Description Usage Arguments Format Details Value Examples

Most of these functions are called internally by plotting functions, but are exported in case the user finds them useful.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
makeBlankData(data, groupsOfFeatures, nBlankLines = 1)
showBigPalette(wh = NULL)
setBreaks(data, breaks = NA, makeSymmetric = FALSE)
bigPalette
showHeatmapPalettes()
seqPal5
seqPal2
seqPal3
seqPal4
seqPal1
``` |

`data` |
matrix with samples on columns and features on rows. |

`groupsOfFeatures` |
list, with each element of the list containing a vector of numeric indices. |

`nBlankLines` |
the number of blank lines to add in the data matrix to separate the groups of indices (will govern the amount of white space if data is then fed to heatmap.) |

`wh` |
numeric. Which colors to plot. Must be a numeric vector with values between 1 and 62. |

`breaks` |
either vector of breaks, or number of breaks (integer) or a number between 0 and 1 indicating a quantile, between which evenly spaced breaks should be calculated. |

`makeSymmetric` |
whether to make the range of the breaks symmetric around zero (only used if not all of the data is non-positive and not all of the data is non-negative) |

An object of class `character`

of length 60.

`makeBlankData`

pulls the data corresponding to the row indices
in `groupsOfFeatures`

adds lines of NA values into data between these
groups. When given to heatmap, will create white space between these groups
of features.

`bigPalette`

is a long palette of colors (length 62) used by
`plotClusters`

and accompanying functions.
`showBigPalette`

creates plot that gives index of each color in
bigPalette.

`showBigPalette`

will plot the `bigPalette`

functions with
their labels and index.

`setBreaks`

gives a set of breaks (of length 52) equally spaced
between the boundaries of the data. If breaks is between 0 and 1, then the
evenly spaced breaks are between these quantiles of the data.

`seqPal1`

-`seqPal4`

are palettes for the heatmap.
`showHeatmapPalettes`

will show you these palettes.

`makeBlankData`

returns a list with items

"dataWBlanks" The data with the rows of NAs separating the given indices.

"rowNamesWBlanks" A vector of characters giving the rownames for the data, including blanks for the NA rows. These are not given as rownames to the returned data because they are not unique. However, they can be given to the

`labRow`

argument of`aheatmap`

or`plotHeatmap`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
data(simData)
x <- makeBlankData(simData[,1:10], groupsOfFeatures=list(c(5, 2, 3), c(20,
34, 25)))
showBigPalette()
setBreaks(data=simData,breaks=.9)
#show the palette colors
showHeatmapPalettes()
#compare the palettes on heatmap
cl <- clusterSingle(simData, clusterFunction="pam", subsample=FALSE,
sequential=FALSE, clusterDArgs=list(k=8))
## Not run:
par(mfrow=c(2,3))
plotHeatmap(cl, colorScale=seqPal1, main="seqPal1")
plotHeatmap(cl, colorScale=seqPal2, main="seqPal2")
plotHeatmap(cl, colorScale=seqPal3, main="seqPal3")
plotHeatmap(cl, colorScale=seqPal4, main="seqPal4")
plotHeatmap(cl, colorScale=seqPal5, main="seqPal5")
par(mfrow=c(1,1))
## End(Not run)
``` |

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