FlowHist {flowPloidy} | R Documentation

## FlowHist

### Description

Creates a `FlowHist` object from an FCS file, setting up the histogram data for analysis.

### Usage

    FlowHist(file, channel, bins = 256, analyze = TRUE,
      linearity = "variable", debris = "SC", samples = 2, pick = FALSE,
      standards = 0, g2 = TRUE, debrisLimit = 40, ...)

    batchFlowHist(files, channel, verbose = TRUE, ...)

### Arguments

`file` | character, the name of the single file to load
`channel` | character, the name of the data column to use
`bins` | integer, the number of bins to use to aggregate events into a histogram
`analyze` | logical, if TRUE the model will be analyzed immediately
`linearity` | character, either "variable", the default, or "fixed". If "fixed", linearity is fixed at 2; if "variable", linearity is fit as a model parameter.
`debris` | character, either "SC", the default, "MC", or "none", to set the debris model component to the Single-Cut or Multi-Cut models, or to not include a debris component (such as for gated data).
`samples` | integer; the number of samples in the data. Default is 2 (unknown and standard), but can be set to 3 if two standards are used, or up to 6 for endopolyploidy analysis.
`pick` | logical; if TRUE, the user will be prompted to select peaks to use for starting values. Otherwise (the default), starting values will be detected automatically.
`standards` | numeric; the size of the internal standard in pg. When loading a data set where different samples have different standards, a vector of all the standard sizes. If set to 0, calculation of pg for the unknown sample will not be done.
`g2` | a logical value, default is TRUE. Should G2 peaks be included in the model?
`debrisLimit` | an integer value, default is 40. Passed to `cleanPeaks`. Peaks with fluorescence values less than `debrisLimit` will be ignored by the automatic peak-finding algorithm. Used to ignore the debris often found at the left side of the histogram.
`...` | additional arguments passed from `batchFlowHist` to `FlowHist`, or to assorted helper functions. See `findPeaks` (arguments `window` and `smooth`)
`files` | character, a vector of file names to load, or a single character value giving the path to a directory; if the latter, all files in the directory will be loaded
`verbose` | logical; if TRUE, `batchFlowHist` will list files as it processes them.

### Details

For most uses, simpling calling `FlowHist` with a `file`, `channel`, and `standards` argument will do what you need. The other arguments are provided for optional tuning of this process. In practice, it's easier to correct the model fit using `browseFlowHist` than to determine 'perfect' values to pass in as arguments to `FlowHist`.

Similarly, `batchFlowHist` is usually used with only the `files`, `channel`, and `standards` arguments.

In operation, `FlowHist` starts by reading an FCS file (using the function `read.FCS` internally). This produces a `flowFrame` object, which we extend to a `FlowHist` object as follows:

1. Extract the fluorescence data from `channel`.

2. Remove the top bin, which contains off-scale readings we ignore in the analysis.

3. Remove negative fluorescence values, which are artifacts of instrument compensation

4. Removes the first 5 bins, which often contain noisy values, probably further artifacts of compensation.

5. aggregates the raw data into the desired number of bins, as specified with the `bins` argument. The default is 256, but you may also try 128 or 512. Any integer is technically acceptable, but I wouldn't stray from the default without a good reason. (I've never had a good reason!)

6. identify model components to include. All `FlowHist` objects will have the single-cut debris model and the G1 peak for sample A, and the broadened rectangle for the S-phase of sample A. Depending on the data, additional components for the G2 peak and sample B (G1, G2, s-phase) may also be added. The `debris` argument can be used to select the Multi-Cut debris model instead, or this can be toggled in `browseFlowHist`

7. Build the NLS model. All the components are combined into a single model.

8. Identify starting values for Gaussian (G1 and G2 peaks) model components. For reasonably clean data, the built-in peak detection is ok. You can evaluate this by plotting the `FlowHist` object with the argument `init = TRUE`. The easiest way to fix bad peak detection is via the `browseFlowHist` interface. You can also play with the `window` and `smooth` arguments (which is tedious!), or pick the peaks visually yourself with `pick = TRUE`.

9. Finally, we fit the model and calculate the fitted parameters. Model fitting is suppressed if the `analyze` argument is set as `FALSE`

### Value

`FlowHist` returns a `FlowHist` object.

`batchFlowHist` returns a list of `FlowHist` objects.

### Slots

`raw`

  a flowFrame object containing the raw data from the FCS file

`channel`

  character, the name of the data column to use

`bins`

  integer, the number of bins to use to aggregate events into a histogram

`linearity`

  character, either "fixed" or "variable" to indicate if linearity is fixed at 2 or fit as a model parameter

`debris`

  character, either "SC" or "MC" to indicate if the model should include the single-cut or multi-cut model

`gate`

  logical, a vector indicating events to exclude from the analysis. In normal use, the gate will be modified via interactive functions, not set directly by users.

`histdata`

  data.frame, the columns are the histogram bin number (xx), florescence intensity (intensity), and the raw single-cut and multi-cut debris model values (SCvals and MCvals), and the raw doublet, triplet and quadruplet aggregate values (DBvals, TRvals, and QDvals). The debris and aggregate values are used in the NLS fitting procedures.

`peaks`

  matrix, containing the coordinates used for peaks when calculcating initial parameter values.

`opts`

  list, currently unused. A convenient place to store flags when trying out new options.

`comps`

  a list of `ModelComponent` objects included for these data.

`model`

  the function (built from `comps`) to fit to these data.

`limits`

  list, a list of lower and upper bounds for model parameters

`init`

  a list of initial parameter estimates to use in fitting the model.

`nls`

  the nls object produced by the model fitting

`counts`

  a list of cells counted in each peak of the fitted model

`CV`

  a list of the coefficients of variation for each peak in the fitted model.

`RCS`

  numeric, the residual chi-square for the fitted model.

`samples`

  numeric, the number of samples included in the data. The default is 2 (i.e., unknown and standard), but if two standards are used it should be set to 3. It can be up to 6 for endopolyploidy analysis, and can be interactively increased (or decreased) via `browseFlowHist`

`standards`

  a `FlowStandards` object.

`g2`

  logical, if TRUE the model will include G2 peaks for each sample (as long as the G1 peak is less than half-way across the histogram). Set to FALSE to drop the G2 peaks for endopolyploidy analyses.

`annotation`

  character, user-added annotation for the sample.

`fail`

  logical, set by the user via the `browseFlowHist` interface to indicate the sample failed and no model fitting should be done.

### Author(s)

Tyler Smith

### Examples

    library(flowPloidyData)
    fh1 <- FlowHist(file = flowPloidyFiles()[1], channel = "FL3.INT.LIN")
    fh1
    batch1 <- batchFlowHist(flowPloidyFiles(), channel = "FL3.INT.LIN")
    batch1

[Package flowPloidy version 1.12.0 Index]