Method for quantifying amplitude of a response of a biological network
One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.
1. An article comprising a non-transitory tangible machine-readable medium that stores a program, the program being executable by a machine to perform a method comprising:
receiving a signature derived from a knowledge base of casual biological facts, where the signature is a collection of measured node entities and their expected directions of change with respect to a reference node; and
scoring one or more data sets against the signature to compute an amplitude score, wherein the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, where the adjustment applied to the log-fold changes is based on their expected direction of change;
wherein the amplitude score is generated according to the following function:
Strength
=
∑
i
direction
i
×
log
2
(
FC
i
)
N
where direction i and FC i represent expected direction of change and measured fold-change of an i th measured node entity, and N is a number of measured node entities in the signature.
2. An article comprising a non-transitory tangible machine-readable medium that stores a program, the program being executable by a machine to perform a method comprising:
receiving a signature derived from a knowledge base of casual biological facts, where the signature is a collection of measured node entities and their expected directions of change with respect to a reference node; and
scoring one or more data sets against the signature to compute an amplitude score, wherein the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, where the adjustment applied to the log-fold changes is based on their expected direction of change;
wherein the amplitude score is generated according to the following function:
Strength
(
f
)
=
∑
i
(
1
-
pval
i
)
f
×
direction
i
×
log
2
(
FC
i
)
∑
i
(
1
-
pval
i
)
f
wherein pval i is a p-value for FCi and f is a constant that controls the degree to which the influence each fold change is weighted according to its p-value.
3. The article as described in claim 2 wherein the knowledge base is a directed network of experimentally-observed causal relationships among biological entities and processes.
4. The article as described in claim 2 wherein the reference node represents a potential perturbation to a biological entity or process.
5. A non-transitory computer-readable storage medium storing a computer readable program of computer instructions, wherein the computer readable program when executed on a computer causes the computer to carry out the following operations:
receiving a signature that is a collection of measurable node entities and their expected directions of change with respect to a reference node; and
assessing a degree of activation of the signature by scoring one or more data sets against the signature to compute an amplitude score, where the amplitude score is computed from a differential data set, where the differential data set is a data set that has two conditions, a first condition, and a second condition;
wherein the first condition and the second condition are one of: a treated condition and a control condition, a disease condition and a non-diseased condition, a first disease condition and a second disease condition, a first patient population and a second patient population, a treatment with a first drug and the treatment with a second drug, a responder and a non-responder, pre- and post- drug treatment, pre- and post-development of a disease, and pre- and post-remission of a disease;
wherein scoring one or more data sets against the signature to compute the amplitude score uses the following function:
M
A
S
S
=
∑
i
direction
i
×
(
treated
i
-
control
i
)
∑
i
(
treated
i
-
control
i
)
2
where direction i represents expected direction of change of an i th measured node entity, treated i is a measurement for an i th measured node entity in a treated sample, and control i is a measurement for an i th measured node entity in a control sample.