bio-single-cell-metabolite-communication

MeboCost Overview

MeboCost infers metabolite-mediated communication by:

1. Predicting metabolite secretion from enzyme expression
2. Identifying metabolite-sensing receptors
3. Computing communication scores between cell types

Basic Workflow

Goal: Infer metabolite-mediated cell-cell communication from scRNA-seq data by predicting which cell types secrete and sense specific metabolites.

Approach: Initialize a MeboCost object from an AnnData with cell type annotations, run permutation-based communication inference to score metabolite secretion-sensing interactions, then filter for statistically significant pairs.

import mebocost as mbc
import scanpy as sc

## Initialize MeboCost

mebo = mbc.create_obj(
    adata=adata,
    group_col='cell_type',  # Cell type annotation column
    species='human'  # 'human' or 'mouse'
)