The present invention provides an approach for the determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, expression markers and other criteria, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties. In addition, the use of modulators of cellular activation allows for characterization of pathways and cell populations. Several exemplary diseases that can be analyzed using the invention include AML, MDS, and MPN.

Methods for Diagnosis, Prognosis and Methods of Treatment

The present invention provides an approach for the simultaneous determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties. In addition, the use of potentiators of cellular activation allows for characterization of such pathways and cell populations.

Methods and compositions for risk stratification

The invention provides systems, compositions, kits and methods for automated processing of biological samples and analysis using a flow cytometer.

High throughput flow cytometry system and method

A set of data points is divided into a plurality of subsets of data points. A set of cluster closures is generated based at least in part on the subset of data points. Each cluster closure envelopes a corresponding cluster of a set of clusters and is comprised of data points of the enveloped cluster and data points neighboring the enveloped cluster. A k-Means approximator iteratively assigns data points to a cluster of the set of clusters and updates a set of cluster centroids corresponding to the set of clusters. The k-Means approximator assigns data points based at least in part on the set of cluster closures.

Approximate K-means via cluster closures

In one embodiment, a method includes sending an indicator of an availability of a sample from a sample pool stored in a physical inventory. The sample being included in the sample pool based on an attribute of the sample satisfying a condition associated with the sample pool. An indicator that the sample has been selected from the sample pool for analysis at a first test site included in an array of test sites is received. A rule is retrieved from a rule database based on an experimental parameter value associated with the first test site. At least one of the experimental parameter value associated with the first test site or an experimental parameter value associated with a second test site is modified based on a condition within the rule being satisfied.

Methods and apparatus related to management of experiments

In one embodiment, one or more processor-readable media storing code representing instructions that when executed by one or more processors cause the one or more processors to receive a set of parameter values defining a boundary within a data space associated with a dataset. The dataset can represent signaling related to a test substance. A first metric can be defined based on a first portion of the dataset associated with a first region defined by the boundary. A second metric can be defined based on a second portion of the dataset associated with a second region defined by the boundary after the boundary is modified. The second region can be different than the first region.

Methods and apparatus related to gate boundaries within a data space

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Methods and apparatus related to gate boundaries within a data space