Package 'RgnTX'

Title: Colocalization analysis of transcriptome elements in the presence of isoform heterogeneity and ambiguity
Description: RgnTX allows the integration of transcriptome annotations so as to model the complex alternative splicing patterns. It supports the testing of transcriptome elements without clear isoform association, which is often the real scenario due to technical limitations. It involves functions that do permutaion test for evaluating association between features and transcriptome regions.
Authors: Yue Wang [aut, cre], Jia Meng [aut]
Maintainer: Yue Wang <[email protected]>
License: Artistic-2.0
Version: 1.7.0
Built: 2024-09-21 04:56:29 UTC
Source: https://github.com/bioc/RgnTX

Help Index

Calculate positional shifting over transcriptome

Description

The first step of calculating positional shift over transcriptome regions.

Usage

calculateShift(regions, disp, direction = "right", strand = "+")

Arguments

regions

A feature set, which should be a GRangesList object.
disp

A data frame object. It should have three columns, which are start: starting positions. Each value represents a starting position in each input feature; width: widths. Each value represents a width of each region to be picked from each feature; names: corresponding transcript ids.
direction

Either to be character "left" or "right", which means the direction to which the starting position is shifting. The former means moving to the direction of 5' while the latter means moving to 3'.
strand

Either to be "+" or "-".

Value

A GRanges object.

See Also

extractRegions

Examples

# Take five transcripts.
# Extract the last 200 nt regions from their CDS part.
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
trans.id.pstv <- c("170", "782", "974", "1364", "1387")
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene

# Download the CDS part of all transcriptome
cds.tx0 <- cdsBy(txdb, use.names = FALSE)

# pick the CDS part of these five transcripts
cds.p <- cds.tx0[trans.id.pstv]

width <- 200
disp.p.l <- data.frame(
    start = as.numeric(max(end(cds.p))),
    distance = width - 1,
    names = trans.id.pstv
)
R.p.l <- calculateShift(
    regions = cds.p, disp = disp.p.l,
    direction = "left", strand = "+"
)

Evaluation function

Description

Evaluation function. This function calculates the mean of the distance from each region of set RS1 to the closest region in RS2.

Usage

distanceTx(A, B, beta = 0.2, ...)

Arguments

A

Region set 1. A Granges or GRangesList object.
B

Region set 2. A Granges or GRangesList object.
beta

It is a user-defined argument that can filter out the corresponding percent of largest distance values. Default value is 0.2.
...

Any additional parameters needed.

Value

A numeric object.

See Also

overlapWidthTx, overlapCountsTx

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids <- c("170", "782", "974", "1364", "1387")
A <- randomizeTx(
    txdb, trans.ids,
    random_num = 20,
    random_length = 100
)
B <- randomizeTx(
    txdb, trans.ids,
    random_num = 20,
    random_length = 100
)
distanceTx(A, B, beta = 0.2)

Extract regions

Description

This function receives three arguments: the scope region set, the target region set and the type of strand. It returns a subset of target region set, which is the intersection of the target region set and the scope region set.

Usage

extractRegions(regions_A, R, strand = "+")

Arguments

regions_A

The scope region set. A GRangesList object. The name of each list element should be the transcript id that it pertains to.
R

The target region set. A GRanges object.
strand

The strand type of the transcripts. It has options "+" and "-".

Value

A GRangesList object.

See Also

calculateShift

Examples

# Take five transcripts.
# Extract the last 200 nt regions from their CDS part.
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
trans.id.pstv <- c("170", "782", "974", "1364", "1387")
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene

# download the CDS part of all transcriptome
cds.tx0 <- cdsBy(txdb, use.names = FALSE)

# pick the CDS part of these five transcripts
cds.p <- cds.tx0[trans.id.pstv]

width <- 200
disp.p.l <- data.frame(
    start = as.numeric(max(end(cds.p))),
    distance = width - 1,
    names = trans.id.pstv
)
R.p.l <- calculateShift(regions = cds.p, disp = disp.p.l, direction = "left", strand = "+")

R.cds.last200 <- extractRegions(regions_A = cds.p, R = R.p.l, strand = "+")

getFormatCorrect

Description

This function makes sure the two input region sets are in the correct format required by RgnTX evaluation functions.

Usage

getFormatCorrect(A, B)

Arguments

A

Region set 1. A Granges or GRangesList object.
B

Region set 2. A Granges or GRangesList object.

Value

A list object.

Get permutation space for features

Description

This function returns a default permutation space for features with isoform ambiguity. The default permutation space of a feature is the aggregate of the multiple transcripts it may overlap with. It requires the input feature to be GRanges format.

Usage

getPermSpaceByFeatures(features, txdb, type = "mature")

Arguments

features

A GRanges object.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of regions over transcriptome.

Value

A list object, which contains two elements.

  • perm.space: A GRangesList object that includes all the transcripts input features may overlap with.

  • index: It contains a series of numbers indicating which feature these transcripts are respectively associated with.

See Also

getPermSpaceByTxID, getPermSpaceByType

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
file <- system.file(package="RgnTX", "extdata/m6A_sites_data.rds")
m6A_sites_data <- readRDS(file)
permSpace <- getPermSpaceByFeatures(features = m6A_sites_data[1:100], txdb)

Get permutation space by specifying transcript ids

Description

This function returns 5'UTR/CDS/3'UTR/mRNA/full part of transcriptome regions grouped by corresponding transcript ids.

Usage

getPermSpaceByTxID(trans_ids = "all", txdb, type = "mature")

Arguments

trans_ids

A character object. The transcript ids. Default is "all". If it takes the default value "all", the space that users get will be the whole transcriptome.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.

Value

A GRangesList object.

See Also

getPermSpaceByType, getPermSpaceByFeatures

Examples

trans.ids <- c("170", "782", "974", "1364", "1387")
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
permspace <- getPermSpaceByTxID(trans.ids, txdb)

Get permutation space by specifying type

Description

This function can return 5'UTR/CDS/3'UTR/mRNA/full part of transcriptome regions, following the format required by the main permutation test functions.

Usage

getPermSpaceByType(txdb, type = "mature")

Arguments

txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.

Value

A GRangesList object.

See Also

getPermSpaceByTxID, getPermSpaceByFeatures

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
permSpace <- getPermSpaceByType(txdb, type = "CDS")

getPvalZscore

Description

Calculate a p-value and z-score based on observed value and random evaluation values.

Usage

getPvalZscore(orig.ev, rand.ev, pval_z = FALSE)

Arguments

orig.ev

Observed value.
rand.ev

Random evaluation values.
pval_z

Boolean. Default is FALSE. If FALSE, the p-value is calculated based on the number of random evaluations is larger or less than the initial evaluation. If TRUE, the p-value is calculated based on a z-test.

Value

A p-value and a z-score.

getStopCodon

Description

Get stop codon regions for input transcripts. This is an example of customPick function.

Usage

getStopCodon(trans_ids, txdb, ...)

Arguments

trans_ids

A character object containing transcript ids.
txdb

A TxDb object.
...

Any additional parameters needed.

Value

A numeric object.

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids <- c("170", "782", "974", "1364", "1387")
RS2 <- getStopCodon(trans.ids, txdb)

Get transcript information

Description

Generate a data frame object that contains information about input genomic feature set and its mapping results over the transcriptome.

Usage

getTransInfo(A, txdb)

Arguments

A

Genomic feature set, which should be a GRanges object.
txdb

A TxDb object.

Value

A data.frame object containing the following components:

  • index_trans: The label of transcripts.

  • index_features: The label of genomic features.

  • seqnames: The chr name.

  • features_pos: The starting coordinate of each genomic feature.

  • width_features: The width of each genomic feature.

  • strand: The strand type of each genomic feature.

  • trans_ID: The ids of the transcripts that each feature can be mapped to.

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
file <- system.file(package="RgnTX", "extdata/m6A_sites_data.rds")
m6A_sites_data <- readRDS(file)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
getTransInfo(A = m6A_sites_data[1:100], txdb)

Convert a GRanges object to a GRangesList object

Description

Convert a GRanges object to a GRangesList object. The output region set follows the format required by the main permutation test functions.

Usage

GRanges2GRangesList(A = NULL)

Arguments

A

A GRanges object.

Details

If input GRanges object has a metadata named as "group", ranges having the same group number represent a region. If not, a range is a region. A region in the input set will be outputted as a list element IN returned GRangesList object.

Value

A GRangesList object.

See Also

GRanges2GRangesList

Examples

library(GenomicRanges)
GRanges.object <- GRanges(
    Rle(c("chr2", "chr2", "chr1", "chr3")),
    IRanges(1:4, width = 5)
)
# Assign the first and the second ranges to the same element.
GRanges.object$group <- c(1, 1, 2, 3)
GRangesList.object <- GRanges2GRangesList(GRanges.object)

Convert a GRangesList object to a GRanges object

Description

Convert a GRangesList object to a GRanges object. The output region set follows the format required by the RgnTX permutation test functions, which should have metadata columns 'group' and 'transcriptsHits'.

Usage

GRangesList2GRanges(A = NULL)

Arguments

A

A GRangesList object.

Value

A GRanges object. Its transcript ids (if available) should be contained in a metadata column named “transcriptsHits”, which are provided by the names of input GRangesList object.

See Also

GRanges2GRangesList

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids <- c("170", "782", "974", "1364", "1387")
RS1 <- randomizeTx(txdb, trans.ids, random_num = 100, random_length = 100)

RS1 <- GRangesList2GRanges(RS1)

Evaluation function

Description

This function receives two region sets and returns the number of their overlaps.

Usage

overlapCountsTx(A, B, count_once = TRUE, over_trans = TRUE, ...)

Arguments

A

Region set 1. A GRangesList object.
B

Region set 2. A GRangesList object.
count_once

Whether the overlap of multiple B regions with a single A region should be counted once or multiple times.
over_trans

Whether the overlapping is counted over the transcriptome or over the genome.
...

Any additional parameters needed.

Value

A numeric object.

See Also

overlapCountsTx

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids <- c("170", "782", "974", "1364", "1387")
exons.tx0 <- exonsBy(txdb)
regions.A <- exons.tx0[trans.ids]
A <- randomizeTransByOrder(regions.A, random_length = 200)
B <- randomizeTransByOrder(regions.A, random_length = 200)

overlapCountsTx(A, B)

Evaluation function

Description

Evaluation function. This function receives a feature set (with isoform ambiguity) and a transcriptome region set (without isoform ambiguity), and returns a weighted number of overlaps between them.

Usage

overlapCountsTxIA(A, B, ...)

Arguments

A

A feature set, which should be GRanges.
B

A region set, which should be GRangesList.
...

Any additional parameters needed.

Value

A numeric object.

See Also

overlapWidthTx, distanceTx, overlapCountsTx

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
file <- system.file(package="RgnTX", "extdata/m6A_sites_data.rds")
m6A_sites_data <- readRDS(file)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
RS1 <- m6A_sites_data[1:100]

trans.info <- getTransInfo(RS1, txdb)
trans.ids <- trans.info[, "trans_ID"]

RS2 <- getStopCodon(trans.ids, txdb = txdb)

# Evaluation step.
orig.ev <- overlapCountsTxIA(RS1, RS2)

Evaluation function

Description

Evaluation function. This function returns the sum of widths of each overlap between two region sets, i.e., the total number of overlapping nucleotides between two input region sets.

Usage

overlapWidthTx(A, B, ...)

Arguments

A

Region set 1. A Granges or GRangesList object.
B

Region set 2. A Granges or GRangesList object.
...

Any additional parameters needed.

Value

A numeric object.

See Also

overlapCountsTx, distanceTx

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids <- c("170", "782", "974", "1364", "1387")
A <- randomizeTx(
    txdb, trans.ids, random_num = 20,
    random.length = 100
)
B <- randomizeTx(
    txdb, trans.ids = trans.ids, random_num = 20,
    random_length = 100
)

overlapWidthTx(A, B)

Perform permutation test

Description

Perform permutation test for evaluating spatial association between a feature set and a region set.

Usage

permTestTx(RS1 = NULL, RS2 = NULL, txdb = NULL, type = "mature",
ntimes = 50, ev_function_1 = overlapCountsTx, ev_function_2 = overlapCountsTx,
pval_z = FALSE, ...)

Arguments

RS1

The region set to be randomized. It should be in the GRanges or GRangesList format.
RS2

The region set to be compared with. It should be in the GRanges or GRangesList format.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.
ntimes

Randomization times.
ev_function_1

Evaluation function defines what statistic to be tested between RS1 and RS2. Default is overlapCountsTx.
ev_function_2

Evaluation function defines what statistic to be tested between each element in RSL and RS2. Default is overlapCountsTx.
pval_z

Boolean. Default is FALSE. If FALSE, the p-value is calculated based on the number of random evaluations is larger or less than the initial evaluation. If TRUE, the p-value is calculated based on a z-test.
...

Any additional parameters needed.

Details

permTestTxIA only needs users to input two region sets. It will automatically randomize the first region set into transcriptome.

Value

A list object, which is defined to be permTestTx.results class. It contains the following items:

  • RSL: Randomized region sets of RS1.

  • RS1: The feature set to be randomized.

  • RS2: The region set to be compared with the feature set.

  • orig.ev: The value of overlapping counts between RS1 and RS2.

  • rand.ev: The values of overlapping counts between each element in RSL and RS2.

  • pval: p-value of the test.

  • zscore: Standard score of the test.

See Also

plotPermResults

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
exons.tx0 <- exonsBy(txdb)
trans.ids <- sample(names(exons.tx0), 500)

A <- randomizeTx(txdb, trans.ids, random_num = 100, random_length = 100)
B <- c(randomizeTx(txdb, trans.ids, random_num = 75, random_length = 100), A[1:25])

permTestTx_results <- permTestTx(A, B, txdb, ntimes = 5)

Perform permutation test

Description

Perform permutation test for evaluating spatial association between region sets. This permutation test function receives two region sets and a set of randomized region sets of one of them. It evaluates if there is an association between these two region sets.

Usage

permTestTx_customAll(RSL = NULL, RS1 = NULL, RS2 = NULL,
ev_function_1 = overlapCountsTx, ev_function_2 = overlapCountsTx, pval_z = FALSE, ...)

Arguments

RSL

Randomized region sets of RS1. It should be a list object and each element should be in the GRanges or GRangesList format.
RS1

The region set. It should be in the GRanges or GRangesList format.
RS2

The region set to be compared with. It should be in the GRanges or GRangesList format.
ev_function_1

Evaluation function defines what statistic to be tested between RS1 and RS2. Default is overlapCountsTx.
ev_function_2

Evaluation function defines what statistic to be tested between each element in RSL and RS2. Default is overlapCountsTx.
pval_z

Boolean. Default is FALSE. If FALSE, p-value is calculated based on the number of random evaluations is larger or less than the initial evaluation. If TRUE, p-value is calculated based on a z-test.
...

Any additional parameters needed.

Details

permTestTx_customAll will use evaluation function ev_function_1 to calculate the test statistic between RS1 and RS2, and use ev_function_2 to evaluate the statistic between RSL and RS2. It will also return a p-value and a z-score.

Value

A list object, which is defined to be permTestTx.results class. It contains the following items:

  • RSL: Randomized region sets of RS1.

  • RS1: The feature set to be randomized.

  • RS2: The region set to be compared with the feature set.

  • orig.ev: The value of overlapping counts between RS1 and RS2.

  • rand.ev: The values of overlapping counts between each element in RSL and RS2.

  • pval: p-value of the test.

  • zscore: Standard score of the test.

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids1<- c("170")
RS1 <- randomizeTx(txdb = txdb, trans_ids = trans.ids1,
                    random_num = 20, random_length = 100)
RS2 <- randomizeTx(txdb = txdb, trans_ids = trans.ids1,
                    random_num = 20, random_length = 100)
trans.ids2 <-  c("170", "782", "974", "1364", "1387")
RSL <- randomizeTx(txdb = txdb, trans_ids = trans.ids2,
                    random_num = 20, random_length = 100, N = 10)
permTestTx_results <- permTestTx_customAll(RSL = RSL, RS1 = RS1, RS2 = RS2)

Perform permutation test

Description

Perform permutation test for evaluating spatial association between a feature set and the customPick regions. The latter is defined by the customPick_function argument provided by users.

Usage

permTestTx_customPick(RS1 = NULL, txdb = NULL, type = "mature",
customPick_function = NULL, ntimes = 50, ev_function_1 = overlapCountsTx,
ev_function_2 = overlapCountsTx,  pval_z = FALSE, ...)

Arguments

RS1

The feature set to be randomized. It should be in the GRanges or GRangesList format.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.
customPick_function

A custom function needs to be inputted by users. The custom function should have two arguments: a TxDb object and a character object of transcript ids. It returns a part of region of each transcript.
ntimes

Randomization times.
ev_function_1

Evaluation function defines what statistic to be tested between RS1 and RS2. Default is overlapCountsTx.
ev_function_2

Evaluation function defines what statistic to be tested between each element in RSL and RS2. Default is overlapCountsTx.
pval_z

Boolean. Default is FALSE. If FALSE, the p-value is calculated based on the number of random evaluations is larger or less than the initial evaluation. If TRUE, the p-value is calculated based on a z-test.
...

Any additional parameters needed.

Details

Each feature in RS1 is only mapped with the customPick regions over its transcript (picked by the customPick_function). The output orig.ev is the number of features that have overlap with its customPick region. The set of randomized region sets is outputted as RSL. The overlapping counts between each set in RSL with RS2 is outputted as rand.ev.

Value

A list object, which is defined to be permTestTx.results class. It contains the following items:

  • RSL: Randomized region sets of RS1.

  • RS1: The feature set to be randomized.

  • RS2: The region set to be compared with the feature set.

  • orig.ev: The value of overlapping counts between RS1 and RS2.

  • rand.ev: The values of overlapping counts between each element in RSL and RS2.

  • pval: p-value of the test.

  • zscore: Standard score of the test.

See Also

plotPermResults

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
exons.tx0 <- exonsBy(txdb)
trans.ids <- sample(names(exons.tx0), 100)
RS1 <- randomizeTx(txdb, trans.ids, random_num = 100,
random_length = 200, type = 'CDS')
getCDS = function(txdb, trans.id){
cds.tx0 <- cdsBy(txdb, use.names=FALSE)
    cds.names <- as.character(intersect(names(cds.tx0), trans.id))
    cds = cds.tx0[cds.names]
    return(cds)
}

permTestTx_results <- permTestTx_customPick(RS1,txdb,
customPick_function = getCDS, ntimes = 5)

Perform permutation test

Description

Perform permutation test for evaluating spatial association between some features (with isoform ambiguity) and a region set. It randomizes the features and compares it with the region set to see if there is an association between the features and the region set. The difference between this function and permTestTx is that it is for RNA-related genomic features that have isoform ambiguity, i.e., features that one does not know which transcript they comes from.

Usage

permTestTxIA(RS1 = NULL,
                    RS2 = NULL,
                    txdb = NULL,
                    type = 'mature',
                    ntimes = 50,
                    ev_function_1 = overlapCountsTx,
                    ev_function_2 = overlapCountsTx,
                    pval_z = FALSE,
                    ...)

Arguments

RS1

The feature set to be randomized. It should be in the GRanges or GRangesList format.
RS2

The region set to be compared with. It should be in the GRanges or GRangesList format.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.
ntimes

Randomization times.
ev_function_1

Evaluation function defines what statistic to be tested between RS1 and RS2. Default is overlapCountsTx.
ev_function_2

Evaluation function defines what statistic to be tested between each element in RSL and RS2. Default is overlapCountsTx.
pval_z

Boolean. Default is FALSE. If FALSE, the p-value is calculated based on the number of random evaluations is larger or less than the initial evaluation. If TRUE, the p-value is calculated based on a z-test.
...

Any additional parameters needed.

Details

permTestTxIA only needs users to input two region sets. It will automatically randomize the first region set into transcriptome.

Value

A list object, which is defined to be permTestTx.results class. It contains the following items:

  • RSL: Randomized region sets of RS1.

  • RS1: The feature set to be randomized.

  • RS2: The region set to be compared with the feature set.

  • orig.ev: The value of overlapping counts between RS1 and RS2.

  • rand.ev: The values of overlapping counts between each element in RSL and RS2.

  • pval: p-value of the test.

  • zscore: Standard score of the test.

See Also

plotPermResults

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
file <- system.file(package="RgnTX", "extdata/m6A_sites_data.rds")
m6A_sites_data <- readRDS(file)
RS1 <- m6A_sites_data[1:500]
trans.ids <- getTransInfo(RS1, txdb)[, "trans_ID"]
RS2 <- getStopCodon(trans.ids, txdb)

permTestTx_results <- permTestTxIA(RS1 = RS1, RS2 = RS2,
                            txdb = txdb, ntimes = 5)

Perform permutation test

Description

Perform permutation test for evaluating spatial association between RNA features and a specified kind of regions. The latter is defined by the customPick_function argument input by users. The difference between this function and permTestTx_customPick is that it is for RNA-related genomic features that have isoform ambiguity, i.e., features that one does not know which transcript they comes from.

Usage

permTestTxIA_customPick(RS1 = NULL, txdb = NULL, type = 'mature',
customPick_function = NULL, ntimes = 50,
ev_function_1 = overlapCountsTxIA, ev_function_2 = overlapCountsTx,  pval_z = FALSE, ...)

Arguments

RS1

The region set to be randomized. It should be in the GRanges or GRangesList format.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.
customPick_function

A custom function needs to be inputted by users. The customPick function should have two arguments: a TxDb object and a character object of transcript ids. It returns a specified region over each transcript.
ntimes

Randomization times.
ev_function_1

Evaluation function defines what statistic to be tested between RS1 and RS2. Default is overlapCountsTxIA.
ev_function_2

Evaluation function defines what statistic to be tested between each element in RSL and RS2. Default is overlapCountsTx.
pval_z

Boolean. Default is FALSE. If FALSE, the p-value is calculated based on the number of random evaluations is larger or less than the initial evaluation. If TRUE, the p-value is calculated based on a z-test.
...

Any additional parameters needed.

Details

permTestTxIA_customPick will assess the test statistic between RS1 and each region in RSL, and the relation between RS1 and RS2. Each RNA feature is only mapped with a part of region on its transcript (picked by the customPick_function). The output orig.ev is the weighted counts between RS1 and RS2. Each feature in RS1 related to n1 isoforms in RS2 and overlapped with n2 RS2 regions will contribute a value of n2/n1 to the total number of overlaps. This test function also randomizes input features per transcript. The set of randomized results is outputted as RSL. The overlapping counts between each set in RSL with RS2 is outputted as rand.ev.

Value

A list object, which is defined to be permTestTx.results class. It contains the following information:

  • RSL: Randomized region sets of RS1.

  • RS1: The feature set to be randomized.

  • RS2: The region set to be compared with the feature set.

  • orig.ev: The value of overlapping counts between RS1 and RS2.

  • rand.ev: The values of overlapping counts between each element in RSL and RS2.

  • pval: p-value of the test.

  • zscore: Standard score of the test.

See Also

plotPermResults

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
file <- system.file(package="RgnTX", "extdata/m6A_sites_data.rds")
m6A_sites_data <- readRDS(file)
RS1 <- m6A_sites_data[1:500]

permTestTx_results <- permTestTxIA_customPick(RS1 = RS1,
                                            txdb = txdb,
                                            type = 'mature',
                                            customPick_function = getStopCodon,
                                            ntimes = 5)

Plot permutation test results

Description

Show a graphical representation of permutation test.

Usage

plotPermResults(permTestTx_results = NULL, breaks = 15, alpha = 0.05,
test_type = "one-sided", binwidth = NULL)

Arguments

permTestTx_results

A permTestTx.results list object, which can be generated by the permTestTx function.
breaks

Histogram breaks. Default is 15.
alpha

Significance level.
test_type

The type of the test. This argument only receives either two options "one-sided" or "two-sided". Default is "one-sided".
binwidth

Histogram binwidth.

Value

A plot object.

See Also

permTestTx

Examples

file <- system.file(package="RgnTX", "extdata", "permTestTx_results.rds")
permTestTx_results <- readRDS(file)
p_a <- plotPermResults(permTestTx_results, binwidth = 1)
p_a

Plot shifted z scores

Description

Plot shifted z scores for permutation test results.

Usage

plotShiftedZScoreTx(shitedZScoresTx_results)

Arguments

shitedZScoresTx_results

A shitedZScoreTx.results object.

Value

A plot.

See Also

shiftedZScoreTx

Examples

file <- system.file(package="RgnTX", "extdata", "shiftedZScoreTx_results1.rds")
shiftedZScoreTx_results <- readRDS(file)
p1 <- plotShiftedZScoreTx(shiftedZScoreTx_results)
p1

Randomize features into transcriptome

Description

Randomize features into transcriptome.

Usage

randomizeFeaturesTx(RS, txdb, type = "mature", N = 1, ...)

Arguments

RS

The feature to be randomized. It should be a GRanges or GRangesList object.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.
N

The number of iterations.
...

Any additional parameters needed.

Value

A GRangesList object. The name of each element is the id of the transcript where the corresponding range is located.

See Also

randomizeTransByOrder, randomizeFeaturesTxIA, randomizeTx

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids <- c("170", "782", "974", "1364", "1387")
RS1 <- randomizeTx(txdb, trans.ids, random_num = 100, random_length = 100)
RS <- randomizeFeaturesTx(RS1, txdb, N = 1)

Randomize features into transcriptome

Description

Randomize features into transcriptome, especially for the features that have isoform ambiguity.

Usage

randomizeFeaturesTxIA(RS, txdb, type = "mature", N = 1, ...)

Arguments

RS

The feature being randomized. It should be a GRanges or GRangesList object.
txdb

A TxDb object.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.
N

Randomization times.
...

Any additional parameters needed.

Value

A GRangesList object. The name of each element is the id of the transcript where the corresponding range is located.

See Also

randomizeTransByOrder, randomizeFeaturesTx, randomizeTx

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
file <- system.file(package="RgnTX", "extdata/m6A_sites_data.rds")
m6A_sites_data <- readRDS(file)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
RS1 <- m6A_sites_data[1:100]
RS <- randomizeFeaturesTxIA(RS1, txdb, N = 1)

Randomize features into transcriptome

Description

This function receives a GRangesList object and picks a random region within each list element of this object. The length of the region to be picked is decided by the input random_length argument.

Usage

randomizeTransByOrder(regions_A, random_length = 20)

Arguments

regions_A

A GRangesList object. The name of each list element should be the corresponding transcript id.
random_length

A numeric object.

Value

A GRangesList object. The name of each list element should be the corresponding transcript id.

See Also

randomizeTx, randomizeFeaturesTx, randomizeFeaturesTxIA

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
exons.tx0 <- exonsBy(txdb)
trans.ids <- sample(names(exons.tx0), 500)
regions.A <- exons.tx0[trans.ids]
RS <- randomizeTransByOrder(regions.A, random_length = 20)

Get randmized regions over transcriptome

Description

Pick random regions over specified transcripts.

Usage

randomizeTx(txdb, trans_ids = 'all',
random_num = 100, random_length = 20, type = 'mature', N = 1, ...)

Arguments

txdb

A TxDb object.
trans_ids

The ids of transcripts, which should be a character object. Random regions will be picked from these transcripts. If this argument takes the default value 'all', the scope of picking random regions will be the whole transcriptome.
random_num

The number of regions to be picked.
random_length

The length of regions to be picked.
type

A character object. Default is "mature". It accepts options "mature", "full", "fiveUTR", "CDS" or "threeUTR", with which one can get corresponding types of transcriptome regions.
N

Randomization times.
...

Any additional parameters needed.

Value

A GRangesList object. The name of each element is the id of the transcript where the corresponding range is located.

See Also

randomizeTransByOrder, randomizeFeaturesTx, randomizeFeaturesTxIA

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
trans.ids <- c("170", "782", "974", "1364", "1387")
RS1 <- randomizeTx(txdb, trans.ids, random_num = 100, random_length = 100)

Calculate shifted z scores

Description

Calculate shifted z scores for permutation test results.

Usage

shiftedZScoreTx(permTestTx_results = NULL, txdb = NULL,
window = 200, step = 20, ev_function_1 = overlapCountsTx, ...)

Arguments

permTestTx_results

A permTestTx.results object.
txdb

A TxDb object.
window

The window of the whole shifting.
step

The step of each shifting.
ev_function_1

Evaluation function. Default is overlapCountsTx.
...

Any additional parameters needed.

Details

see examples in plotShiftedZScoreTx

Value

A list object, which is defined to be shitedZScore.results class. It contains the following items:

  • shifted.z.scores: Standard z-scores after shifting.

  • window: Window of the whole shifting.

  • step: Step of each shifting.

  • original.z.score: Original standard score.

See Also

plotShiftedZScoreTx

Examples

library(TxDb.Hsapiens.UCSC.hg19.knownGene)
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene
file <- system.file(package="RgnTX", "extdata/m6A_sites_data.rds")
m6A_sites_data <- readRDS(file)
RS1 <- m6A_sites_data[1:500]
permTestTx_results <- permTestTxIA_customPick(RS1 = RS1,
                                        txdb = txdb,
                                        customPick_function = getStopCodon,
                                        ntimes = 5)
shiftedZScoreTx_results <- shiftedZScoreTx(permTestTx_results, txdb = txdb,
                                        window = 2000,
                                        step = 200,
                                        ev_function_1 = overlapCountsTxIA)

Shift over transcripts

Description

Calculate positional shifting over transcript regions. This function accepts a feature set and outputs a region set from it. Each output region is from each input feature.

Usage

shiftTx(regions, start, width, direction, strand)

Arguments

regions

A feature set following the format indicated in vignette section 3. Either to be GRanges or GRangesList.
start

Starting positions. Each value represents a starting position in each input feature.
width

Widths. Each value represents a width of each region to be picked from each feature.
direction

Either to be character "left" or "right", which means the direction to which the starting position is shifting. The former means moving to the direction of 5' while the latter means moving to 3'.
strand

The strand type of the transcripts. It receives "+" or "-".

Value

A Granges object.

Examples

# Take five transcripts.
# Extract the last 200 nt regions from their CDS part.
library(TxDb.Hsapiens.UCSC.hg19.knownGene)
trans.id.pstv <- c("170", "782", "974", "1364", "1387")
txdb <- TxDb.Hsapiens.UCSC.hg19.knownGene

# download the CDS part of all transcriptome
cds.tx0 <- cdsBy(txdb, use.names = FALSE)

# pick the CDS part of these five transcripts
cds.p <- cds.tx0[trans.id.pstv]

width <- 200
start <- as.numeric(max(end(cds.p)))
R.cds.last200 <- shiftTx(cds.p, start = start, width = width, direction = 'left', strand = "+")

vector2GRangesList

Description

Generate GRangesList object from vectors. The output region set follows the format required by the main permutation test functions.

Usage

vector2GRangesList(RefSeqID, targetName, strand, blockSizes, targetStart)

Arguments

RefSeqID

The name of each element.
targetName

The seqnames of each range.
strand

The strand of each range.
blockSizes

The width of each range.
targetStart

The stard coordinate of each range.

Value

A GRangesList object.

See Also

GRanges2GRangesList