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Cibersort Immune Infiltration Analysis

skill-aipoch-medical-research-skills-cibersort-immune-infiltration-analysis · by aipoch

Use when estimating relative immune cell infiltration from a bulk expression matrix with a CIBERSORT-style nu-SVR deconvolution workflow based on an LM22 signature matrix, comparing one case group against one control group, and generating structured tables plus immune-fraction plots. NOT for single-cell RNA-seq, spatial data, clinical diagnosis, or workflows that require the original hosted CIBER…

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Install

$ agentstack add skill-aipoch-medical-research-skills-cibersort-immune-infiltration-analysis

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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Declared compatibility

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Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

> Source: https://github.com/aipoch/medical-research-skills

CIBERSORT Immune Infiltration Analysis

When to Use

  • Estimate relative immune cell fractions from a bulk expression matrix.
  • Compare one case group against one control group after deconvolution.
  • Generate structured tables, a serialized result object, and optional PDF plots.

When Not to Use

  • Single-cell RNA-seq, spatial transcriptomics, or clustering tasks.
  • Absolute clinical interpretation or treatment recommendation.
  • Workflows that require the original online CIBERSORT service instead of a local R implementation.

Workflow

  1. Confirm that the expression matrix, group file, and signature matrix are available.
  2. Run scripts/main.R with the case and control groups.
  3. Review the full result table, derived summary tables, and optional plots.
  4. Inspect run_record.txt and output_manifest.txt after each run, including failed validation attempts.

When to Read External Files

| Situation | File to Read | Purpose | |-----------|--------------|---------| | Need to run the analysis | scripts/main.R | CLI entry point | | Need algorithm details | references/algorithm.md | HQ reference workflow and result interpretation | | Encounter an error | references/troubleshooting.md | Error codes and environment fixes | | Need CLI examples or the baseline record | references/cli-guide.md | Example commands and validation notes | | Need packaged test inputs | tests/data/ | Demo expression matrix, group file, and LM22 file |

Usage

Rscript scripts/main.R \
  --input_file ./expression_matrix.csv \
  --group_file ./group_info.csv \
  --signature_file ./LM22.txt \
  --case_group treatment \
  --control_group control \
  --output_dir ./output \
  --qn false \
  --seed 42

Arguments

| Short | Long | Type | Default | Description | |-------|------|------|---------|-------------| | -i | --input_file | file | required | Expression matrix with genes as rows and samples as columns | | -g | --group_file | file | required | Group annotation table | | -a | --case_group | string | required | Case group label | | -b | --control_group | string | required | Control group label | | -o | --output_dir | dir | ./output | Output directory | | | --signature_file | file | tests/data/LM22.txt when present | Signature matrix file | | | --sample_col | string/int | none | Optional sample column name or 1-based index | | | --group_col | string/int | none | Optional group column name or 1-based index | | | --gene_id_case | string | upper | Gene ID normalization: asis, upper, or lower | | | --auto_unlog | boolean | true | Apply 2^x only if the expression matrix passes a conservative log-scale heuristic | | | --min_mean_expression | numeric | 1 | Minimum mean expression before deconvolution | | | --perm | integer | 1000 | Permutation count for empirical p-value estimation; 0 keeps the run lightweight but records P-value as NA | | | --qn | boolean | true | Apply quantile normalization to the mixture matrix | | | --svm_cores | integer | 1 | Worker count for the nu-SVR model selection step | | | --make_plots | boolean | true | Generate PDF plots | | | --plot_width | numeric | 16 | Default plot width in inches | | | --plot_height | numeric | 10 | Default plot height in inches | | -s | --seed | integer | 42 | Random seed | | -t | --timeout_seconds | integer | 0 | Optional timeout in seconds; 0 disables it | | | --verbose | boolean | true | Print progress logs |

Input Format

Expression Matrix

CSV or TSV. The first column must contain gene identifiers. Remaining columns must be numeric sample-level expression values.

When --auto_unlog=true, the workflow reports summary statistics and applies 2^x only if the matrix passes a conservative log-scale heuristic. If the matrix is ambiguous, the values are left unchanged and the startup log explains why.

If duplicate gene identifiers are present, they are consolidated after gene-ID normalization by taking the per-sample maximum before downstream filtering and deconvolution.

gene,Sample1,Sample2,Sample3
TP53,10.2,8.5,9.1
CXCL9,4.3,6.1,5.7

Group File

CSV or TSV with one sample column and one group column.

sample,group
Sample1,control
Sample2,treatment
Sample3,treatment

Signature Matrix

The packaged default is tests/data/LM22.txt. A custom signature matrix must contain one gene column followed by immune-cell signature columns.

All immune-cell signature columns must be numeric and finite. If duplicate gene identifiers are present, they are consolidated by taking the per-cell-type maximum before gene intersection.

Output Files

| File | Description | |------|-------------| | data/cibersort_input.rds | Serialized aligned input matrices used by the local algorithm | | data/cibersort_null_distribution.rds | Serialized permutation null distribution | | data/cibersort_result.rds | Serialized result object with cell fractions, metrics, runtime settings, and heatmap rendering metadata | | table/CIBERSORT_Results.csv | Full result table in CSV format | | table/CIBERSORT-Results.txt | Full result table in tab-delimited text format | | table/cibersort_cell_fractions_wide.csv | Wide-format immune cell fraction table | | table/cibersort_cell_fractions_long.csv | Long-format immune cell fraction table | | table/cibersort_group_compare.csv | Case-vs-control comparison summary | | table/cibersort_quality_metrics.csv | Sample-level P-value, Correlation, and RMSE table | | table/immune_cell_correlation_matrix.csv | Spearman correlation matrix across immune cell types | | table/immune_cell_correlation_pvalue.csv | P-value matrix aligned to the correlation matrix | | plot/immune_cell_composition_sample.pdf | Sample-level stacked composition plot when --make_plots=true | | plot/immune_group_boxplot.pdf | Group comparison boxplot when --make_plots=true | | plot/immune_correlation_heatmap.pdf | Immune-cell correlation heatmap when --make_plots=true | | session_info.txt | R session information | | output_manifest.txt | Append-only output manifest for successful and failed runs | | run_record.txt | Append-only structured run record, including runtime notes and failed-run summaries |

When --make_plots=false, the plot/ directory may still exist as part of the standard output layout, but no PDF plot files are written.

When --perm=0, the workflow logs a warning and completes without empirical permutation testing, so the P-value column is recorded as NA.

When a rerun targets an existing --output_dir and then fails validation or execution, the previous successful payload is preserved and the failure is appended to run_record.txt and output_manifest.txt.

Error Handling

| Error Code | Meaning | Solution | |------------|---------|----------| | SKILL_FILE_NOT_FOUND | An input file or signature matrix was not found | Check the file path and rerun | | SKILL_MISSING_COLUMNS | A required column is missing | Fix the input schema | | SKILL_EMPTY_DATA | No usable genes, samples, or deconvolution outputs remain | Check the data, filtering, or signature overlap | | SKILL_INVALID_PARAMETER | A CLI parameter is missing or invalid | Review the argument table and input values | | SKILL_SAMPLE_MISMATCH | Expression samples and group annotations do not align | Harmonize sample identifiers | | SKILL_PACKAGE_NOT_FOUND | A required R package is missing | Install the missing package | | SKILL_TIMEOUT | The configured time limit was exceeded | Increase --timeout_seconds or set it to 0 |

If the error persists, READ: references/troubleshooting.md

Input Validation

This skill accepts:

  • A bulk expression matrix file in CSV or TSV format with one gene column and numeric sample columns.
  • A group annotation file in CSV or TSV format with one sample column and one group column.
  • Exactly one case group label and one control group label for comparison.
  • An optional custom signature matrix compatible with the documented LM22-style schema.

Do not use this skill for:

  • Single-cell RNA-seq, spatial transcriptomics, or cell clustering workflows.
  • Clinical diagnosis, treatment recommendation, or patient-level medical decision making.
  • Requests that need the hosted CIBERSORT web service rather than this local R implementation.
  • Multi-group study designs that require more than one case group versus one control group in a single run.

If the user's request is outside this scope, do not proceed with the workflow. Instead respond:

> "cibersort-immune-infiltration-analysis is designed for local CIBERSORT-style immune deconvolution from a bulk expression matrix with one case group and one control group. Your request appears to be outside this scope. Please provide compatible bulk-expression inputs and group labels, or use a more appropriate tool for your task."

Testing

Rscript scripts/main.R --help

Rscript tests/run_tests.R

Rscript tests/test_skill.R

Validated packaged test path:

Rscript scripts/main.R \
  --input_file tests/data/expression_matrix.csv \
  --group_file tests/data/group_info.csv \
  --signature_file tests/data/LM22.txt \
  --case_group Tumor \
  --control_group Healthy \
  --output_dir tests/output \
  --perm 25 \
  --qn false \
  --svm_cores 1 \
  --seed 42

Container note:

  • The packaged test path uses --qn false because preprocessCore::normalize.quantiles() may trigger environment-level thread failures in some containers.
  • If you need a quantile-normalized run, validate that environment first and record the result in references/cli-guide.md.
  • tests/run_tests.R also checks that a failed rerun does not erase an existing successful payload directory.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.