get_coincident_foci {synapsis} | R Documentation

## get_coincident_foci

### Description

calculates the statistic to compare to crisp_criteria, which determines whether the foci count will be reliable

### Usage

    get_coincident_foci(
      offset_px,
      offset_factor,
      brush_size,
      brush_sigma,
      annotation,
      watershed_stop,
      watershed_radius,
      watershed_tol,
      crowded_foci,
      artificial_amp_factor,
      strand_amp,
      disc_size,
      disc_size_foci,
      img_file,
      cell_count,
      img_orig,
      img_orig_foci,
      stage,
      WT_str,
      KO_str,
      WT_out,
      KO_out,
      C1_search,
      discrepant_category,
      C1,
      C2,
      df_cells,
      C_weigh_foci_number
    )

### Arguments

`offset_px,` | Pixel value offset used in thresholding of synaptonemal complex channel
`offset_factor,` | Pixel value offset used in thresholding of foci channel
`brush_size,` | size of brush to smooth the foci channel. Should be small to avoid erasing foci.
`brush_sigma,` | sigma for Gaussian smooth of foci channel. Should be small to avoid erasing foci.
`annotation,` | Choice to output pipeline choices (recommended to knit)
`watershed_stop` | Stop default watershed method with "on"
`watershed_radius` | Radius (ext variable) in watershed method used in foci channel. Defaults to 1 (small)
`watershed_tol` | Intensity tolerance for watershed method. Defaults to 0.05.
`crowded_foci` | TRUE or FALSE, defaults to FALSE. Set to TRUE if you have foci > 100 or so.
`artificial_amp_factor` | Amplification of foci channel, for annotation only.
`strand_amp` | multiplication of strand channel to make masks
`disc_size` | size of disc for local background calculation in synaptonemal complex channel
`disc_size_foci` | size of disc for local background calculation in foci channel
`img_file` | cell's file name
`cell_count` | unique cell counter
`img_orig` | original strand crop
`img_orig_foci` | cropped foci channel
`stage,` | meiosis stage of interest. Currently count_foci determines this with thresholding/ object properties in the synaptonemal complex channel by previosly calling the get_pachytene function. Note that if using this option, the count_foci function requires that the input directory contains a folder called “pachytene” with the crops in it.
`WT_str` | string in filename corresponding to wildtype genotype. Defaults to ++.
`KO_str` | string in filename corresponding to knockout genotype. Defaults to –.
`WT_out` | string in output csv in genotype column, for knockout. Defaults to +/+.
`KO_out` | string in output csv in genotype column, for knockout. Defaults to -/-.
`C1_search` | TRUE or FALSE whether the image is still being modified until it meets the crispness criteria
`discrepant_category` | estimated number of foci that are NOT on a strand.
`C1` | Default crispness criteria = sd(foci_area)/(mean(foci_area)+1)
`C2` | Alternative crisp criteria.
`df_cells` | current data frame
`C_weigh_foci_number` | choose crispness criteria- defaults to TRUE to use C1 (weighing with number). Otherwise set to FALSE to use C2

### Value

data frame with new row with most recent foci per cell appended

[Package synapsis version 1.0.0 Index]