MERFISH MultiCSV DotPlot is a lightweight Python utility for generating dot-plot style summary figures from multiple MERFISH cell-by-gene CSV datasets and multiple selected genes. Each input CSV is represented as one column and each selected gene as one row. Dot size represents the fraction of cells with expression greater than a user-defined positive-cell threshold. Dot color can represent either absolute mean expression or per-gene relative mean expression scaled from 0 to 1 across the supplied datasets. The software accepts an arbitrary number of MERFISH CSV files and an arbitrary number of genes. It exports both publication-style figures and a long-format numerical summary table. Two color modes are available:- "absolute": dot color represents mean expression on the original input scale.- "gene_scaled": mean expression is independently scaled from 0 to 1 for each gene across the supplied datasets, emphasizing relative expression patterns between datasets. Positive cells are defined as:expression > positive_threshold The positive-cell threshold is explicitly specified by the user because appropriate thresholds depend on the expression scale and preprocessing of the input data. No automatic log/linear transformation is performed. Expression values are used exactly as supplied in the input CSV files.Input CSV format: Each CSV should contain one cell per row and gene-expression values in gene-named columns. Additional metadata or coordinate columns (e.g., cell ID, x, y, z, section information) may also be included. All genes selected for plotting must be present as numeric columns in every input CSV. The software was functionally validated using MERFISH-derived cell-by-gene datasets with multiple cell populations and genes. Expected qualitative differences between canonical D1- and D2-associated gene-expression patterns were reproduced during validation. No third-party MERFISH dataset is distributed with this software. Generative AI (ChatGPT, OpenAI) was used to assist with code generation, refinement, testing, packaging, and documentation. The concept, intended scientific use, validation, and final responsibility for the software remain with the author.
Sora Mitamura· Zenodo (CERN European Organi...· 0 citations
MERFISH MultiCSV DotPlot is a lightweight Python utility for generating dot-plot style summary figures from multiple MERFISH cell-by-gene CSV datasets and multiple selected genes. Each input CSV is represented as one column and each selected gene as one row. Dot size represents the fraction of cells with expression greater than a user-defined positive-cell threshold. Dot color can represent either absolute mean expression or per-gene relative mean expression scaled from 0 to 1 across the supplied datasets. The software accepts an arbitrary number of MERFISH CSV files and an arbitrary number of genes. It exports both publication-style figures and a long-format numerical summary table. Two color modes are available:- "absolute": dot color represents mean expression on the original input scale.- "gene_scaled": mean expression is independently scaled from 0 to 1 for each gene across the supplied datasets, emphasizing relative expression patterns between datasets. Positive cells are defined as:expression > positive_threshold The positive-cell threshold is explicitly specified by the user because appropriate thresholds depend on the expression scale and preprocessing of the input data. No automatic log/linear transformation is performed. Expression values are used exactly as supplied in the input CSV files.Input CSV format: Each CSV should contain one cell per row and gene-expression values in gene-named columns. Additional metadata or coordinate columns (e.g., cell ID, x, y, z, section information) may also be included. All genes selected for plotting must be present as numeric columns in every input CSV. The software was functionally validated using MERFISH-derived cell-by-gene datasets with multiple cell populations and genes. Expected qualitative differences between canonical D1- and D2-associated gene-expression patterns were reproduced during validation. No third-party MERFISH dataset is distributed with this software. Generative AI (ChatGPT, OpenAI) was used to assist with code generation, refinement, testing, packaging, and documentation. The concept, intended scientific use, validation, and final responsibility for the software remain with the author.
Sora Mitamura· Zenodo (CERN European Organi...· 0 citations