superexacttestpy.tl.supertest
- superexacttestpy.tl.supertest(data, n, names=[], degree=-1, lower_tail=True)
Calculate the supertest for a given data set
- Parameters:
- data : list
The data set to use
- n : int
The number of background-size
- names : list
The list of names to use
- degree : int
The degree of the barcode (if -1, no degree selection)
- lower_tail : bool
If True, the probability is P[overlap < m], otherwise, P[overlap >= m], where m is the number of elements shared by all sets.
- Returns:
A dataframe with all the information computed by the supertest
- Return type:
pd.DataFrame
Example
>>> data = [["A","B","C","D","E","F","G","H","I","J","K","L","M","N","O","P","Q"], ["L","M","N","O","P","Q","R","S","T","U","V","W","X","Y","Z"], ["H","I","J","K","L","M","N","O","P","Q"]] >>> supertest(data, n=100,degree=-1, names=["First","Second","Third"], lower_tail=False) ... | | intersection | degree | observed_overlap | expected_overlap | fold_enrichment | p_value | elements | ... |----:|:-----------------------|---------:|-------------------:|-------------------:|------------------:|-----------:|:--------------------------------------------------| ... | 001 | Third | 1 | 10 | nan | nan | nan | H, I, J, K, L, M, N, O, P, Q | ... | 010 | Second | 1 | 15 | nan | nan | nan | L, M, N, O, P, Q, R, S, T, U, V, W, X, Y, Z | ... | 011 | Second & Third | 2 | 6 | 1.5 | 4 | 0.999415 | L, M, N, O, P, Q | ... | 100 | First | 1 | 17 | nan | nan | nan | A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q | ... | 101 | First & Third | 2 | 10 | 1.7 | 5.88235 | 1 | H, I, J, K, L, M, N, O, P, Q | ... | 110 | First & Second | 2 | 6 | 2.55 | 2.35294 | 0.983943 | L, M, N, O, P, Q | ... | 111 | First & Second & Third | 3 | 6 | 0.255 | 23.5294 | 1 | L, M, N, O, P, Q |