DotMatch Workflow Integration Roadmap

This roadmap builds on the workflow integration kit in docs/workflow-integration-kit.md. It turns reviewer-facing work into concrete assets for maintainers, workflow reviewers, core facilities, CRISPR teams, and assay developers without expanding DotMatch’s validated scope.

Use docs/workflow-integration-plan.json as the machine-readable checklist for these ten assets. Reviewer readiness is checked by docs/reviewer-readiness.json and scripts/check_reviewer_readiness_assets.py. Public use records follow the approval requirements in docs/adopters/README.md.

1. Reviewer 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 separately from local examples.

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 teams	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 Packet

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

• Positioning: homepage.

• Bioinformatics evaluation: docs/bioinformatics-evaluation.md.

• External review packet: docs/external-review-packet.md.

• Install proof: PyPI, Bioconda, packaging notes.

• Output contract: schemas and command reference.

• Validated scope: scientific claims and trust/scope docs.

• Evidence: evidence gallery and benchmark pages.

• Citation: methods and citation template.

• Public use records: adopter notes and workflow status JSON.

• Integration status: docs/integration-targets.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.

6. Technical Communication Pack

Technical Thread

DotMatch focuses on one layer: assigning fixed read windows to known short DNA
targets.

Why that matters:
1. unique reads can be counted
2. ambiguous reads stay out of forced calls
3. unmatched reads remain reviewable
4. invalid windows are visible QC failures

Docs: https://dotmatch.readthedocs.io/
Homepage: https://dnncha.github.io/dotmatch

Forum Prompt

I am looking for feedback from teams that run known-target sequencing assays:
CRISPR guide counting, inline barcode demultiplexing, feature tags, primers, or
panel starts. DotMatch is scoped to assignment reliability, not downstream
screen statistics or genome alignment. Which workflow wrapper would make review
easiest for your lab: nf-core, MultiQC, Galaxy, Snakemake, or something else?

Release Follow-Up

The latest DotMatch release gates package installability, docs, scientific
validated scope, workflow examples, and public evidence checks before release
tagging. The project is looking for reviewed workflow integrations and scoped
technical feedback.

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. Evaluation Scorecard

Use docs/pilot-program.md for intake fields, review steps, and public-use record requirements.

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 use record approved	0-2	Approved wording and public URL, if applicable

Interpretation:

• 0-4: workflow fit is poor or incomplete.

• 5-8: useful evaluation; record blockers and repeat after fixes.

• 9-12: strong candidate for a documented public workflow example or approved use record.

9. Integration Tracking Metrics

Track integration status 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 use 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 metrics with performance or correctness claims. Workflow interest can increase before external integration is accepted.

10. Release Communications Calendar

Use this around each release or major integration push.

Time	Action	Evidence link
T-7 days	Confirm validated scope 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 integration metrics snapshot	public records only

Completion Rule

These assets are complete only when the homepage, docs index, integration 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.