Description Usage Arguments Value Author(s) See Also Examples

View source: R/combineBlocks.R

Combine DataFrames of statistics computed separately for each block. This usually refers to feature-level statistics and sample-level blocks.

1 2 3 4 5 6 7 8 9 10 | ```
combineBlocks(
blocks,
ave.fields,
pval.field,
method,
geometric,
equiweight,
weights,
valid
)
``` |

`blocks` |
A list of DataFrames containing blockwise statistics. These should have the same number of rows and the same set of columns. |

`ave.fields` |
Character vector specifying the columns of |

`pval.field` |
String specifying the column of |

`method` |
String specifying how p-values should be combined, see |

`geometric` |
Logical scalar indicating whether the geometric mean should be computed when averaging |

`equiweight` |
Logical scalar indicating whether each block should be given equal weight. |

`weights` |
Numeric vector of length equal to |

`valid` |
Logical vector indicating whether each block is valid.
Invalid blocks are still stored in the |

A DataFrame containing all fields in `ave.fields`

and the p-values,
where each column is created by combining the corresponding block-specific columns.
A `per.block`

column is also reported, containing a DataFrame of the DataFrames of blockwise statistics.

Aaron Lun

This function is used in `modelGeneVar`

and friends, `combineVar`

and `testLinearModel`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
library(scuttle)
sce <- mockSCE()
y1 <- sce[,1:100]
y1 <- logNormCounts(y1) # normalize separately after subsetting.
results1 <- modelGeneVar(y1)
y2 <- sce[,1:100 + 100]
y2 <- logNormCounts(y2) # normalize separately after subsetting.
results2 <- modelGeneVar(y2)
# A manual implementation of combineVar:
combineBlocks(list(results1, results2),
ave.fields=c("mean", "total", "bio", "tech"),
pval.field='p.value',
method='fisher',
geometric=FALSE,
equiweight=TRUE,
weights=NULL,
valid=c(TRUE, TRUE))
``` |

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