The mFISH Object

Author

Kaitlin Sullivan

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Video Tutorial

The following video tutorial demonstrates the structure of the formal mFISH class object.

Read below for code and a visual representation of the mFISH object’s structure.

Creating an mFISH Object with ruMake()

######### STEP 2: CREATE YOUR OBJECT #########
#take your individual section or combined dataset and turn it into an mFISH object for analysis

myobj <- ruMake(mydata)
[1] "Creating object..."
# Save your analysis object at any point using saveRDS()

saveRDS(myobj, 'demo.rds')

# Read it back in with readRDS()
# myobj <- readRDS('demo.rds')

mFISH Object Structure

The mFISH object contains four slots:

@rawData

This contains the original data frame, without metadata, from ruRead().

head(myobj@rawData)
       Nnat      Synpr      Pcp4    Slc17a7      Cdh9      Ctgf    Slc17a6 Lxn
1 0.1834896  0.0000000 5.5177946  0.0000000 0.7358308 0.3679154 0.73583077   0
2 0.0000000  0.0000000 0.0000000  0.0000000 2.1668655 0.0000000 2.16686552   0
3 0.0000000  0.0000000 0.0000000  0.6694704 0.0000000 0.0000000 1.00420555   0
4 0.0000000  0.2438931 0.4888655 13.1972094 0.2438931 0.4888655 0.73275862   0
5 0.1613582  0.2426580 0.8893321 38.7961045 0.3233371 0.3233371 0.08067912   0
6 0.0000000 12.5748426 0.0000000 23.0532699 0.0000000 0.0000000 0.00000000   0
    Slc30a3     Gfra1     Spon1      Gnb4 RSC LEC id
1 0.0000000 0.0000000 1.1037462 0.0000000   0   0  1
2 0.7216701 0.0000000 0.0000000 0.0000000   0   0  2
3 0.0000000 0.3347352 0.6694704 0.6694704   0   0  3
4 0.0000000 0.0000000 0.0000000 0.0000000   0   0  4
5 0.4040162 0.0000000 3.1520710 2.0207016   0   0  5
6 0.0000000 1.3976102 0.0000000 0.0000000   0   0  6

@filteredData

This contains a data frame of the normalized and filtered data from downstream analysis.

For now this is empty, however this slot will be populated automatically during analysis with the goFISH Shiny app or generated via ruFilter() and ruProcess()).

head(myobj@filteredData)
data frame with 0 columns and 0 rows

@metaData

This contains a data frame of all the metadata from the initial ruRead() data frame.

head(myobj@rawData)
       Nnat      Synpr      Pcp4    Slc17a7      Cdh9      Ctgf    Slc17a6 Lxn
1 0.1834896  0.0000000 5.5177946  0.0000000 0.7358308 0.3679154 0.73583077   0
2 0.0000000  0.0000000 0.0000000  0.0000000 2.1668655 0.0000000 2.16686552   0
3 0.0000000  0.0000000 0.0000000  0.6694704 0.0000000 0.0000000 1.00420555   0
4 0.0000000  0.2438931 0.4888655 13.1972094 0.2438931 0.4888655 0.73275862   0
5 0.1613582  0.2426580 0.8893321 38.7961045 0.3233371 0.3233371 0.08067912   0
6 0.0000000 12.5748426 0.0000000 23.0532699 0.0000000 0.0000000 0.00000000   0
    Slc30a3     Gfra1     Spon1      Gnb4 RSC LEC id
1 0.0000000 0.0000000 1.1037462 0.0000000   0   0  1
2 0.7216701 0.0000000 0.0000000 0.0000000   0   0  2
3 0.0000000 0.3347352 0.6694704 0.6694704   0   0  3
4 0.0000000 0.0000000 0.0000000 0.0000000   0   0  4
5 0.4040162 0.0000000 3.1520710 2.0207016   0   0  5
6 0.0000000 1.3976102 0.0000000 0.0000000   0   0  6

@attributes

This contains a list of all the important variables used throughout analysis to assist with code reproducibility.

head(myobj@attributes)
$filter.by
[1] NA

$thresh
[1] NA

$umap_nn
[1] NA

$umap_mindist
[1] NA

$umap_metric
[1] NA

$hclust_k
[1] NA

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