Auto Proteomics
/install auto-proteomics
Auto Proteomics
Author: Guo Xuan 郭轩
Contact: [email protected]
auto-proteomics is a public v0.x skill for processed proteomics downstream work.
The current public promise is intentionally narrow:
- one shipped runnable workflow:
dda-lfq-processed - one public input family: processed DDA LFQ protein-level tables
- one public comparison model:
group-avsgroup-b
Everything else in this repository should be read as routing context, internal prototype, or future scaffold unless a document explicitly marks it as part of the public promise.
Presence of a script, schema, or branch document does not mean the route is publicly supported.
In particular, dia-quant is intentionally exposed as an internal prototype route for correct routing and contract validation, not as a shipped public workflow.
Use this skill when
- the user already has processed protein-level quantification output
- the main table is MaxQuant-like
proteinGroups.txt - the goal is QC, normalized matrix generation, and two-group differential protein analysis
- the user wants a low-token, file-driven workflow instead of a long chat-only protocol
Do not use this skill when
- the user starts from raw spectra and needs search/identification
- the request is primarily DIA, phosphoproteomics, enrichment, or multi-omics execution
- the task requires more than one comparison design in the current release
- the user only wants generic statistics with no proteomics context
Public promise in v0.x
Shipped and supported now:
- route processed DDA LFQ downstream requests into
dda-lfq-processed - validate the expected processed-input shape
- generate matrix, QC, differential tables, report, and manifest outputs
Not promised yet:
- raw-spectrum search pipelines
- DIA public execution support
- phosphoproteomics execution
- enrichment execution
- multi-omics execution
- generalized study-design handling beyond the current two-group path
Internal prototype route available for routing only:
dia-quantmay be selected only when the request is explicitly about processed DIA quant tables that fit the checked-in DIA contract- selecting
dia-quantmeans internal prototype triage, never a publicv0.xexecution recommendation
Important boundary:
- non-shipped branches may contain scaffold or prototype execution files for internal framework development
- smaller models must not treat those files as public runnable recommendations unless a route is explicitly marked
shipped
Minimal workflow
- Read
references/WORKFLOW_INDEX.yaml - If the route is unclear, run
scripts/decision/route_proteomics.py - Check that the request fits the public
v0.xboundary - Run
scripts/workflows/dda_lfq_processed.sh - Use
references/for runtime, onboarding, and development rules
Public runnable entrypoint
bash scripts/workflows/dda_lfq_processed.sh \
--input-dir \x3Crun_dir> \
--protein-groups \x3CproteinGroups.txt> \
--summary \x3Csummary.txt> \
--parameters \x3Cparameters.txt> \
--output-dir \x3Coutput_dir> \
--group-a \x3Ccondition_a> \
--group-b \x3Ccondition_b>
Input contract
Required:
proteinGroups.txtwithLFQ intensity *orIntensity *columnssummary.txtwithRaw fileandExperimentcolumns
Optional:
parameters.txt
Output contract
The shipped workflow produces:
- normalized protein matrix files under
matrix/ - QC outputs under
qc/ - differential protein tables under
stats/ REPORT.mdsummary.jsonrun_manifest.json
Repository layers
SKILL.md: public entry and release boundaryreferences/WORKFLOW_INDEX.yaml: machine-readable routing and shipped-vs-non-shipped mapreferences/BRANCH_FRAMEWORK.md: standard branch contract for future routesreferences/branches/: per-branch specs for scaffold and prototype workflowsreferences/DIA_INPUT_SCHEMA.md: first narrow schema for DIA prototype intakescripts/workflows/dda_lfq_processed.sh: shipped workflow entrypoint- shipped public guidance lives in documents that explicitly describe the processed DDA
v0.xpath - non-shipped reference docs exist for internal framework development and must not be surfaced as public support
Read next
references/WORKFLOW_INDEX.yamlreferences/RUNTIME_REQUIREMENTS.mdreferences/BRANCH_FRAMEWORK.mdreferences/DEMO_INPUT_GUIDE.mdreferences/DEVELOPMENT_GUIDE.md
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install auto-proteomics - After installation, invoke the skill by name or use
/auto-proteomics - Provide required inputs per the skill's parameter spec and get structured output
What is Auto Proteomics?
Public OpenClaw skill for low-token routing and downstream analysis of processed DDA LFQ proteomics inputs. Use when the user already has protein-level quant... It is an AI Agent Skill for Claude Code / OpenClaw, with 123 downloads so far.
How do I install Auto Proteomics?
Run "/install auto-proteomics" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Auto Proteomics free?
Yes, Auto Proteomics is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Auto Proteomics support?
Auto Proteomics is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Auto Proteomics?
It is built and maintained by Billwanttobetop (@billwanttobetop); the current version is v0.2.0.