-
Notifications
You must be signed in to change notification settings - Fork 5
Code documentation
Follow the links below to view documentation on each of the scripts for running WExT.
- Process mutations (
process_mutations.py) - Permute mutation data and compute mutation probabilities (
compute_mutation_probabilities.py) -
Find exclusive sets (
find_exclusive_sets.py) or find sets (find_sets.py)
We strive to make it easy to compute the weighted-row exclusivity (WR-exclusivity) test with WExT, or the row-exclusivity (RE-exclusivity) test with CoMEt in your own Python scripts. We provide documentation of the interface for computing the WR-exclusivity or RE-exclusivity tests, as well as an example, below.
WExT's wre_test computes the WR-exclusivity p-value exactly or with the saddlepoint approximation.
wre_test(t, x, p, method=EXACT, verbose=0)
| Parameter | Required (Default) | Description |
|---|---|---|
| t | True | Number of samples with an exclusive mutation. |
| x | True | List of length k number of mutated samples per gene. |
| p | True | k nested lists of length N with the per gene, per patient mutation probabilities. |
| method | False (EXACT) |
The method (EXACT or SADDLEPOINT) used to compute the p-value. |
| verbose | False (0) |
Flag verbose output. |
The re_test computes the p-value exactly (with CoMEt's tail enumeration procedure) or with the saddlepoint approximation.
re_test(t, x, tbl, method=EXACT, verbose=0)
| Parameter | Required (Default) | Description |
|---|---|---|
| t | True | Number of samples with an exclusive mutation. |
| x | True | List of length k number of mutated samples per gene. |
| tbl | True | List representing a flattened contingency table. |
| method | False (EXACT) |
The method (EXACT or SADDLEPOINT) used to compute the p-value. |
| verbose | False (0) |
Flag verbose output. |
WExT's general_wre_test computes the WR p-value with for various test statistics, including exclusivity, using the saddlepoint approximation.
general_wre_test(gene_set, geneToCases, p, condition, verbose=0)
| Parameter | Required (Default) | Description |
|---|---|---|
| gene_set | True | List of genes. |
| geneToCases | True | Dictionary with mutated samples for each gene in gene set. |
| p | True | k nested lists of length N with the per gene, per patient mutation probabilities. |
| condition | True | The test statistic (EXCLUSIVITY, ANY_CO_OCCURRENCE, ALL_CO_OCCURRENCE, or user defined) used to compute the p-value. |
| verbose | False (0) |
Flag verbose output. |
In this code example, we compute the weighted (WExT) and unweighted (CoMEt) tests directly.
# Load required modules
from wext import wre_test, re_test, SADDLEPOINT, EXACT
import numpy as np
# Hard-code data and generate random mutation probabilities
N = 100
k = 3
T = 54
X = [ 29, 26, 19 ]
tbl = [ 35, 22, 17, 5, 15, 0, 2, 2 ]
P = np.random.rand(k, N)
# Compute the saddlepoint approximation of WExT
wre_test( T, X, P, method=EXACT )
wre_test( T, X, P, method=SADDLEPOINT )
# Compute the exact and saddlepoint approximation of CoMEt
re_test( T, X, tbl, method=SADDLEPOINT )
re_test( T, X, tbl, method=EXACT )
Last modified: 1:43 PM Tuesday, Jan 2, 2017 (EST)