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predict_expression

Read-only

Predict a gene's expression from the sequence around its TSS.

    Expression is cell-type-specific, so `description` (cell type /
    assay context, e.g. 'K562 cell line') is REQUIRED — the API
    rejects requests without it.

    The input rule is the same for every expression model: at least
    9,198 bp, with the TSS at least 4,599 bp from each end, up to
    500,000 bp. Longer TSS-centred sequence gives better predictions:
    each model's bio_spec.recommended_flank_bp (see list_models) says how
    many bp it reads on each side of the TSS, and flank beyond that is
    ignored. Less flank, down to 4,599 bp, is accepted and scored, but
    the model then reads less than it was trained on. Omit `model` for
    the server's default.

    - A 9,198 bp sequence with the TSS at offset 4,599 (the midpoint)
      needs no `tss_index`.
    - Any longer sequence needs `tss_index`: the 0-based offset of the
      TSS into it (a fetch_gene_for_expression handle carries its own).
      The API cuts what the model reads around that offset and never
      scans for a TSS itself.

    Under 9,198 bp, or a TSS closer than 4,599 bp to either end, is
    rejected here and by the API (422). A locus with no offset is
    rejected too, because it is indistinguishable from a mis-centred
    window. A very N-rich or low-complexity window can also be refused
    by the API (422).

    An offset that is merely WRONG (e.g. counted over a wrapped FASTA's
    characters, or against a chromosome coordinate instead of an offset
    into THIS sequence) still succeeds and scores the wrong window —
    verify meta.task_specific_counts.scored_window in the response.

    Easiest paths: fetch_gene_for_expression(gene) already fetches a
    long TSS-centred handle (as much flank as the listed models
    recommend) and records its `tss_index`, which is sent for you when
    you pass that handle without one; find_genes_and_predict_expression
    takes a raw region and finds each TSS for you.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional model id; omit for the task default. See list_models.
sequenceNoDNA bases A/C/G/T/N (case-insensitive). Line breaks are ignored (a wrapped FASTA body may be pasted verbatim; a `>` header line may not). Mutually exclusive with `sequence_ref`.
tss_indexNo0-based offset of the transcription start site into the sequence, counted in bases (whitespace is ignored). Required unless the sequence is exactly 9,198 bp; must leave at least 4,599 bp on each side (4,599 <= tss_index <= length - 4,599). The model reads the sequence around this offset (9,198 bp for g0-expression, more flank for a model with a larger bio_spec.recommended_flank_bp) and the API reports the slice it used as meta.task_specific_counts.scored_window. Check it: a wrong-but-in-range offset scores the wrong window silently.
descriptionNoREQUIRED experimental context — cell type / assay / conditions (e.g. 'K562 cell line', 'liver tissue'). Expression is cell-type-specific; the API rejects requests without it.
sequence_refNoHandle (seq_…) from any acquisition tool (fetch_ensembl_sequence, fetch_region, fetch_gene_for_expression, load_demo_sequence, load_local_fasta, store_inline_sequence). Mutually exclusive with `sequence`.
sequence_nameNoLabel echoed back in the response (ignored when `sequence_ref` is used).sequence

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / tss_index / description
      Previous value: -"0-based offset of the transcription start site into the sequence, counted in bases (whitespace is ignored). Required unless the sequence is exactly 9,198 bp; must leave 4,599 bp on each side. The API scores only sequence[tss_index-4599 : tss_index+4599] and reports the slice it used as meta.task_specific_counts.scored_window — check it: a wrong-but-in-range offset scores the wrong window silently."New value: +"0-based offset of the transcription start site into the sequence, counted in bases (whitespace is ignored). Required unless the sequence is exactly 9,198 bp; must leave at least 4,599 bp on each side (4,599 <= tss_index <= length - 4,599). The model reads the sequence around this offset (9,198 bp for g0-expression, more flank for a model with a larger bio_spec.recommended_flank_bp) and the API reports the slice it used as meta.task_specific_counts.scored_window. Check it: a wrong-but-in-range offset scores the wrong window silently."
  2. Changed2 schema fields changed
    • changedInput schema / properties / sequence / description
      Previous value: -"DNA bases A/C/G/T/N (case-insensitive). Mutually exclusive with `sequence_ref`."New value: +"DNA bases A/C/G/T/N (case-insensitive). Line breaks are ignored (a wrapped FASTA body may be pasted verbatim; a `>` header line may not). Mutually exclusive with `sequence_ref`."
    • addedInput schema / properties / tss_index
      Added value: +{
      +  "anyOf": [
      +    {
      +      "minimum": 0,
      +      "type": "integer"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "0-based offset of the transcription start site into the sequence, counted in bases (whitespace is ignored). Required unless the sequence is exactly 9,198 bp; must leave 4,599 bp on each side. The API scores only sequence[tss_index-4599 : tss_index+4599] and reports the slice it used as meta.task_specific_counts.scored_window — check it: a wrong-but-in-range offset scores the wrong window silently.",
      +  "title": "Tss Index"
      +}
  3. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations cover safety (readOnly/openWorld/non-destructive), but the description adds substantial behavior beyond them: the API 422s for missing description, sub-9,198 bp sequences, off-centre TSS, and N-rich/low-complexity windows; a WRONG-but-in-range tss_index silently scores the wrong window; extra flank beyond recommended_flank_bp is ignored. That is exactly the kind of failure-mode disclosure that prevents misuse.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then constraints, then easiest paths. It is long and repeats some tss_index/4,599 bp rules already in the schema, which costs a bit, but the ordering is sensible and nearly every sentence carries operational value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex, high-stakes prediction tool with an output schema present, the description is complete: it covers required context, sequence windows, offset semantics, verification of meta.task_specific_counts.scored_window, and the recommended acquisition path. An agent needs nothing more to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description goes well beyond the schema by explaining parameter interactions: description is REQUIRED despite being schema-optional, tss_index is unnecessary for exactly 9,198 bp but mandatory for longer sequences, sequence_ref handles carry their own offset, and wrong offsets succeed silently. This is real added meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource+scope ('Predict a gene's expression from the sequence around its TSS'), which cleanly separates it from siblings like predict_chromatin, predict_promoter, and predict_splice that share the same prediction idiom.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent: 'Easiest paths' names fetch_gene_for_expression for pre-fetched TSS-centred handles and find_genes_and_predict_expression for raw regions, and points at list_models for recommended flank sizes. It also states when to omit model (server default) and which params are mutually exclusive via the schema.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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