Convert genomic intervals between coordinate conventions, normalise and compare variant representations, and detect assembly or contig-naming mismatches before they corrupt an analysis. Use whenever coordinates cross a format, tool, or assembly boundary - converting between BED, GFF/GTF, VCF, SAM/BAM, WIG, PSL, genePred, Picard interval_list, or region strings; reconciling 0-based half-open with 1-based inclusive; left-aligning or trimming indels; checking whether two variant records describe the same change; mapping genomic to transcript, CDS, or protein positions; auditing a BED/GTF/VCF for convention violations; or diagnosing GRCh37 vs hg19 vs GRCh38 vs T2T, chr-prefix, and liftover problems. Triggers include "off by one", "0-based", "1-based", "half-open", "coordinate system", "left-align", "normalize variant", "bcftools norm", "chr prefix", "wrong genome build", "liftover", "REF mismatch", and "HGVS".
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill genomic-coordinates
Any time a coordinate crosses a boundary: between two file formats, between two
tools, between two assemblies, or between the genome and a transcript.
**A coordinate is three facts, not one: the number, the convention it is written
in, and the assembly it was measured against.** Carry all three or the number is
not interpretable.
Coordinate errors are the quietest class of bug in genomics. An off-by-one BED
file parses, sorts, and intersects without complaint. A GRCh37 VCF joined against
a GRCh38 annotation returns rows. A right-shifted indel simply fails to match its
entry in ClinVar, and the result is a variant reported as novel. Nothing raises
an error; the answer is just wrong, and it is wrong in a direction that looks
plausible.
So: convert with the table, not from memory, and verify against the reference
whenever a reference is available.
1-based inclusive -> 0-based half-open : start - 1, end
0-based half-open -> 1-based inclusive : start + 1, end
The end coordinate never moves. If a conversion changed both numbers, it is wrong.
| 0-based, half-open | 1-based, inclusive |
| --- | --- |
| BED, bedGraph, bigWig, narrowPeak | GFF3, GTF, VCF |
| BAM/CRAM (binary POS) | SAM (text POS) |
| PSL, genePred, refFlat | WIG, Picard interval_list |
| MAF (UCSC multiple alignment) | MAF (TCGA mutation annotation) |
| PyRanges, pybedtools | GRanges/IRanges, samtools & UCSC & Ensembl region strings |
Both "MAF" formats exist, they mean different things, and they disagree. UCSC
serves 0-based files through a 1-based browser box. references/format-conventions.md
has the full table with per-format detail.
cd skills/genomic-coordinates/scripts
python3 convert_coords.py --list # the table
python3 convert_coords.py --from bed --to gff chr1 999 1000
python3 convert_coords.py --from ucsc --to bed "chr7:5,530,601-5,530,625"
python3 convert_coords.py --from granges --to pyranges --input regions.tsv
contig input output length status detail
chr7 chr7:5530601-5530625 5530600-5530625 25 ok
Zero-length BED features (chromStart == chromEnd, a legal insertion point) are
reported as unrepresentable rather than converted to end = start - 1. Exit
code is 1 when any interval is degenerate or invalid.
A VCF POS for an indel is the anchor base — the base *before* the event,
itself unchanged. And the same change can be written many ways:
chr1:7:CAC:C, chr1:3:CAC:C and chr1:2:GCA:G are one deletion. Joining,
deduplicating, or looking up variants before normalising loses real matches
silently, and it loses them preferentially in repeats, where indels concentrate.
Normalise — trim to parsimony, then left-align against the reference — before any
comparison:
python3 normalize_variant.py --fasta ref.fa chr1 7 CAC C
python3 normalize_variant.py --fasta ref.fa --split --input cohort.vcf
python3 normalize_variant.py --fasta ref.fa --compare chr1:7:CAC:C chr1:2:GCA:G
input normalized type pos_shift ref_check changed
chr1:7:CAC:C chr1:2:GCA:G deletion 5 ok yes
Every record's REF is checked against the FASTA first. A MISMATCH means the
variants and the reference are different assemblies — stop and run
check_contigs.py rather than adjusting coordinates. Multi-allelic records must
be split with --split before normalising, never after.
HGVS shifts indels the opposite way, 3'-most along the transcript. For a
minus-strand gene that is the opposite genomic direction from VCF's
left-alignment. Details and the full procedure: references/variant-representation.md.
python3 check_contigs.py --identify unknown.fa.fai
python3 check_contigs.py variants.vcf annotation.gtf --genome GRCh38.fa.fai
file kind contigs naming assembly detail
ref.fa.fai sizes 25 plain GRCh37 24/24 primary chromosome lengths match;
chrM is 16569 bp, i.e. GRCh37/38 (rCRS MT)
The script reads .fai, .chrom.sizes, VCF headers, SAM headers, FASTA, BED,
and GTF/GFF, identifies the assembly from primary-chromosome lengths, and reports
every reason a join between two files would go wrong: naming mismatch, length
conflict, coordinates past a contig end, contigs present in one file only. Exit
code 1 on any incompatibility.
GRCh37 and hg19 differ only in the mitochondrion — 16,569 bp (rCRS) versus
16,571 bp. Nuclear coordinates are identical, so a mixed pipeline runs fine and
only the mtDNA results are wrong. check_contigs.py reports which one it found.
Builds, naming schemes, ALT contigs, and liftover pitfalls:
references/reference-builds.md.
python3 audit_intervals.py peaks.bed
python3 audit_intervals.py gencode.gtf --genome hg38.chrom.sizes
python3 audit_intervals.py cohort.vcf --genome GRCh38.fa.fai
Looks for the evidence that a coordinate mistake leaves behind:
| Finding | What it proves |
| --- | --- |
| start_below_one in GFF/GTF | 0-based data in a 1-based file; everything is one base left |
| many_zero_length in BED | 1-based single-base features written into a 0-based file |
| past_contig_end | wrong assembly, or an off-by-one at the contig edge |
| mixed_contig_naming | any join will silently match one subset |
| first_block_offset | BED12 blockStarts written as absolute coordinates |
| not_parsimonious | untrimmed alleles; normalise before joining |
| bad_alt_allele | Ensembl/VEP - notation in a VCF, which has no anchor base |
Exit code 1 on any fatal finding, so it works as a CI gate on a data directory.
c.742 and chr17:7,674,220 are both "position", and neither converts to the
other by arithmetic. Transcript coordinates count spliced bases in transcription
order — decreasing genomic coordinate on the minus strand — and c.1 is the A
of the initiator ATG, not the start of the transcript.
The rules that get mis-remembered: there is no c.0; 5' UTR positions are
negative and 3' UTR positions take a *; GFF phase is the bases to *remove* to
reach the next codon, not start % 3; and a c. description is meaningless
without a versioned transcript accession, because the same variant numbers
differently in each transcript. references/transcript-coordinates.md has the
conversion procedure and the boundary cases.
Do the conversion with a tool that holds the transcript model — VEP,
bcftools csq, Mutalyzer, the hgvs package — not by hand.
State the assembly next to the coordinates, every time.
chr7:5,530,601-5,530,625 is not a location; chr7:5,530,601-5,530,625 (GRCh38)
is. Say which convention a coordinate column is in, in the column header or the
file's documentation. When a conversion produced a result, say which direction it
went.
references/format-conventions.md — every format's convention, with per-formatdetail, BED12 block rules, region-string syntax, and tool behaviour.
references/variant-representation.md — VCF allele conventions, thenormalisation algorithm, equivalence checking, multi-allelic splitting, and how
HGVS disagrees with VCF.
references/reference-builds.md — build signatures, GRCh37 vs hg19, ALTcontigs, naming schemes, and liftover failure modes.
references/transcript-coordinates.md — genomic ↔ transcript ↔ CDS ↔ protein,HGVS numbering, phase, and transcript choice.
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Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
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Take k-dense-ai/genomic-coordinates from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.