OptiFoot: a method for recording protein footprints on DNA for microscopy and sequence analysis

This is a collection of Python and Bash scripts supporting the data analysis in the manuscript: https://doi.org/10.64898/2026.05.12.724470.

The workflow is organized into two main stages:

1. Extraction of OptiFoot signal as continuous fluorescence profile aligned to hg38 reference genome.
2. Further processing and analysis of the profiles using established genome analysis tools.

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Data:

• 3-color fluorescent images of individual gDNA molecules acquired on Saphyr instrument (Bionano Genomics)

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Tested with:

• Python 3.12
• BEDtools 2.31.1
• deepTools 3.5.6
• USCS bedGraphToBigWig v4

In addition requires software from Bionano Genomics:

• Bionano Access
• Saphyr Molecule Detect

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Usage

• Download scripts to you computer.
• Run scripts from inside the dataset directory.
• To run correctly, filenames must follow specific naming conventions that are shown inside each script. Typically, a filename consists of:
  • a user-defined sample ID,
  • a predefined suffix.
• Some file paths are hard-coded into the scripts. Before running, update the path variables in each script to match your local environment.

The paths within the scripts are based on the example project tree and assume that initial input files are in the Data folder.

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Workflow overview

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config:
  look: handDrawn
  theme: neutral
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flowchart TD
f2(["raw molecule images"]) --- a1["`**1.Extract OptiFoot profiles**`"] --- s["`sripts #01-09`"] -->f(["chr[i].BEDgraph <br> one profile file per chromosome"])
f --- a2["`**2.Analyze profiles**`"] --> a3["`**2a.Calculate enrichment at genome features**<br> sripts #10-16`"] 
a2 --> a4["`**2b.Calculate correlation between datasets**<br> sripts #10, #11, #16`"] 
classDef files fill:#B8E6FE,stroke:#1A7595
class f2,f files
classDef stages fill:#ffffff,stroke:#cc0000
class a1,a2 stages

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