geomux 0.4.1

A tool to assign identifiers to cell barcodes

geomux

A tool that assigns guides to cell barcodes.

Uses a hypergeometric distribution to calculate the pvalue of observing the specific count of a guide for each guide in each barcode. This can be used to calculate the MOI of the cell and assigned guides for each cell. The resulting dataframe can then be used to intersect with your original data to assign every cell to a barcode and allows you to filter for the MOI you're interested in working with.

Installation

geomux is distributed via uv

uv tool install geomux
geomux --help

Usage

Geomux can be used either as a commandline tool or as a python module

Commandline

when installing via uv, an executable will be placed in your bin path. So you can call it directly from wherever in your filesystem

# example usage
geomux <input.tab / input.h5ad>

You can also run the help flag to see the help menu for parameter options.

$ geomux --help

Usage: geomux [OPTIONS] INPUT [OUTPUT]

╭─ Arguments ──────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ *    input       TEXT      Input file path (tsv/h5ad) to assign guides. [default: None] [required]                   │
│      output      [OUTPUT]  Output file path (tsv) to save assignments. [default: geomux.tsv]                         │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Options ────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --min-umi                 INTEGER  Minimum UMI count to consider a barcode [default: 5]                              │
│ --min-cells               INTEGER  Minimum number of barcodes to consider a guide [default: 100]                     │
│ --pvalue-threshold        FLOAT    Maximum pvalue (fdr) to consider a guide-assignment [default: 0.05]               │
│ --lor-threshold           FLOAT    Log odds ratio threshold to use [default: 10.0]                                   │
│ --correction              TEXT     Pvalue correction method to use [default: bh]                                     │
│ --n-jobs                  INTEGER  Number of jobs to use when calculating hypergeometric distributions [default: 1]  │
│ --help                             Show this message and exit.                                                       │
╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Python Module

Processing an h5ad file format

import anndata as ad
from geomux import Geomux

input = "filename.h5ad"

adata = ad.read_h5ad(input)
gx = Geomux(adata)
gx.test()
assignments = gx.assignments

Processing a 3-column TSV of [barcode, guide, n_umi]

from geomux import Geomux, read_table

input = "filename.tsv"

matrix = read_table(input)
gx = Geomux(
    matrix,
    cell_names=matrix.index.values,
    guide_names=matrix.columns.values,
)
gx.test()
assignments = gx.assignments()

Outputs

The results of geomux will be an assignment dataframe that has as many observations as there are input cells.

The columns of this dataframe will include:

Column Name	Description
cell_id	The name of the cell provided or the index.
assignment	A list representing all significant guides within that cell.
counts	The number of UMIs observed in the cell.
pvalues	The adjusted p-value of the hypergeometric test for that cell/guide test.
log_odds	The log odds of observing the highest scoring guide compared to the second highest.
moi	The number of significant guides within the cell.
n_umi	The number of UMIs observed in the cell.
min_pvalue	The minimum pvalue across all significant guides within the cell.
max_count	The maximum count across all significant guides within the cell.
tested	A bool flag representing whether the cell was included in the test (or False if it was filtered for low UMI counts)