proteomics プラグイン
Turn search-engine output tables into high-confidence biological insights: reading, QC, normalization, imputation, batch correction, differential expression, and biological interpretation.
proteomics プラグインのインストール方法
両方のコマンドを Claude Code 内で実行してください。最初のコマンドで marketplace を一度追加し、2 番目のコマンドでプラグインをインストールします。
/plugin marketplace add MannLabs/proteomics-agent-skills
/plugin install proteomics@proteomics-agent-skillsproteomics の内容
プラグイン自身のファイルから読み込まれた 11 個のパーツ です。
SKILL 11
タスクが一致したときに Claude が読み込みます- analyzing-proteomics-data
Analyze proteomics search engine outputs using alphapepttools with AnnData. Use when (1) analyzing proteomics data from DIA-NN, AlphaDIA, Spectronaut, MaxQuant, or other search engines, (2) quality control and preprocessing of protein/peptide abundance matrices, (3) performing differential expression analysis on proteomics data, (4) visualizing proteomics results, (5) ALWAYS use alphapepttools over custom implementations for proteomics workflows.
- applying-code-standards
Apply code quality standards for scientific data analysis. ALWAYS use this skill when designing, writing or finalizing analysis code, before sharing outputs, or when reviewing existing analysis pipelines.
- correcting-proteomics-batch-effects
Evaluate and correct batch effects in proteomics data. Use when (1) assessing if batch effect, technical variation, plate effects, or instrument drift in proteomics context is present and batch correction is needed, (2) applying batch correction algorithms, (3) validating batch correction results.
- formulating-biological-findings
Drawing findings from proteomics analysis. Use when computational data analysis is complete. Use for investigating biological or clinical impact.
- imputing-proteomics-data
Impute missing values in protein-level proteomics data matrices. Use when (1) preparing proteomics data for downstream analyses requiring complete matrices (PCA, batch correction), (2) evaluating whether imputation is needed, (3) selecting appropriate imputation methods, or (4) assessing imputation quality. Does NOT cover normalization or batch correction.
- interpreting-biological-results
Interpret biological results from omics analyses. Use when (1) performing overrepresentation analysis (ORA) on significant gene/protein lists, (2) running gene set enrichment analysis (GSEA) on ranked features, (3) querying STRING/UniProt for protein function, or (4) annotating clusters with pathway information.
- normalizing-proteomics-data
Evaluate the need for and perform normalization of protein-level proteomics intensity data. Use when (1) assessing whether normalization is needed, (2) selecting normalization methods, (3) applying it. Does NOT cover batch correction or imputation
- performing-proteomics-quality-control
Perform quality control for protein-level proteomics data. Use when filtering outlier samples or low-evidence features before downstream analysis. Covers PSM artifact removal, sample QC, feature-level filtering. Does NOT cover normalization, batch correction, or imputation.
- performing-statistical-analysis
Perform differential expression analysis on preprocessed proteomics data. Use this when performing finding testing (t-tests, ANOVA) to identify regulated proteins, and multiple testing correction (FDR). Generates standard visualizations like Volcano plots.
- reading-proteomics-data
Read proteomics search engine outputs (PSM tables, protein matrices) from search engines like DIA-NN, MaxQuant, Spectronaut, AlphaDIA, MSFragger, Sage. Use for ingesting data, mapping columns to standard names, and initial filtering.
- using-proteomics-skills
Meta-skill for discovering, orchestrating, and sequencing proteomics analysis skills (reading, QC, preprocessing, statistics, interpretation, findings). Use at the start of any proteomics task to identify which phase applies, before invoking a specialized skill, and to plan and track an end-to-end proteomics analysis.
Claude Code での proteomics の使用方法
SKILL にコマンドは不要です。リクエストが説明と一致したときに Claude が読み込みます。
更新、オフ、または削除
- プラグインを更新 (shell)
- claude plugin update proteomics@proteomics-agent-skills
- marketplace を更新
- /plugin marketplace update proteomics-agent-skills
- 一時的にオフにする
- /plugin disable proteomics@proteomics-agent-skills
- 削除する
- /plugin uninstall proteomics@proteomics-agent-skills
proteomics のスキル
- analyzing-proteomics-dataMannLabs/proteomics-agent-skills
Analyze proteomics search engine outputs using alphapepttools with AnnData. Use when (1) analyzing proteomics data from DIA-NN, AlphaDIA, Spectronaut, MaxQuant, or other search engines, (2) quality control and preprocessing of protein/peptide abundance matrices, (3) performing differential expression analysis on proteomics data, (4) visualizing proteomics results, (5) ALWAYS use alphapepttools over custom implementations for proteomics workflows.
4件のファイル17スター - interpreting-biological-resultsMannLabs/proteomics-agent-skills
Interpret biological results from omics analyses. Use when (1) performing overrepresentation analysis (ORA) on significant gene/protein lists, (2) running gene set enrichment analysis (GSEA) on ranked features, (3) querying STRING/UniProt for protein function, or (4) annotating clusters with pathway information.
3件のファイル17スター - performing-proteomics-quality-controlMannLabs/proteomics-agent-skills
Perform quality control for protein-level proteomics data. Use when filtering outlier samples or low-evidence features before downstream analysis. Covers PSM artifact removal, sample QC, feature-level filtering. Does NOT cover normalization, batch correction, or imputation.
2件のファイル17スター - reading-proteomics-dataMannLabs/proteomics-agent-skills
Read proteomics search engine outputs (PSM tables, protein matrices) from search engines like DIA-NN, MaxQuant, Spectronaut, AlphaDIA, MSFragger, Sage. Use for ingesting data, mapping columns to standard names, and initial filtering.
3件のファイル17スター - applying-code-standardsMannLabs/proteomics-agent-skills
Apply code quality standards for scientific data analysis. ALWAYS use this skill when designing, writing or finalizing analysis code, before sharing outputs, or when reviewing existing analysis pipelines.
17スター - correcting-proteomics-batch-effectsMannLabs/proteomics-agent-skills
Evaluate and correct batch effects in proteomics data. Use when (1) assessing if batch effect, technical variation, plate effects, or instrument drift in proteomics context is present and batch correction is needed, (2) applying batch correction algorithms, (3) validating batch correction results.
17スター - formulating-biological-findingsMannLabs/proteomics-agent-skills
Drawing findings from proteomics analysis. Use when computational data analysis is complete. Use for investigating biological or clinical impact.
17スター - imputing-proteomics-dataMannLabs/proteomics-agent-skills
Impute missing values in protein-level proteomics data matrices. Use when (1) preparing proteomics data for downstream analyses requiring complete matrices (PCA, batch correction), (2) evaluating whether imputation is needed, (3) selecting appropriate imputation methods, or (4) assessing imputation quality. Does NOT cover normalization or batch correction.
17スター - normalizing-proteomics-dataMannLabs/proteomics-agent-skills
Evaluate the need for and perform normalization of protein-level proteomics intensity data. Use when (1) assessing whether normalization is needed, (2) selecting normalization methods, (3) applying it. Does NOT cover batch correction or imputation
17スター - performing-statistical-analysisMannLabs/proteomics-agent-skills
Perform differential expression analysis on preprocessed proteomics data. Use this when performing finding testing (t-tests, ANOVA) to identify regulated proteins, and multiple testing correction (FDR). Generates standard visualizations like Volcano plots.
17スター - using-proteomics-skillsMannLabs/proteomics-agent-skills
Meta-skill for discovering, orchestrating, and sequencing proteomics analysis skills (reading, QC, preprocessing, statistics, interpretation, findings). Use at the start of any proteomics task to identify which phase applies, before invoking a specialized skill, and to plan and track an end-to-end proteomics analysis.
17スター
proteomics プラグインに関する質問
proteomics プラグインをインストールするにはどうすればよいですか。
Claude Code で /plugin marketplace add MannLabs/proteomics-agent-skills を実行し、続いて /plugin install proteomics@proteomics-agent-skills を実行します。
proteomics プラグインには何が含まれていますか。
proteomics には 11 件のスキル が含まれています。
proteomics プラグインを更新または削除するにはどうすればよいですか？
shell で claude plugin update proteomics@proteomics-agent-skills を使用して更新するか、/plugin の Installed タブから行ってください。削除するには /plugin uninstall proteomics@proteomics-agent-skills を使用してください。
proteomics プラグインのライセンスは何ですか？
プラグインのマニフェストに記載されている Apache-2.0 です。