REAL WORKFLOWS

End-to-end workflows with full provenance

Every use case shows the full provenance manifest — not just the output. That's the differentiator.

CRISPR bc7: 87

CRISPR Guide Design & Off-Target Scoring

TP53 knockout in A549 — proven end-to-end in crispr-system

From a gene target to ranked guide RNAs with genome-wide off-target analysis. Every step traceable to input files, tool versions, and scoring parameters.

Tools: crispr-system Cas-OFFinder CRISPRon CHOPCHOP

Terminal Session

$ hordago crispr design --gene TP53 --cell-line A549

> Loading genome index (hg38)...

> Scoring guide RNAs with CRISPRon...

> Running off-target analysis (Cas-OFFinder)...

RESULTS: 3 guides ranked

TP53-g1 GCAGCCTTTGTGAACCAACA on=0.92 off=0.02

TP53-g2 TGGTTCTCACTTGGTGGAAG on=0.89 off=0.04

TP53-g3 AGCAGGTCTGTTCCAAGGGA on=0.87 off=0.01

> Provenance manifest written: ./manifest.json

✓ Done in 4.2s

manifest.json — 4 inputs · 3 outputs

Provenance Manifest manifest.json

{
  "workflow": "crispr-guide-design",
  "version": "1.3.0",
  "timestamp": "2026-03-14T09:12:43Z",
  "inputs": {
    "gene": "TP53",
    "genome": "hg38",
    "cell_line": "A549",
    "pam": "NGG"
  },
  "tools": {
    "CRISPRon": "1.0.0",
    "Cas-OFFinder": "2.4.1",
    "CHOPCHOP": "3.0.0"
  },
  "git_commit": "a3f8c12",
  "outputs": [
    "guides.tsv",
    "offtargets.tsv",
    "summary.pdf"
  ]
}

Genomics bc7: 92

scRNA-seq QC, UMAP & Cell Type Annotation

Public 10X PBMC dataset — reproducible single-cell pipeline

Raw count matrices to annotated cell clusters. QC metrics, UMAP embeddings, and marker-based annotation — all with a manifest linking every figure to its source data.

Tools: Scanpy CellRanger UMAP SingleR

Terminal Session

$ hordago scrna qc --input pbmc_10x.h5 --species human

> Loading count matrix (2700 cells × 32738 genes)...

> Filtering: min_genes=200 max_genes=5000 pct_mito<20

> Retained 2638 cells after QC

> Computing PCA (50 components)...

> Running UMAP embedding...

> Clustering (leiden, res=0.5): 9 clusters found

> Annotating cell types with SingleR...

CELL TYPES: T cells (34%), Monocytes (22%), B cells (18%), NK (12%), ...

> Provenance manifest written: ./manifest.json

✓ Done in 38.7s

manifest.json — 4 inputs · 4 outputs

Provenance Manifest manifest.json

{
  "workflow": "scrna-qc-umap",
  "version": "2.1.0",
  "timestamp": "2026-03-14T10:05:17Z",
  "inputs": {
    "file": "pbmc_10x.h5",
    "source": "10X Genomics PBMC 3k dataset",
    "species": "human",
    "genome": "GRCh38"
  },
  "tools": {
    "Scanpy": "1.9.6",
    "CellRanger": "7.2.0",
    "UMAP": "0.5.5",
    "SingleR": "2.0.0"
  },
  "git_commit": "b7e2d45",
  "outputs": [
    "qc_metrics.csv",
    "umap.png",
    "clusters.h5ad",
    "cell_types.csv"
  ]
}

ML bc7: 75

Publication-Ready Volcano Plot from DESeq2

Differential expression results to print-ready figure

DESeq2 results compiled into a publication-ready volcano plot with statistical thresholds, gene labels, and a provenance manifest linking the figure to the exact analysis parameters.

Tools: DESeq2 R ggplot2 Life Sciences Factory

Terminal Session

$ hordago figure volcano --input deseq2_results.csv

> Loading DESeq2 results (18432 genes)...

> Applying thresholds: padj<0.05, |log2FC|>1

> Significant: 847 up, 612 down

> Labeling top 20 genes by significance...

> Rendering figure (300 DPI, CMYK)...

OUTPUT: volcano_plot.pdf (publication-ready)

Format: PDF + PNG

Size: 7in × 5in

Color profile: CMYK

> Provenance manifest written: ./manifest.json

✓ Done in 2.1s

manifest.json — 4 inputs · 3 outputs

Provenance Manifest manifest.json

{
  "workflow": "figure-volcano",
  "version": "1.0.4",
  "timestamp": "2026-03-14T11:30:02Z",
  "inputs": {
    "file": "deseq2_results.csv",
    "padj_threshold": 0.05,
    "log2fc_threshold": 1,
    "top_labels": 20
  },
  "tools": {
    "R": "4.3.2",
    "DESeq2": "1.40.2",
    "ggplot2": "3.4.4",
    "life-sciences-factory": "0.8.1"
  },
  "git_commit": "c9a1f78",
  "outputs": [
    "volcano_plot.pdf",
    "volcano_plot.png",
    "significant_genes.csv"
  ]
}

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