DotMatch Next 10 Industry Exposure Wins

This playbook builds on the first five exposure wins in docs/industry-exposure.md. It turns the next adoption layer into concrete assets that can be used by maintainers, workflow reviewers, core facilities, CRISPR teams, and assay developers without expanding DotMatch’s public claim boundary.

Use docs/industry-exposure-plan.json as the machine-readable checklist for these ten wins. Keep private conversations, unmerged PRs, and internal examples out of public adopter evidence until the rules in docs/adopters/README.md are satisfied.

1. Evaluator Decision Tree

Use this when someone asks whether DotMatch is relevant.

Question	If yes	If no
Do you already know the expected short target sequences?	Continue.	DotMatch is probably not the right first tool.
Is the read window fixed, scaffolded, or inferable?	Use count, demux, assay, barcode, or panel docs.	Use extraction or preprocessing before DotMatch.
Do ambiguous, unmatched, or invalid reads affect interpretation?	Lead with reliability and output artifacts.	Use DotMatch only if ordinary count outputs still help.
Do you need genome coordinates, CIGAR strings, UMI deduplication, or hit statistics?	Use established downstream tools.	DotMatch can own the assignment layer.
Do you need a public pipeline integration?	Start with workflow submissions.	Start with local install and methods text.

2. Persona One-Pagers

Core Facilities

Promise: visible assignment QC for known guides, barcodes, and panels.
Proof path: homepage, barcode troubleshooting, evidence gallery, packaging.
First command: dotmatch barcode autopsy ...
Review artifact: HTML report plus TSV/JSON outputs for lab handoff.

CRISPR Screen Teams

Promise: guide counts with explicit ambiguity and unmatched diagnostics.
Proof path: CRISPR tutorial, public CRISPR evidence, methods citation text.
First command: dotmatch crispr-count ...
Review artifact: count matrix, sample QC, top unmatched, MAGeCK-compatible table.

Workflow Maintainers

Promise: stable TSV, JSON, FASTQ, and HTML artifacts for wrappers.
Proof path: workflow submission pack, schemas, MultiQC parser, release gates.
First command: make workflow-examples-ready
Review artifact: wrapper fixture, command log, expected output contract.

Assay Developers

Promise: barcode panel design and correction-safety review before sequencing.
Proof path: barcode panel design docs, assay evidence, panel report.
First command: dotmatch panel design ...
Review artifact: design report, collision tables, plate layout, lab README.

3. Integration Target Tracker

Track external integration work without calling it adoption too early.

Target	Why it matters	Ready asset	Public state to record
nf-core modules	High-trust workflow reuse and container automation	`docs/workflow-submissions.md`	Merged PR or released module page
MultiQC module	Makes DotMatch visible in existing pipeline reports	`python/dotmatch/multiqc.py`	Released plugin or upstream integration
Galaxy/IUC	Reaches core facilities and wet-lab users	Galaxy wrapper examples	IUC acceptance or ToolShed publication
Snakemake wrapper	Easy lab workflow reuse	Snakemake example workflow	Public wrapper or external lab pipeline
bio.tools entry	Searchable bioinformatics registry presence	Homepage and metadata	Accepted bio.tools record

4. Reviewer Evidence Packet

Send this packet when a maintainer, reviewer, procurement evaluator, or PI asks what is real today.

Positioning: homepage.
Install proof: PyPI, Bioconda, packaging notes.
Output contract: schemas and command reference.
Claim boundary: scientific claims and trust/scope docs.
Evidence: evidence gallery and benchmark pages.
Citation: methods and citation template.
Adoption rules: adopter notes and workflow adoption JSON.

5. Conference Abstracts

Short Abstract

DotMatch is a deterministic known-target sequencing assignment toolkit for fixed read windows such as CRISPR guides, inline barcodes, feature tags, primers, and panel targets. It reports unique, ambiguous, unmatched, and invalid read outcomes so assignment failures remain visible in workflow artifacts.

Methods Abstract

Known-target sequencing workflows often collapse assignment decisions into count tables, making ambiguous reads, shifted windows, unsafe correction, and recurring unmatched sequences hard to inspect. DotMatch separates the assignment layer from downstream interpretation: it compares configured read windows with known short DNA targets, records explicit read outcomes, and writes TSV, JSON, FASTQ, and HTML artifacts for workflow review. Public claims are scoped to checked repository evidence and release gates.

Core Facility Abstract

DotMatch helps sequencing cores review known-target assays before results leave the facility. It supports guide counting, inline barcode demultiplexing, barcode panel design, and assignment autopsy reports while preserving ambiguity, unmatched reads, and invalid extraction windows as visible QC signals.

7. Maintainer Issue Templates

nf-core / Workflow Module Opening

Title: Add DotMatch known-target assignment module

DotMatch assigns fixed read windows to known short DNA targets and writes TSV,
JSON, FASTQ, and HTML outputs. This module proposal is scoped to assignment
artifacts and explicit unique/ambiguous/unmatched/invalid outcomes.

Review asks:
- command shape and metadata
- output contract
- container pinning
- fixture coverage
- MultiQC compatibility

MultiQC Opening

Title: Parse DotMatch assignment QC outputs

DotMatch writes sample QC, summaries, top-unmatched rows, and panel-safety
outputs for known-target sequencing assignments. A MultiQC module should expose
assignment rate, ambiguity rate, unmatched rate, invalid windows, and panel
safety status without implying downstream biological pass/fail calls.

8. Pilot Scorecard

Use this privately during pilots. Publish only quote-approved summaries.

Dimension	Score	Notes
Install worked from released channel	0-2	PyPI, Bioconda, source, or container
Input mapping was understandable	0-2	Target table, sample table, read window
Assignment failures were clearer	0-2	Ambiguous, unmatched, invalid, unsafe correction
Outputs fit existing workflow	0-2	TSV, JSON, FASTQ, HTML, MultiQC, notebook
Citation and methods text was usable	0-2	Version, command, ambiguity policy
Public adoption record approved	0-2	Only with explicit approval and public URL

Interpretation:

0-4: do not publicize; fix product or docs first.
5-8: useful private feedback; consider a follow-up pilot.
9-12: candidate for quote-approved adopter record.

9. Adoption KPI Dashboard Spec

Track exposure health separately from scientific evidence.

KPI	Source	Cadence
Homepage visits to install clicks	site analytics if enabled	monthly
Docs visits to tutorial starts	docs analytics if enabled	monthly
External workflow PRs opened	GitHub URLs	weekly during push
External workflow PRs merged	accepted public records	release cycle
Public pilot records approved	`docs/adopters/`	release cycle
Citation artifacts generated	release or assay outputs	release cycle
Distribution channel health	`make distribution-channels`	release cycle

Do not combine these KPIs with performance or correctness claims. Exposure can increase before external adoption is proven.

10. Release Communications Calendar

Use this around each release or major integration push.

Time	Action	Evidence link
T-7 days	Confirm claim boundary and release notes	`docs/scientific-claims.md`
T-5 days	Prepare maintainer issue or PR drafts	`docs/workflow-submissions.md`
T-3 days	Prepare short social and forum posts	this page
Tag day	Announce only after release workflow artifacts are visible	release URL
T+1 day	Verify PyPI, Bioconda, containers, Zenodo as applicable	`docs/distribution-release.json`
T+7 days	Follow up with maintainers and pilot contacts	public URLs only
T+30 days	Update adoption KPI snapshot	private tracker or public records

Completion Rule

These wins are complete only when the homepage, docs index, exposure kit, structured plan, and site guard all reference the same ten items. If the JSON plan and markdown playbook diverge, treat the playbook as not release-ready.