atn 0.0.2

A/T/N staging for Alzheimer's Disease based on CSF biomarkers

atn

Based on the A/T/N/ classification scheme for Alzheimer's disease biomarkers Jack et al., 2016, what this Python module does is basically applying predefined thresholds to a given DataFrame (containing biomarker data such as cerebrospinal fluid (CSF) levels of ABeta42, ptau, ttau) and building multiple lists of subjects with distinct profiles according to their CSF biomarkers.

Example (with random data):

import random
n = 10

abeta42 = [random.randrange(600e3, 1800e3)/1e3 for e in range(0, n)]
ptau = [random.randrange(4e3, 80e3)/1e3 for e in range(0, n)]
ttau = [random.randrange(97e3, 500e3)/1e3 for e in range(0, n)]
data = pd.DataFrame(data=[abeta42, ptau, ttau], index=['abeta42', 'ptau', 'ttau']).transpose()
data

	abeta42	ptau	ttau
0	1142.327	76.636	375.448
1	833.484	77.321	181.75
2	951.601	6.981	309.215
3	1623.797	65.063	232.303
4	920.706	62.899	310.1
5	704.215	58.526	160.826
6	1687.357	53.335	422.249
7	1701.997	68.676	173.33
8	1774.046	37.214	255.638
9	939.946	21.128	164.803

import atn
staging = atn.stage(data, thresholds = {'abeta42':1100, 'ptau':19.2, 'ttau':242})
staging

	A	T	N
ID
0	FALSE	TRUE	TRUE
1	TRUE	TRUE	FALSE
2	TRUE	FALSE	TRUE
3	FALSE	TRUE	FALSE
4	TRUE	TRUE	TRUE
5	TRUE	TRUE	FALSE
6	FALSE	TRUE	TRUE
7	FALSE	TRUE	FALSE
8	FALSE	TRUE	TRUE
9	TRUE	TRUE	FALSE

print(atn.staging_summary(staging))

CSF amyloid (A) positive/negative: 5/5 CSF ptau (T) positive/negative: 9/1 CSF ttau (N) positive/negative: 5/5

A+T+: 4 A+T-: 1 A-T-: 0 A-T+ (SNAPs): 5

A+T+N+: 1 A+T+N-: 3 A-T+N+: 3 A-T+N-: 2 A-T-N-: 0 A-T-N+: 0 Total subjects: 10

So yes, it is simple, stupid. But this allows one to quickly select groups of subjects as follows:

groups = atn.groups(staging)
data.loc[groups['A+'].index]

	abeta42	ptau	ttau
ID
1	833.484	77.321	181.75
2	951.601	6.981	309.215
4	920.706	62.899	310.1
5	704.215	58.526	160.826
9	939.946	21.128	164.803

Dependencies

• Python >= 3.5
• Pandas >= 0.24.1

Install

First make sure you have installed all the dependencies listed above. Then you can install atn by running the following command in a command prompt:

pip install atn