> ## Documentation Index
> Fetch the complete documentation index at: https://proto.evodesign.org/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# MinCED

> [MinCED](https://github.com/ctSkennerton/minced) (Mining CRISPRs in Environmental Datasets) is a fast Java program that locates [CRISPR](https://en.wikipedia.org/wiki/CRISPR) arrays in nucleotide sequences from isolate genomes or metagenomic contigs. It returns each detected array as an ordered list of repeat-spacer units with their genomic coordinates, the repeat consensus, and per-spacer sequence.

<div class="page-hero">
  <img class="page-hero-banner" src="https://proto-bio.github.io/proto-assets/images/tool/minced/hero.png" alt="MinCED" />
</div>

<Note>
  **License:** MinCED has a GPL-3.0 license. Please refer to [the license](https://github.com/ctSkennerton/minced/blob/master/LICENSE) for full terms.
</Note>

<p class="entity-disclaimer">This toolkit is open source. Any third-party models, product names, or trademarks referenced are the property of their respective owners, and Proto is not affiliated with them.</p>

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  <div class="cite-code-wrap">
    ```bibtex theme={null}
    @software{skennerton2019minced,
      title={MinCED: Mining CRISPRs in Environmental Datasets},
      author={Skennerton, Connor T and Angly, Florent},
      year={2019},
      url={https://github.com/ctSkennerton/minced},
      note={Derived from the CRISPR Recognition Tool (CRT) by Bland et al., 2007}
    }
    ```
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<div class="entity-contributors"><span class="entity-contributors-label">Toolkit contributors</span><span class="entity-contributors-people"><a class="entity-contributor" href="https://github.com/bviggiano" target="_blank" rel="noopener" title="bviggiano: 22 commits"><img noZoom class="entity-contributor-avatar" src="https://avatars.githubusercontent.com/u/21143637?v=4&s=64" alt="" loading="lazy" /><span class="entity-contributor-login">bviggiano</span></a><a class="entity-contributor" href="https://github.com/dguo8412" target="_blank" rel="noopener" title="dguo8412: 17 commits"><img noZoom class="entity-contributor-avatar" src="https://avatars.githubusercontent.com/u/46211285?v=4&s=64" alt="" loading="lazy" /><span class="entity-contributor-login">dguo8412</span></a><a class="entity-contributor" href="https://github.com/brianhie" target="_blank" rel="noopener" title="brianhie: 1 commit"><img noZoom class="entity-contributor-avatar" src="https://avatars.githubusercontent.com/u/6365340?v=4&s=64" alt="" loading="lazy" /><span class="entity-contributor-login">brianhie</span></a><a class="entity-contributor" href="https://github.com/leba01" target="_blank" rel="noopener" title="leba01: 1 commit"><img noZoom class="entity-contributor-avatar" src="https://avatars.githubusercontent.com/u/124846286?v=4&s=64" alt="" loading="lazy" /><span class="entity-contributor-login">leba01</span></a></span></div>

| Function       | Description                                               |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
| -------------- | --------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `run_minced()` | Detect CRISPR arrays in nucleotide sequences using MinCED | <a href="#api-run-minced" class="func-table-btn func-api-btn"><svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><path d="M4 19.5v-15A2.5 2.5 0 0 1 6.5 2H19a1 1 0 0 1 1 1v18a1 1 0 0 1-1 1H6.5a1 1 0 0 1 0-5H20" /></svg> Docs</a> <a href="https://github.com/evo-design/proto-tools/blob/47e34afa5ea240a3b406e323dc38aa5dc85f223e/proto_tools/tools/gene_annotation/minced/minced.py#L242" target="_blank" class="func-table-btn func-source-btn"><svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="16 18 22 12 16 6" /><polyline points="8 6 2 12 8 18" /></svg> Source</a> |

## Background

MinCED is a derivative of the [CRISPR Recognition Tool (CRT)](https://pmc.ncbi.nlm.nih.gov/articles/PMC1924867/) ([Bland et al., 2007](https://doi.org/10.1186/1471-2105-8-209)), maintained by [Connor Skennerton](https://github.com/ctSkennerton). CRISPR arrays are blocks of short, near-identical direct repeats (typically 23 to 47 nt) separated by unique [spacer](https://en.wikipedia.org/wiki/CRISPR#Spacer_acquisition) sequences (typically 26 to 50 nt) that record fragments of past viral and plasmid infections; they form the heritable memory of the [CRISPR-Cas adaptive immune system](https://en.wikipedia.org/wiki/CRISPR) of bacteria and archaea.

Internally, MinCED uses a [k-mer](https://en.wikipedia.org/wiki/K-mer) seed-and-extend strategy. It scans for short exact k-mer matches that recur at a consistent spacing, then extends each seed bidirectionally to the actual repeat length, and finally validates the candidate by checking that the inter-repeat spacers fall within the configured length window. The algorithm runs on raw DNA, has linear time complexity in sequence length, and finishes in seconds on a typical 5 Mb bacterial genome on commodity CPU hardware.

### Learning Resources

* [ctSkennerton/minced](https://github.com/ctSkennerton/minced) (Connor Skennerton) - official repository with the canonical command-line flag surface, installation instructions, and example output.
* [PMC1924867 (CRT paper)](https://pmc.ncbi.nlm.nih.gov/articles/PMC1924867/) (Bland et al.) - the full text of the algorithm description, including the seed-and-extend mechanism and the comparison against PatScan and PILER-CR.

## Tools

<a name="api-run-minced" />

<div class="tool-section-card">
  ### MinCED CRISPR Array Detection (`minced-crispr`)

  Detects CRISPR arrays in one or more nucleotide sequences. Returns, per input sequence, a list of `CrisprArray` objects; each carries an ordered list of `CrisprRepeatSpacer` units with the repeat's start position, the repeat sequence, and the following spacer (the last unit has no spacer).

  #### API Reference

  <div class="api-model-section api-input-section">
    <a href="https://github.com/evo-design/proto-tools/blob/47e34afa5ea240a3b406e323dc38aa5dc85f223e/proto_tools/tools/gene_annotation/minced/minced.py#L79" target="_blank" class="func-table-btn func-source-btn api-model-source"><svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="16 18 22 12 16 6" /><polyline points="8 6 2 12 8 18" /></svg> Source</a>

    <Accordion title="Input: MincedInput">
      <ParamField path="sequences" type="List[string]" required>
        Nucleotide sequence(s) to search for CRISPR arrays. Labeled positionally (`seq_0`, `seq_1`, ...); results are returned in input order.
      </ParamField>
    </Accordion>
  </div>

  <div class="api-model-section api-config-section">
    <a href="https://github.com/evo-design/proto-tools/blob/47e34afa5ea240a3b406e323dc38aa5dc85f223e/proto_tools/tools/gene_annotation/minced/minced.py#L159" target="_blank" class="func-table-btn func-source-btn api-model-source"><svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="16 18 22 12 16 6" /><polyline points="8 6 2 12 8 18" /></svg> Source</a>

    <Accordion title="Config: MincedConfig">
      <ParamField path="min_num_repeats" type="integer" default="3">
        Minimum repeats per array. Default 3.
      </ParamField>

      <ParamField path="min_repeat_length" type="integer" default="23">
        Minimum repeat length in nt. Default 23.
      </ParamField>

      <ParamField path="max_repeat_length" type="integer" default="47">
        Maximum repeat length in nt. Default 47. Must be ≥ `min_repeat_length`.
      </ParamField>

      <ParamField path="min_spacer_length" type="integer" default="26">
        Minimum spacer length in nt. Default 26.
      </ParamField>

      <ParamField path="max_spacer_length" type="integer" default="50">
        Maximum spacer length in nt. Default 50. Must be ≥ `min_spacer_length`.
      </ParamField>

      <ParamField path="verbose" type="integer" default="0">
        Verbosity level (0=quiet, 1=info, 2=debug, 3=raw subprocess stderr). `True` is coerced to `1` and `False` to `0`.
      </ParamField>

      <ParamField path="device" type="string" default="cpu">
        Device to run the tool on.
      </ParamField>

      <ParamField path="timeout" type="integer" default="3600">
        Maximum execution time in seconds. `None` waits indefinitely.
      </ParamField>

      <ParamField path="seed" type="integer">
        Random seed. When set, tools run reproducibly up to small GPU float noise (see `BaseToolOutput.approx_equal`), and the seed participates in cache keys. When None, cacheable seed-sensitive tools skip cache until seeded.
      </ParamField>
    </Accordion>
  </div>

  <div class="api-model-section api-output-section">
    <a href="https://github.com/evo-design/proto-tools/blob/47e34afa5ea240a3b406e323dc38aa5dc85f223e/proto_tools/tools/gene_annotation/minced/minced.py#L103" target="_blank" class="func-table-btn func-source-btn api-model-source"><svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><polyline points="16 18 22 12 16 6" /><polyline points="8 6 2 12 8 18" /></svg> Source</a>

    <Accordion title="Output: MincedOutput">
      <ResponseField name="results" type="List[MincedSequenceResult]">
        Per-sequence CRISPR detection results.

        <Expandable title="MincedSequenceResult">
          <ResponseField name="sequence_id" type="string" required>
            ID of the input sequence
          </ResponseField>

          <ResponseField name="crispr_arrays" type="List[CrisprArray]">
            CRISPR arrays detected in this sequence
          </ResponseField>
        </Expandable>
      </ResponseField>
    </Accordion>
  </div>

  #### Applications

  Use this to confirm and catalog CRISPR loci across newly sequenced bacterial and archaeal genomes, or to mine spacer libraries from metagenomic assemblies for phage-host interaction studies. As a pre-filter, run `minced-crispr` first to verify that a candidate contig actually carries a CRISPR array before spending compute on downstream Cas and tracrRNA analysis with [`pyhmmer-hmmsearch`](https://bio-pro.mintlify.app/tools/gene-annotation/pyhmmer) for Cas effector domains and [`crispr-tracr-rna`](https://bio-pro.mintlify.app/tools/gene-annotation/crispr-tracr-rna) for tracrRNA on the same locus. The spacer set returned for each array can then be aligned against phage or plasmid sequence databases to reconstruct the host's immune history.

  #### Usage Tips

  * **`min_num_repeats` controls the sensitivity-versus-specificity trade-off.** The default of 3 balances both for typical bacterial and archaeal genomes. Lower it to 2 to catch partial or degraded arrays at the cost of more false positives, and raise it to 4 or more when only high-confidence arrays should pass through.
  * **The 23 to 47 nt repeat and 26 to 50 nt spacer windows match canonical CRISPR loci.** Widen `max_repeat_length` and `max_spacer_length` to detect atypical families such as Type IV-A or CRISPR systems with unusually long spacers, and lower `min_repeat_length` only when chasing partial repeats since values below 23 nt start to pick up generic tandem repeats.
  * **MinCED only locates the array; it does not identify Cas genes or classify the CRISPR system.** Type assignment requires downstream Cas-effector annotation, typically `pyhmmer-hmmsearch` against curated Cas HMMs or a dedicated classifier such as CRISPRcasIdentifier.
  * **Inverted length ranges are caught at config time.** Setting `max_repeat_length < min_repeat_length` or `max_spacer_length < min_spacer_length` raises `ValueError` before the run starts, so the call fails fast instead of completing with an empty result set.
  * **Spacer count is not an immunity-breadth metric.** Multiple spacers in an array can target the same phage, and many spacers are degraded remnants of historical encounters, so the number of spacers overestimates how many distinct threats the host can recognize today.
</div>

## Toolkit Notes

These apply to every MinCED tool in this toolkit (`minced-crispr`).

* **Runs on CPU only.** MinCED is a Java program; the standalone install bundles a Java runtime alongside the `minced` program. There is no GPU acceleration to enable, and runtime is seconds per typical bacterial genome.
* **Self-contained after install.** The standalone `setup.sh` downloads the `minced` program once; subsequent runs need no network access and no model weights or reference databases.
* **Sequences are processed one at a time.** The wrapper iterates over `inputs.sequences` sequentially rather than parallelizing across them. For large batches, run independent calls in parallel from the caller side.

<Tip>
  **Example notebook:** See the [full working example](https://github.com/evo-design/proto-tools/blob/47e34afa5ea240a3b406e323dc38aa5dc85f223e/proto_tools/tools/gene_annotation/minced/examples/example.ipynb) for a copy-paste-ready walkthrough.
</Tip>

## Infrastructure Guides

The following guides cover how to run tools efficiently and at scale.

<CardGroup cols={2}>
  <Card title="Tool Persistence" icon="repeat" href="/docs/tools/guides/tool-persistence">Keep a tool's model warm across calls instead of reloading it every invocation.</Card>
  <Card title="Device Management" icon="cpu" href="/docs/tools/guides/device-management">How GPUs are allocated to tools and how to target specific devices.</Card>
  <Card title="Parallel Execution" icon="layers" href="/docs/tools/guides/parallel-execution">Fan a batch of inputs out across multiple GPUs.</Card>
</CardGroup>
