382024
2	[{'url': 'https://ftp.ncbi.nlm.nih.gov/gene/DA...	23	313740182	21958041
3	[{'url': 'https://ftp.ncbi.nlm.nih.gov/gene/DA...	23	313740182	33958791
4	[{'url': 'https://ftp.ncbi.nlm.nih.gov/gene/DA...	23	313740183	8752349

R

In [1]:

library(bedrockbio)

lf <- load_table("ncbi_gene.pubmed_links")
df <- head(lf, 5) |> collect()

head(df)

Out[1]:

Sample output (5 rows, showing 3 of 4 columns)
   taxon_id | gene_id   | pubmed_id
   -------- | --------- | ---------
0  23       | 313740179 | 8041738
1  23       | 313740182 | 20382024
2  23       | 313740182 | 21958041
3  23       | 313740182 | 33958791
4  23       | 313740183 | 8752349

Description

NCBI Gene-to-PubMed links, one row per taxonomy, GeneID, and PubMed identifier combination.

Partitions

Not partitioned.

Schema

Column	Type	Description
sources	STRUCT(url TEXT, filename TEXT, last_modified_at TIMESTAMPTZ, sha256 TEXT)[]	Provenance for the NCBI Gene PubMed mapping file.
taxon_id	TEXT	NCBI taxonomy identifier for the gene’s species or strain.
gene_id	TEXT	NCBI Gene identifier.
pubmed_id	TEXT	PubMed citation identifier.