Description Usage Arguments Value Note Examples

View source: R/functions_evaluation.R

We partition the correlation matrix into 10x10 bins of equal size, with genes ordered according to expression level. As reference bin, we choose the (9,9) bin (ie. the almost-highest expressed genes). We then make a QQ-plot of the (i,j)'th submatrix vs. the (9,9) submatrix. See the SpQN paper for detail on these choices.

1 | ```
qqplot_condition_exp(cor_mat,ave_exp, i,j)
``` |

`cor_mat` |
Matrix, correlation matrix, generated by gene expression matrix. |

`ave_exp` |
Vector, average expression level of each gene for the normalized expression matrix. |

`i` |
Integer, row number of the submatrix (see details). |

`j` |
Integer, column number of the submatrix (see details). |

Invoked for the side effect of producing a plot.

The mnemonic for `condition_exp`

is â€˜conditional on
expressionâ€™.

1 2 3 4 5 6 |

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