What is Biexponential transformation?
Biexponential scaling helps visualize data that is compressed against the low x- and y- axes. Specifically, they address the problem of how to visualize high dynamic range data that contains both negative and positive values. For a more general overview on transforms, go here.
What is the advantage of a biexponential scale?
By applying a biexponential transform to the data, the scale is compressed in the lower range, typically from 1-10 or 1-100, leading to a more accurate visual representation of fluorescence units in the low range of the scale as compared to the higher range of the scale.
What is Arcsinh transformation?
The hyperbolic arcsine (arcsinh) is a function used in Cytobank for transforming data. It serves a similar purpose as transformation functions such as biexponential, logicle, hyperlog, etc. For values beyond the scale argument, data are displayed in a log-like fashion.
What is Biexponential analysis?
A biexponential fluorescence decay model is normally used to analyze FLIM-FRET data, where a measured lifetime at a given image pixel is assumed to be composed of two different lifetime components: one with FRET and the other without FRET [21], [22].
How do you represent flow cytometry data?
Flow cytometry data is typically represented in one of two ways: histograms, which measure or compare only a single parameter, and dot-plots which compare 2 or 3 parameters simultaneously on a two- or three-dimensional scatter-plot.
What is a transformed scale?
Scale transformations refer to transformations made directly on the numerical data of your dataset, for example conversions from the natural scale to a logarithmic scale, or a radial co-ordinate system. These should take place before statistical transformations.
What does negative MFI mean?
Negative values mean that the equipment s not well calibrated perhaps control antibodies are not appropriate. You may eventually move the axis to the left. The answer is given by assuming that your cells have the marker you are looking for.
What is the inverse hyperbolic sine function?
The hyperbolic sine function, sinhx, is one-to-one, and therefore has a well-defined inverse, sinh−1x, shown in blue in the figure. This function is shown in red in the figure; notice that cosh−1x is defined only for x 1 (at least where real numbers are concerned). …
What is flow cytometry Slideshare?
• Flow cytometry is a technique used to detect and measure physical and chemical characteristics of a population of cells or particles • A sample containing cells or particles is suspended in a fluid and injected into the flow cytometer instrument.
What can flow cytometry measure?
Cytometry, in its purest form, is the measurement of cell characteristics, which can include cell size, cell count, cell cycle and more. This technique allows researchers to get highly specific information about individual cells.
Why are scale transformations made?
The manipulation of scale variables to ensure comparability with other scales and enable comparisons to be made. The most frequently used scale transformation procedure is standardization.
Is scaling the same as transformation?
Scaling is a linear transformation, and a special case of homothetic transformation (scaling about a point). In most cases, the homothetic transformations are non-linear transformations.
What is the biexponential transformation In FlowJo?
For an explanation on benefits, go here. The method used to address this challenge in FlowJo is called biexponential transformation. It’s primary purpose is to provide display settings that are, in effect, a hybridization of linear and log scaling technique. For low magnitude values (around 0), the scaling is displayed as if it were linear.
Why use a biexponential display transformation?
Hence, using a biexponential transformation provides a more precise visualization tool when comparing populations with low fluorescence versus those with high fluorescence, as opposed to a standard log scale. In the images below, data is shown before and after the application of the display transformation.
What is biexponential scaling and how does it work?
Biexponential scaling helps visualize data that is compressed against the low x- and y- axes. “Squished” data is easily viewed by adding a section of linear scale to log acquired data.
What is the difference between biexponential transformation and standard log scale?
Traditionally, without biexponential transformation, after background fluorescence subtraction and the introduction of compensation error, data points may have negative fluorescence. In a standard log scale, there is no zero and no negative, so data is ‘piled-up’ on the axis in the first channel.