![]() When calculating the cosine similarity of two fluorochromes, the component values of the vectors cannot be negative, in which case the cosine similarity is bounded in . The cosine similarity always belongs to the interval . For example, two proportional vectors have a cosine similarity of 1, two orthogonal vectors have a similarity of 0, and two opposite vectors have a similarity of -1. It follows that the cosine similarity does not depend on the magnitudes of the vectors, but only on their angle. That is, it is the dot product of the vectors divided by the product of their lengths. Cosine similarity is the cosine of the angle between the vectors. The CSM can be visualized and/or exported from the Compensation Matrix Preview/Edit window as shown below.Ĭosine similarity is a measure of similarity between two non-zero vectors defined in an inner product space. Once spectral compensation has been performed, the results can be previewed and applied to samples in much the same way standard compensation is treated.In FlowJo 10.9.0 and later, a cosine similarity matrix (CSM) is automatically created when a compensation matrix is calculated in the compensation wizard. As of FlowJo v10.10 an alternate optimization approach called SpectralFX is available for data from specific BD cytometers. Note: Because of the immense amount of computation required for this optimization feature, it can take up to 30 minutes to complete. ![]() Running the Optimize Weights function for spectral compensation will utilize currently selected compensation control populations to compare hypothetical spillover spreading matrices (SSM) for different weights and adjust those weights to minimize the SSM. Samples used for primary detectors also help to name those parameters after spectral compensation. Once that assignment is confirmed and/or adjusted as necessary, you can click in the sample column to the left of an unused detector and choose “Remove Unused Parameters” to quickly trim away non-primary channels. FlowJo will try to automatically assign the proper control sample to its respective detector. When first running spectral compensation, researchers are prompted to choose their primary detectors – We generally recommend selecting all detectors to start with. The primary control samples are used for parameter naming. Using spectral compensation means that signal from non-primary detectors are still used to enhance the true signal of markers where possible. Fluorochromes used for compensation need to be the same fluorochromes used for the experimental samples.Īlso, there should be no single stained control samples or rows used for the extra detectors, as there should be no fluorescent marker for those overdetermining channels included in the experiment.The positive and negative populations for a channel need to have the same autofluorescence (e.g., Beads must be paired with beads and cells with cells, in terms of negative and positive control population pairs).Positive controls must be at least as bright as the experimental sample’s positive signal.The same basic rules of compensation apply in spectral as in standard compensation: Just like standard compensation, researchers will need to select their single-stained control samples for each probe of interest, as well as the negative and positive control populations for each single stained control. To utilize spectral compensation, you will first need data that contains more detectors than fluorescent probes (an overdetermined system) and corresponding single stained controls for each of those parameters. Alongside that check-box are options to choose weights per fluorescence detector and to optimize the weighting used. Beginning in FlowJo v10.6 there is now a check-box labelled Spectral at the top of the compensation wizard to enable spectral compensation functionality.
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