mapToTranscripts {GenomicFeatures} | R Documentation

## Map range coordinates between transcripts and genome space

### Description

Map range coordinates between features in the transcriptome and genome (reference) space.

See `?mapToAlignments` in the GenomicAlignments package for mapping coordinates between reads (local) and genome (reference) space using a CIGAR alignment.

### Usage

    ## mapping to transcripts
    ## S4 method for signature 'GenomicRanges,GenomicRanges'
    mapToTranscripts(x, transcripts,
              ignore.strand = FALSE)
    ## S4 method for signature 'GenomicRanges,GRangesList'
    mapToTranscripts(x, transcripts,
              ignore.strand = FALSE, intronJunctions=FALSE)
    ## S4 method for signature 'ANY,TxDb'
    mapToTranscripts(x, transcripts, ignore.strand = FALSE,
              extractor.fun = GenomicFeatures::transcripts, ...)
    ## S4 method for signature 'GenomicRanges,GRangesList'
    pmapToTranscripts(x, transcripts,
              ignore.strand = FALSE)

    ## mapping from transcripts
    ## S4 method for signature 'GenomicRanges,GRangesList'
    mapFromTranscripts(x, transcripts,
              ignore.strand = FALSE)
    ## S4 method for signature 'GenomicRanges,GRangesList'
    pmapFromTranscripts(x, transcripts,
              ignore.strand = FALSE)
    ## S4 method for signature 'Ranges,GRangesList'
    pmapFromTranscripts(x, transcripts)

### Arguments

`x` | `GenomicRanges` object of positions to be mapped. The seqnames of `x` are used in `mapFromTranscripts`, i.e., when mapping from transcripts to the genome. In the case of `pmapFromTranscripts`, `x` can be a `Ranges` object.
`transcripts` | A named `GenomicRanges` or `GRangesList` object used to map between `x` and the result. The ranges can be any feature in the transcriptome extracted from a `TxDb` (e.g., introns, exons, cds regions). See ?`transcripts` and ?`transcriptsBy` for a list of extractor functions. The `transcripts` object must have names. When mapping from transcripts to the genome, they are used to determine mapping pairs; in the reverse direction they become the seqlevels of the output object.
`ignore.strand` | When `ignore.strand` is TRUE, strand is ignored in overlaps operations (i.e., all strands are considered "+") and the strand in the output is '*'. When `ignore.strand` is FALSE strand in the output is taken from the `transcripts` argument. When `transcripts` is a `GRangesList`, all inner list elements of a common list element must have the same strand or an error is thrown. Mapped position is computed by counting from the transcription start site (TSS) and is not affected by the value of `ignore.strand`.
`intronJunctions` | Logical to indicate whether intronic ranges in `x` should be reported. Ranges in `x` that do not fall ‘within’ a range in `transcripts` are considered a non-hit and have no mapping. When `intronJunctions=TRUE` the non-hits that fall between 2 ranges in `transcripts` are reported as a zero-width range (start and end taken from the ranges they fall between). To be considered 'intronic', the `x` range must fall between ranges in `transcripts`. Those that 'fall off' either end or overlap the intron gap and a range in `transcripts` will not be mapped. This argument is only supported in `mapToTranscripts` when `transcripts` is a GRangesList.
`extractor.fun` | Function to extract genomic features from a `TxDb` object. This argument is only applicable to `mapToTranscripts` when `transcripts` is a `TxDb` object. The `extractor` should be the name of a function (not a character()) described on the `?transcripts`, `?transcriptsBy`, or `?microRNAs` man page. Valid `extractor` functions: transcripts ## default exons cds genes promoters exonicParts intronicParts transcriptsBy exonsBy cdsBy intronsByTranscript fiveUTRsByTranscript threeUTRsByTranscript microRNAs tRNAs
`...` | Additional arguments passed to `extractor.fun` functions.

### Details

In GenomicFeatures >= 1.21.10, the default for `ignore.strand` was changed to `FALSE` for consistency with other methods in GenomicRanges and GenomicAlignments. Additionally, the mapped position is computed from the TSS and does not depend on the `ignore.strand` argument. See the section on `ignore.strand` for details.

- `mapToTranscripts`, `pmapToTranscripts` The genomic range in `x` is mapped to the local position in the `transcripts` ranges. A successful mapping occurs when `x` is completely within the `transcripts` range, equivalent to:

            findOverlaps(..., type="within")

  Transcriptome-based coordinates start counting at 1 at the beginning of the `transcripts` range and return positions where `x` was aligned. The seqlevels of the return object are taken from the `transcripts` object and should be transcript names. In this direction, mapping is attempted between all elements of `x` and all elements of `transcripts`.

  `mapToTranscripts` uses `findOverlaps` to map ranges in `x` to ranges in `transcripts`. This method does not return unmapped ranges.

  `pmapToTranscripts` maps the i-th range in `x` to the i-th range in `transcripts`. Recycling is supported for both `x` and `transcripts` when either is length == 1L; otherwise the lengths must match. Ranges in `x` that do not map (out of bounds or strand mismatch) are returned as zero-width ranges starting at 0. These ranges are given the seqname of "UNMAPPED".

- `mapFromTranscripts`, `pmapFromTranscripts` The transcript-based position in `x` is mapped to genomic coordinates using the ranges in `transcripts`. A successful mapping occurs when the following is TRUE:

            width(transcripts) >= start(x) + width(x)

  `x` is aligned to `transcripts` by moving in `start(x)` positions in from the beginning of the `transcripts` range. The seqlevels of the return object are chromosome names.

  `mapFromTranscripts` uses the seqname of `x` and the names of `transcripts` to determine mapping pairs (vs attempting to match all possible pairs). Name matching is motivated by use cases such as differentially expressed regions where the expressed regions in `x` would only be related to a subset of regions in `transcripts`. This method does not return unmapped ranges.

  `pmapFromTranscripts` maps the i-th range in `x` to the i-th range in `transcripts` and therefore does not use name matching. Recycling is supported in `pmapFromTranscripts` when either `x` or `transcripts` is length == 1L; otherwise the lengths must match. Ranges in `x` that do not map (out of bounds or strand mismatch) are returned as zero-width ranges starting at 0. These ranges are given the seqname of "UNMAPPED".

### Value

`pmapToTranscripts` returns a `GRanges` the same length as `x`.

`pmapFromTranscripts` returns a `GRanges` when `transcripts` is a `GRanges` and a `GRangesList` when `transcripts` is a `GRangesList`. In both cases the return object is the same length as `x`. The rational for returning the `GRangesList` is to preserve exon structure; ranges in a list element that are not overlapped by `x` are returned as a zero-width range. The `GRangesList` return object will have no seqlevels called "UNMAPPED"; those will only occur when a `GRanges` is returned.

`mapToTranscripts` and `mapFromTranscripts` return `GRanges` objects that vary in length similar to a `Hits` object. The result contains mapped records only; strand mismatch and out of bound ranges are not returned. `xHits` and `transcriptsHits` metadata columns (similar to the `queryHits` and `subjectHits` of a `Hits` object) indicate elements of `x` and `transcripts` used in the mapping.

When `intronJunctions` is TRUE, `mapToTranscripts` returns an extra metdata column named `intronic` to identify the intron ranges.

When mapping to transcript coordinates, seqlevels of the output are the names on the `transcripts` object and most often these will be transcript names. When mapping to the genome, seqlevels of the output are the seqlevels of `transcripts` which are usually chromosome names.

### Author(s)

V. Obenchain, M. Lawrence and H. Pagès

### See Also

- `?mapToAlignments` in the GenomicAlignments package for methods mapping between reads and genome space using a CIGAR alignment.

### Examples

    ## ---------------------------------------------------------------------
    ## A. Basic Use
    ## ---------------------------------------------------------------------

    ## ------------------------------------
    ## (i) Map from genome to transcript:

    ## The seqnames of the output are the transcript names, not chromosomes. For
    ## this reason 'transcripts' must be named.
    x <- GRanges("A", IRanges(16, 18))
    gr1 <- GRanges("A", IRanges(1, 10, names="tx_a"))
    gr2 <- GRanges("A", IRanges(15, 20, names="tx_b"))

    ## 'transcripts' as GRanges:
    mapToTranscripts(x, gr2)

    ## 'transcripts' as GRangesList:
    mapToTranscripts(x, GRangesList("tx_c" = c(gr1, gr2)))

    ## Round trip from genomic -> transcript -> genomic coordinates:
    tx_coord <- mapToTranscripts(x, gr2)
    mapFromTranscripts(tx_coord, gr2)

    ## ------------------------------------
    ## (ii) Map from transcript to genome:

    ## A prerequisite for mapping from transcript -> genome is that the seqname
    ## of the range in 'x' match the name of the range in 'transcripts'. Here
    ## the seqname of 'x' is "TX_1" and mapping is only attempted with the second
    ## range in 'gr':
    x <- GRanges("TX_1", IRanges(5, 10))
    gr <- GRanges("chr3", IRanges(c(1, 1), width=50, names=c("TX_2", "TX_1")))
    mapFromTranscripts(x, gr)

    ## ------------------------------------
    ## (iii) Element-wise versions:

    ## Recycling is supported when length(transcripts) == 1; otherwise the
    ## lengths of 'x' and 'transcripts' must be the same.
    x <- GRanges("A", IRanges(c(1, 5, 10), width=1))
    transcripts <- GRanges("A", IRanges(4, 7))
    pmapToTranscripts(x, transcripts)

    ## ---------------------------------------------------------------------
    ## B. Map local sequence locations to the genome
    ## ---------------------------------------------------------------------

    ## NAGNAG alternative splicing plays an essential role in biological processes
    ## and represents a highly adaptable system for posttranslational regulation
    ## of gene function. The majority of NAGNAG studies largely focus on messenger
    ## RNA. A study by Sun, Lin, and Yan
    ## (http://www.hindawi.com/journals/bmri/2014/736798/) demonstrated that
    ## NAGNAG splicing is also operative in large intergenic noncoding RNA
    ## (lincRNA).

    ## One finding of interest was that linc-POLR3G-10 exhibited two NAGNAG
    ## acceptors located in two distinct transcripts: TCONS_00010012 and
    ## TCONS_00010010.

    ## Extract the exon coordinates of TCONS_00010012 and TCONS_00010010:
    lincrna <- c("TCONS_00010012", "TCONS_00010010")
    library(TxDb.Hsapiens.UCSC.hg19.lincRNAsTranscripts)
    txdb <- TxDb.Hsapiens.UCSC.hg19.lincRNAsTranscripts
    exons <- exonsBy(txdb, by="tx", use.names=TRUE)[lincrna]
    exons

    ## The two NAGNAG acceptors were identified in the upstream region of
    ## the fourth and fifth exons located in TCONS_00010012.
    ## Extract the sequences for transcript TCONS_00010012:
    library(BSgenome.Hsapiens.UCSC.hg19)
    genome <- BSgenome.Hsapiens.UCSC.hg19
    exons_seq <- getSeq(genome, exons[[1]])

    ## TCONS_00010012 has 4 exons:
    exons_seq

    ## The most common triplet among the lincRNA sequences was CAG. Identify
    ## the location of this pattern in all exons.
    cag_loc <- vmatchPattern("CAG", exons_seq)

    ## Convert the first occurance of CAG in each exon back to genome coordinates.
    first_loc <- do.call(c, sapply(cag_loc, "[", 1, simplify=TRUE))
    pmapFromTranscripts(first_loc, exons[[1]])

    ## -----------------------------------------------------------------------
    ## C. Map 3'UTR variants to genome coordinates
    ## -----------------------------------------------------------------------

    ## A study by Skeeles et. al (PLoS ONE 8(3): e58609. doi:
    ## 10.1371/journal.pone.0058609) investigated the impact of 3'UTR variants
    ## on the expression of cancer susceptibility genes.

    ## 8 candidate miRNA genes on chromosome 12 were used to test for
    ## differential luciferase expression in mice. In Table 2 of the manuscript
    ## variant locations are given as nucleotide position within the gene.
    geneNames <- c("Bcap29", "Dgkb", "Etv1", "Hbp1", "Hbp1", "Ifrd1",
                   "Ifrd1", "Pik3cg", "Pik3cg", "Tspan13", "Twistnb")
    starts <- c(1409, 3170, 3132, 2437, 2626, 3239, 3261, 4947, 4979, 958, 1489)
    snps <- GRanges(geneNames, IRanges(starts, width=1))

    ## To map these transcript-space coordinates to the genome we need gene ranges
    ## in genome space.
    library(org.Mm.eg.db)
    geneid <- select(org.Mm.eg.db, unique(geneNames), "ENTREZID", "SYMBOL")
    geneid

    ## Extract the gene regions:
    library(TxDb.Mmusculus.UCSC.mm10.knownGene)
    txdb <- TxDb.Mmusculus.UCSC.mm10.knownGene
    genes <- genes(txdb)[geneid$ENTREZID]

    ## A prerequesite of the mapping from transcript space to genome space
    ## is that seqnames in 'x' match names in 'transcripts'. Rename
    ## 'genes' with the appropriate gene symbol.
    names(genes) <- geneid$SYMBOL

    ## The xHits and transcriptsHits metadta columns indicate which ranges in
    ## 'snps' and 'genes' were involved in the mapping.
    mapFromTranscripts(snps, genes)

    ## -----------------------------------------------------------------------
    ## D. Map dbSNP variants to cds or cDNA coordinates
    ## -----------------------------------------------------------------------

    ## The GIPR gene encodes a G-protein coupled receptor for gastric inhibitory
    ## polypeptide (GIP). Originally GIP was identified to inhibited gastric acid
    ## secretion and gastrin release but was later demonstrated to stimulate
    ## insulin release in the presence of elevated glucose.

    ## In this example 5 SNPs located in the GIPR gene are mapped to cDNA
    ## coordinates. A list of SNPs in GIPR can be downloaded from dbSNP or NCBI.
    rsids <- c("rs4803846", "rs139322374", "rs7250736", "rs7250754", "rs9749185")

    ## Extract genomic coordinates with a SNPlocs package.
    library(SNPlocs.Hsapiens.dbSNP141.GRCh38)
    snps <- snpid2grange(SNPlocs.Hsapiens.dbSNP141.GRCh38, rsids)

    ## Gene regions of GIPR can be extracted from a TxDb package of compatible
    ## build. The TxDb package uses Entrez gene identifiers and GIPR is a gene
    ## symbol. Conversion between gene symbols and Entrez gene IDs is done by
    ## calling select() on an organism db package.
    library(org.Hs.eg.db)
    geneid <- select(org.Hs.eg.db, "GIPR", "ENTREZID", "SYMBOL")

    ## The transcriptsBy() extractor returns a range for each transcript that
    ## includes the UTR and exon regions (i.e., cDNA).
    library(TxDb.Hsapiens.UCSC.hg38.knownGene)
    txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene
    txbygene <- transcriptsBy(txdb, "gene")
    cDNA <- txbygene[geneid$ENTREZID]
    cDNA

    ## Before mapping, the chromosome names (seqlevels) in the two objects must
    ## be harmonized. The style for 'snps' is dbSNP and 'cDNA' is UCSC.
    seqlevelsStyle(snps)
    seqlevelsStyle(cDNA)

    ## Modify the style and genome in 'snps' to match 'cDNA'.
    seqlevelsStyle(snps) <- seqlevelsStyle(cDNA)
    genome(snps) <- genome(cDNA)

    ## The 'cDNA' object is a GRangesList of length 1. This single list element
    ## contains the cDNA range for 4 different transcripts. To map to each
    ## transcript individually 'cDNA' must be unlisted before mapping.

    ## Map all 5 SNPS to all 4 transcripts:
    mapToTranscripts(snps, unlist(cDNA))

    ## Map the first SNP to transcript uc002pct.2 and the second to uc002pcu.2.
    pmapToTranscripts(snps[1:2], unlist(cDNA)[1:2])

    ## The cdsBy() extractor returns coding regions by gene or by transcript.
    ## Extract the coding regions for transcript uc002pct.2.
    cds <- cdsBy(txdb, "tx", use.names=TRUE)["uc002pct.2"]
    cds

    ## The 'cds' object is a GRangesList of length 1 containing all cds ranges
    ## for the single transcript uc002pct.2.

    ## To map to the concatenated group of ranges leave 'cds' as a GRangesList.
    mapToTranscripts(snps, cds)

    ## Only the second SNP could be mapped. Unlisting the 'cds' object maps the
    ## SNPs to the individual cds ranges (vs the concatenated range).
    mapToTranscripts(snps[2], unlist(cds))

    ## The location is the same because the SNP hit the first cds range. If the
    ## transcript were on the "-" strand the difference in concatenated vs
    ## non-concatenated position would be more obvious.

    ## Change strand:
    strand(cds) <- strand(snps) <- "-"
    mapToTranscripts(snps[2], unlist(cds))

[Package GenomicFeatures version 1.30.3 Index]