nta

Run single-omic NTA (Network-topology based analysis) with edge list and list of starting analytes/nodes

Parameters

• edge_list - list[list[str]] of the network which is a list of lists where each entry is a node.
• analyte_list - list[str] of analytes for starting the NTA with.
• nta_method - a NTAMethod object specifying the NTA method for the analysis.
• n - the number of seeds or nodes to identify according to nta_method

Returns

Returns a dictionary object containing the candidates (seed nodes when using prioritization), scores (random-walk probabilities), and neighborhood (identified nodes)

Panics

Panics if the network or the analyte list is malformed or not at specified path. Will also panic if nta_method is not specified correctly

Example

import webgestaltpy

def file_to_list(file_path: str) -> list[str]:
    """Convert file to list[str]"""
    with open(file_path, "r") as r:
        return list(r.readlines())

def read_network(file_path: str) -> list[list[str]]:
    """Read .net file to format for nta()"""
    with open(file_path, "r") as r:
        lines = r.readlines()
    net = []
    for line in lines:
        if "\t" in line:
            net.append(line.split("\t"))
    return net

nta_method = webgestaltpy.NTAMethod.Prioritization
y = webgestaltpy.nta(read_network("data/hsapiens_network_CPTAC_Proteomics_OV_entrezgene.net"),
                     file_to_list("data/net_genes.txt"(), nta_method, 5)
print(y)

Output

{
  'candidates': [
    'ACTA1',
    'ACTA2',
    'ACTB',
    'ACTG1'
  ],
  'scores': [
    0.015611545101449542,
    0.015611545101449542,
    0.015227515228472441,
    0.015227515228472441,
    0.015105514420304793
  ],
  'neighborhood': [
    'ACTA1',
    'ACTA2',
    'ACTB',
    'ACTG1',
    'ACTG2'
  ]
}