Genomic Coordinate Conventions — BED versus GFF3 Side by Side (.csv)
Every interval written in both coordinate conventions with its length, which is identical either way. It is the lookup table for the most common bioinformatics off-by-one, and the length column is what proves a conversion did not quietly change an interval's size.
name,bed_start_0_based,bed_end_half_open,gff_start_1_based,gff_end_inclusive,length,strand
gene0001,100,460,101,460,360,+
exon0001,100,220,101,220,120,+
exon0002,300,460,301,460,160,+
cds0001,120,220,121,220,100,+
cds0002,300,420,301,420,120,+
gene0002,500,580,501,580,80,-
Specifications
- Rows
- 6
- Columns
- 7
- Conventions
- 0-based half-open and 1-based inclusive
- Length Invariant
- true
- Conversion Rule
- gffStart = bedStart + 1; gffEnd = bedEnd
Testing contract
Reference control- Scenario
- Convert each interval from one convention to the other in your own code and compare all four coordinate columns.
- Expected result
- Your conversions match every row and the length column stays constant under both conventions, so an off-by-one shows up as a changed length rather than a shifted-but-plausible interval.
What is a .csv file?
CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.
How to use this file
Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.
How to use this file for testing
“Genomic Coordinate Conventions — BED versus GFF3 Side by Side (.csv)” is a deterministic Novus Examples fixture for Scientific data, Editor testing, Conversion testing. Citation catalogs (BibTeX, RIS), chemistry structures (MDL Molfile, PDB), and gridded binary data (NetCDF, FITS) — for testing reference managers, molecule viewers, and scientific-data loaders.
Documented properties for this file: 6 rows · 7 columns. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such — expect parsers to fail loudly rather than silently accept them.
Scientific fixtures are small, valid, and fully synthetic — no real organism, patient, sample, or observation. Point your parser or loader at the file and check it reads the documented records, variables, or headers; binary formats ship a readable twin or metadata listing for comparison.
Code examples
import pandas as pd
df = pd.read_csv("coordinate-convention-reference.csv")
print(df.head())
print(df.dtypes)Related files
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