Package 'LISTO'

Build a Seurat marker list ready to be used by LISTO

Description

This function builds a Seurat marker list ready to be used by LISTO. Requires Seurat (not automatically installed with LISTO).

Usage

buildSeuratMarkerList(seuratObj, col, logFCThr = 1, minPct = 0.2, ...)

Arguments

seuratObj	A Seurat object.
col	Seurat metadata column used for grouping.
logFCThr	Fold change threshold for testing.
minPct	The minimum fraction of in-cluster cells in which tested genes need to be expressed.
...	Additional arguments passed to Seurat::FindMarkers.

Value

A list consisting of data frames generated with Seurat::FindMarkers.

Examples

seuratPath <- system.file('extdata', 'seuratObj.qs2', package='LISTO')
seuratObj <- qs2::qs_read(seuratPath)
a <- buildSeuratMarkerList(seuratObj, 'Cell_Cycle', logFCThr=0.1)

---

Generate the prime factor decomposition of n factorial.

Description

This function generates the prime factor decomposition of n factorial.

Usage

factorialPrimePowers(n)

Arguments

n	A positive integer.

Value

A vector in which positions represent prime numbers (that is, the first position corresponds to 2, the second position corresponds to 3, the third position corresponds to 5, etc.) and values represent their exponents in the factorial decomposition.

Examples

factorialPrimePowers(8)

---

Perform multiple testing correction on a data frame column

Description

This function orders a data frame based on a column of p-values, performs multiple testing on the column, and filters the data-frame based on it.

Usage

mtCorrectDF(
  df,
  mtMethod = c("BY", "holm", "hochberg", "hommel", "bonferroni", "BH", "fdr", "none"),
  colStr = "pval",
  newColStr = "pvalAdj",
  pvalThr = 0.05,
  doOrder = TRUE,
  nComp = nrow(df)
)

Arguments

df	A data frame with a p-values column.
mtMethod	Multiple testing correction method. Choices are 'BY' (default), 'holm', hochberg', hommel', 'bonferroni', 'BH', 'fdr' and 'none'.
colStr	Name of the column of p-values.
newColStr	Name of the column of adjusted p-values that will be created.
pvalThr	p-value threshold used for filtering. If NULL, no filtering will be performed.
doOrder	Whether to increasingly order the data frame based on the adjusted p-values.
nComp	Number of comparisons. In most situations, this parameter should not be changed.

Value

A data frame with the p-value column corrected for multiple testing.

Examples

df <- data.frame(elem = c('A', 'B', 'C', 'D', 'E'),
pval = c(0.032, 0.001, 0.0045, 0.051, 0.048))
mtCorrectDF(df)

---

Perform multiple testing correction on a vector of p-values

Description

This function performs multiple testing correction on a vector of p-values.

Usage

mtCorrectV(
  pvals,
  mtMethod = c("BY", "holm", "hochberg", "hommel", "bonferroni", "BH", "fdr", "none"),
  mtStat = c("identity", "median", "mean", "max", "min"),
  nComp = length(pvals)
)

Arguments

pvals	A numeric vector.
mtMethod	Multiple testing correction method. Choices are 'BY' (default), 'holm', hochberg', hommel', 'bonferroni', 'BH', 'fdr' and 'none'.
mtStat	A statistics to be optionally computed. Choices are 'identity' (no statistics will be computed and the adjusted p-values will be returned as such), 'median', 'mean', 'max' and 'min'.
nComp	Number of comparisons. In most situations, this parameter should not be changed.

Value

If mtStat is 'identity' (as default), a numeric vector of p-values corrected for multiple testing. Otherwise, a statistic based on these corrected p-values defined by mtStat.

Examples

pvals <- c(0.032, 0.001, 0.0045, 0.051, 0.048)
mtCorrectV(pvals)

---

Compute the probability that two subsets of sets M and N intersect in k points

Description

This function computes the probability that two subsets of sets M and N intersect in k points. Intersection sizes (M with N, A with N and B with M) must be provided.

Usage

probCounts2MN(intMN, intAN, intBM, k)

Arguments

intMN	Number of elements in the intersection of sets M and N.
intAN	Number of elements in the intersection of sets A (subset of M) and N.
intBM	Number of elements in the intersection of sets B (subset of N) and M.
k	Number of elements in the intersection of sets A and B.

Value

A numeric value in [0, 1] representing the probability that two subsets of sets M and N intersect in k points.

Examples

probCounts2MN(8, 6, 4, 2)

---

Compute the probability that three subsets of given sizes intersect in k points

Description

This function computes the probability that three subsets of given sizes intersect in k points.

Usage

probCounts3N(a, b, c, n, k)

Arguments

a	Size of the first subset.
b	Size of the second subset.
c	Size of the third subset.
n	Size of the set.
k	Size of the intersection.

Value

A numeric value in [0, 1] representing the probability that three subsets of given sizes intersect in k points.

Examples

probCounts3N(8, 6, 10, 20, 3)

---

Compute the probability that two subsets of sets M and N intersect in at least k points

Description

This function computes the probability that two subsets A and B of sets M and N intersect in at least k points.

Usage

pvalCounts2MN(intMN, intAN, intBM, k)

Arguments

intMN	Number of elements in the intersection of sets M and N.
intAN	Number of elements in the intersection of sets A (subset of M) and N.
intBM	Number of elements in the intersection of sets B (subset of N) and M.
k	Number of elements in the intersection of sets A and B.

Value

A numeric value in [0, 1] representing the probability that two subsets of sets M and N intersect in at least k points.

Examples

pvalCounts2MN (300, 23, 24, 6)

---

Compute the probability that three subsets of a set intersect in at least k points

Description

This function computes the probability that three subsets of a set intersect in at least k points.

Usage

pvalCounts3N(lenA, lenB, lenC, n, k)

Arguments

lenA	Size of the first subset.
lenB	Size of the second subset.
lenC	Size of the third subset.
n	Size of the set comprising the subsets.
k	Size of the intersection.

Value

A numeric value in [0, 1] representing the probability that three subsets of a set intersect in at least k points.

Examples

pvalCounts3N (300, 200, 250, 400, 180)

---

Assess the overlap of two or three objects

Description

This function assesses the statistical significance of the overlap of two or three objects (character vectors, or data frames having a numeric column).

Usage

pvalObjects(
  obj1,
  obj2,
  obj3 = NULL,
  universe1,
  universe2 = NULL,
  numCol = NULL,
  isHighTop = TRUE,
  maxCutoffs = 500,
  mtMethod = c("BY", "holm", "hochberg", "hommel", "bonferroni", "BH", "fdr", "none"),
  nCores = 1,
  type = c("2N", "2MN", "3N")
)

Arguments

obj1	Either 1) a data frame having items as row names and a numeric column or 2) a character vector.
obj2	Either 1) a data frame having items as row names and a numeric column or 2) a character vector.
obj3	Either 1) a data frame having items as row names and a numeric column or 2) a character vector.
universe1	The set from which the items stored in obj1 are selected.
universe2	The set from which the items stored in obj2 are selected.
numCol	The name of the numeric column used for data frame ordering.
isHighTop	Whether higher values in the numeric column correspond to better-ranked items. Ignored if all provided objects are character vectors.
maxCutoffs	Maximum number of cutoffs. If the input data frames contain more cutoffs than this value, only maxCutoffs linearly spaced cutoffs will be selected from the generated cutoff list. Ignored if all provided objects are character vectors.
mtMethod	Multiple testing correction method.
nCores	Number of cores. If performing an overlap assessment between sets belonging to the same universe, it is recommended not to use parallelization (that is, leave this parameter as 1).
type	Type of overlap assessment. Choose between: two sets belonging to the same universe ('2N'), two sets belonging to different universes ('2MN'), three sets belonging to the same universe ('3MN').

Value

A numeric value in [0, 1] representing the p-value of the overlap of the two objects.

Examples

pvalObjects(LETTERS[seq(2, 7)], LETTERS[seq(3, 19)], universe1=LETTERS)

---

Compute the p-value of intersection of two subsets of sets M and N

Description

This function computes the p-value of intersection of two subsets of sets M and N.

Usage

pvalSets2MN(a, b, m, n)

Arguments

a	A character vector.
b	A character vector.
m	Set from which a is selected.
n	Set from which b is selected.

Details

A thin wrapper around pvalCounts2MN.

Value

A numeric value in [0, 1] representing the p-value of intersection of two subsets of sets M and N.

Examples

pvalSets2MN(LETTERS[seq(4, 10)],
LETTERS[seq(7, 15)],
LETTERS[seq(19)],
LETTERS[seq(6, 26)])

---

Calculate the p-value of intersection for two sets

Description

This function calculates the p-value of intersection for two sets.

Usage

pvalSets2N(a, b, n)

Arguments

a	A character vector.
b	A character vector.
n	Set from which a and b are selected.

Details

A thin wrapper around stats::phyper.

Value

A numeric value in [0, 1] representing the p-value of intersection for two sets.

Examples

pvalSets2N(LETTERS[seq(4, 10)], LETTERS[seq(7, 15)], LETTERS)

---

Compute the p-value of intersection of three subsets

Description

This function computes the p-value of intersection of three subsets.

Usage

pvalSets3N(a, b, c, n)

Arguments

a	A character vector.
b	A character vector.
c	A character vector.
n	Set from which a, b and c are selected.

Details

A thin wrapper around pvalCounts3N.

Value

A numeric value in [0, 1] representing the p-value of intersection of three subsets.

Examples

pvalSets3N(LETTERS[seq(4, 10)],
LETTERS[seq(7, 15)],
LETTERS[seq(19)],
LETTERS)

---

Assess the overlap of two or three lists of objects.

Description

This function assesses the overlap of two or three lists of objects (character vectors, or data frames having at least one numeric column).

Usage

runLISTO(
  list1,
  list2,
  list3 = NULL,
  universe1,
  universe2 = NULL,
  numCol = NULL,
  isHighTop = TRUE,
  maxCutoffs = 500,
  mtMethod = c("BY", "holm", "hochberg", "hommel", "bonferroni", "BH", "fdr", "none"),
  pvalThr = NULL,
  nCores = 1,
  verbose = TRUE,
  ...
)

Arguments

list1	A list containing either 1) data frames having items as row names and a numeric column or 2) character vectors.
list2	A list containing either 1) data frames having items as row names and a numeric column or 2) character vectors.
list3	A list containing either 1) data frames having items as row names and a numeric column or 2) character vectors.
universe1	Character vector; the set from which the items corresponding to the elements in list1 are selected.
universe2	Character vector; the set from which the items corresponding to the elements in list2 are selected. If not specified, universe1 is used.
numCol	The name of the numeric column used for data frame ordering.
isHighTop	Whether higher values in the numeric column correspond to better-ranked items. Ignored if all provided objects are character vectors.
maxCutoffs	Maximum number of cutoffs. If the input data frames contain more cutoffs than this value, only maxCutoffs linearly spaced cutoffs will be selected from the generated cutoff list. Ignored if all provided objects are character vectors.
mtMethod	Multiple testing correction method.
pvalThr	Threshold to filter the results based on the adjusted p-values. If NULL as default, no filtering will be performed.
nCores	Number of cores. If performing an overlap assessment between sets belonging to the same universe, it is recommended not to use parallelization (that is, leave this parameter as 1).
verbose	Logical; whether the output should be verbose.
...	Additional arguments passed to mtCorrectDF.

Value

A data frame listing the p-value and adjusted p-value for each overlap. Combinations of overlaps are represented through the first two (or three if list3 is not NULL) columns, while the penultimate column records the overlap p-values and the last column records the adjusted overlap p-values.

Examples

donorPath <- system.file('extdata', 'donorMarkers.qs2', package='LISTO')
donorMarkers <- qs2::qs_read(donorPath)[seq(3)]
labelPath <- system.file('extdata', 'labelMarkers.qs2', package='LISTO')
labelMarkers <- qs2::qs_read(labelPath)[seq(3)]
universe1Path <- system.file('extdata', 'universe1.qs2', package='LISTO')
universe1 <- qs2::qs_read(universe1Path)
res <-  runLISTO(donorMarkers, labelMarkers, universe1=universe1,
numCol='avg_log2FC')

---

Compute the prime factor decomposition of the binomial coefficient

Description

This function computes the prime factor decomposition of the binomial coefficient.

Usage

vChoose(n, k)

Arguments

n	Total number of elements.
k	Number of selected elements.

Value

A vector in which positions represent prime numbers (that is, the first position corresponds to 2, the second position corresponds to 3, the third position corresponds to 5, etc.) and values represent their exponents in the factorial decomposition.

Examples

vChoose(8, 4)

---

Add numeric vectors of different lenghts

Description

This function adds numeric vectors of different lengths by filling shorter vectors with zeroes.

Usage

vSum(...)

Arguments

...	Numeric vectors.

Value

A numeric vector.

Examples

vSum(c(1, 4), c(2, 8, 6), c(1, 7), c(10, 4, 6, 7))

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