Transform lengthy academic papers into concise, structured 250-word abstracts.
日本語の概要は準備中です。原文の説明を表示しています。
Run GSEA on a ranked gene list and produce the enrichment table, running-score table, and enrichment plots.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
| Situation | Read | Purpose |
|---|---|---|
| Need algorithm details | references/algorithm.md | Statistical method and formulas |
| Need to run an analysis | scripts/main.R | Full command reference |
| Hit an error | references/troubleshooting.md | Look up error codes and fixes |
| Need CLI examples | references/cli-guide.md | Worked argument examples |
Use this skill for:
enrichGSEA.csv and gsea_running_scores.csvtests/data/sample_deg_results.csvDo not use it for:
Analysis mode:
Rscript scripts/main.R --input tests/data/sample_deg_results.csv --outdir ./GSEA_analysis --type KEGG --species human --seed 42 --timeout 300
Plot mode:
Rscript scripts/main.R --running_file ./GSEA_analysis/Table/gsea_running_scores.csv --enrich_file ./GSEA_analysis/Table/enrichGSEA.csv --plot_output ./GSEA_analysis/plot/gsea_plot.pdf --top_n 5 --plot_format pdf --seed 42 --timeout 300
See references/cli-guide.md for more.
Mode selection:
--input runs analysis mode--running_file and --enrich_file runs plot mode| Short | Long | Type | Default | Required | Description |
|---|---|---|---|---|---|
-i | --input | character | NULL | yes | Input CSV file |
-o | --outdir | character | GSEA_analysis | no | Output directory |
-g | --gene_col | character | name | no | Gene column name |
-f | --fc_col | character | logFC | no | Ranking-statistic column name |
-t | --type | character | KEGG | no | Gene-set type: KEGG, HALLMARKS, GO_BP, GO_MF, GO_CC. With a preloaded RDS, HALLMARKS is automatically mapped to the asset key Hallmarks |
-s | --species | character | human | no | Species: human, mouse, rat |
-p | --pvalue_cutoff | numeric | 0.05 | no | Significance threshold |
-m | --method | character | fgsea | no | GSEA backend: fgsea or DOSE |
-c | --chunk_size | numeric | 1000 | no | Chunk size for large gene-set conversion |
-r | --rds_path | character | NULL | no | Path to a pre-stored gene-set RDS |
-v | --verbose | logical | FALSE | no | Verbose logging |
--seed | integer | 42 | no | Random seed | |
--timeout | integer | 300 | no | Timeout in seconds; <=0 disables it | |
-h | --help | logical | FALSE | no | Show help |
| Short | Long | Type | Default | Required | Description |
|---|---|---|---|---|---|
--running_file | character | NULL | yes | Path to gsea_running_scores.csv | |
--enrich_file | character | NULL | yes | Path to enrichGSEA.csv | |
--plot_output | character | gsea_plot.pdf | no | Output plot path | |
--plot_width | numeric | 8 | no | Plot width | |
--plot_height | numeric | 6 | no | Plot height | |
--plot_format | character | pdf | no | Output format: pdf or png | |
--top_n | numeric | 1 | no | Number of top pathways to plot when geneSetID is not given | |
--rank_by | character | p.adjust | no | Column used to rank pathways | |
--geneSetID | character | "" | no | Comma-separated pathway IDs | |
--plot_title | character | "" | no | Plot title | |
--colors | character | #4DBBD5,#E64B35,#00A087,#F39B7F,#3C5488,#8491B4 | no | Color list | |
--base_size | numeric | 11 | no | Base font size | |
--subplots | character | 1,2,3 | no | Sub-panel indices to display | |
--rel_heights | character | 1.5,0.8,1 | no | Relative panel heights | |
--NES_table | logical | TRUE | no | Show NES annotation | |
--no_NES_table | logical | FALSE | no | Disable NES annotation | |
--NES_label_size | numeric | 4 | no | NES label font size | |
--NES_label_x | numeric | 0.75 | no | NES label x position | |
--NES_label_y | numeric | 0.75 | no | NES label y position | |
--NES_label_color | character | black | no | NES label color | |
--NES_label_hjust | numeric | 0 | no | NES label horizontal justification | |
--NES_label_vjust | numeric | 1 | no | NES label vertical justification | |
--line_width | numeric | 1 | no | ES line width | |
--dot_size | numeric | 1.2 | no | ES dot size | |
--legend_position | character | auto | no | Legend position | |
--legend_x | numeric | 0.02 | no | Inset legend x coordinate | |
--legend_y | numeric | 0.02 | no | Inset legend y coordinate | |
--legend_just_x | numeric | 0 | no | Legend horizontal justification | |
--legend_just_y | numeric | 0 | no | Legend vertical justification | |
--legend_text_size | numeric | 9 | no | Legend text size | |
--legend_key_size | numeric | 0.6 | no | Legend key size | |
--legend_bg_alpha | numeric | 0 | no | Legend background alpha | |
--grid_major_color | character | grey92 | no | Major grid color | |
--grid_minor_color | character | grey92 | no | Minor grid color | |
--ylab_es | character | Enrichment Score | no | ES panel y-axis title | |
--ylab_rank | character | Ranked List Metric | no | Rank panel y-axis title | |
--xlab_rank | character | Rank in Ordered Dataset | no | Rank panel x-axis title | |
--hit_height | numeric | 1 | no | Hit-bar height | |
--hit_gap | numeric | 0 | no | Hit-bar gap | |
--hit_linewidth | numeric | 0.5 | no | Hit-bar line width | |
--rank_bar_alpha | numeric | 0.9 | no | Rank-bar alpha | |
--rank_bar_height_ratio | numeric | 0.3 | no | Rank-bar height ratio | |
--rank_metric_segment_color | character | grey | no | Rank-line color | |
--rank_metric_segment_width | numeric | 0.3 | no | Rank-line width | |
--rank_metric_segment_alpha | numeric | 1 | no | Rank-line alpha | |
--pvalue_table | logical | FALSE | no | Show p-value table | |
--ES_geom | character | line | no | ES geometry: line or dot | |
--verbose | logical | FALSE | no | Verbose logging | |
--seed | integer | 42 | no | Random seed | |
--timeout | integer | 300 | no | Timeout in seconds; <=0 disables it | |
-h | --help | logical | FALSE | no | Show help |
Analysis-mode input is a CSV with at least:
name)logFC)Example:
name,logFC,pvalue,padj
TP53,2.5,0.001,0.01
BRCA1,1.8,0.005,0.02
EGFR,-1.2,0.01,0.05
Value constraints:
type accepts KEGG, HALLMARKS, GO_BP, GO_MF, GO_CCHALLMARKS is automatically matched to the asset key Hallmarksspecies accepts human, mouse, rat| File | Format | Description |
|---|---|---|
data/GSEA_list.rda | RDA | Full GSEA result object |
Table/enrichGSEA.csv | CSV | Enrichment result table |
Table/gsea_running_scores.csv | CSV | Running-score table; if no enrichment passes, a header-only file is still written |
plot/ | directory | Plot output directory |
session_info.txt | TXT | R version and package versions |
enrichGSEA.csv mainly contains: ID, Description, NES, pvalue, p.adjust, core_enrichment.
Common error codes:
SKILL_FILE_NOT_FOUND: input file does not existSKILL_MISSING_COLUMNS: required columns are missingSKILL_EMPTY_DATA: input is empty, or empty after filteringSKILL_INVALID_PARAMETER: an argument has an invalid valueSKILL_PACKAGE_NOT_FOUND: a required package is not installedSKILL_ANALYSIS_FAILED: GSEA still failed after retriesTriage doc: references/troubleshooting.md
Exit codes:
0: success1: failureMinimal test dataset: tests/data/sample_deg_results.csv
Minimal command:
Rscript scripts/main.R --input tests/data/sample_deg_results.csv --outdir ./test_output --type KEGG --species human --seed 42 --timeout 300 --verbose
Expected output:
./test_output/data/GSEA_list.rda./test_output/Table/enrichGSEA.csv./test_output/Table/gsea_running_scores.csv./test_output/session_info.txtgsea_running_scores.csv is still written but contains only the header0まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Transform lengthy academic papers into concise, structured 250-word abstracts.
日本語の概要は準備中です。原文の説明を表示しています。
Precision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.
日本語の概要は準備中です。原文の説明を表示しています。
Refines long medical academic texts into SCI-style unstructured Chinese and English abstracts; use when you need to condense drafts/reports/summaries into bilingual abstracts and generate Summary_Report.md.
日本語の概要は準備中です。原文の説明を表示しています。
Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content. Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript.
日本語の概要は準備中です。原文の説明を表示しています。
Generates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze data with `adme-property-predictor` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
日本語の概要は準備中です。原文の説明を表示しています。