Learn R Programming

tximport (version 1.0.3)

tximport: Import transcript-level abundances and estimated counts for gene-level analysis packages

Description

tximport imports transcript-level estimates from various external software and optionally summarizes abundances, counts, and transcript lengths to the gene-level (default) or outputs transcript-level matrices (see txOut argument). While tximport summarizes to the gene-level by default, the user can also perform the import and summarization steps manually, by specifing txOut=TRUE and then using the function summarizeToGene. Note however that this is equivalent to tximport with txOut=FALSE (the default).

Usage

tximport(files, type = c("none", "kallisto", "salmon", "sailfish", "rsem"), txIn = TRUE, txOut = FALSE, countsFromAbundance = c("no", "scaledTPM", "lengthScaledTPM"), tx2gene = NULL, reader = read.delim, geneIdCol, txIdCol, abundanceCol, countsCol, lengthCol, importer, collatedFiles, ignoreTxVersion = FALSE)
summarizeToGene(txi, tx2gene, ignoreTxVersion = FALSE, countsFromAbundance = c("no", "scaledTPM", "lengthScaledTPM"))

Arguments

files
a character vector of filenames for the transcript-level abundances
type
character, the type of software used to generate the abundances. Options are "kallisto", "salmon", "sailfish", "rsem". This argument is used to autofill the arguments below (geneIdCol, etc.) "none" means that the user will specify these columns.
txIn
logical, whether the incoming files are transcript level (default TRUE)
txOut
logical, whether the function should just output transcript-level (default FALSE)
countsFromAbundance
character, either "no" (default), "scaledTPM", or "lengthScaledTPM", for whether to generate estimated counts using abundance estimates scaled up to library size (scaledTPM) or additionally scaled using the average transcript length over samples and the library size (lengthScaledTPM). if using scaledTPM or lengthScaledTPM, then the counts are no longer correlated with average transcript length, and so the length offset matrix should not be used.
tx2gene
a two-column data.frame linking transcript id (column 1) to gene id (column 2). the column names are not relevant, but this column order must be used. this argument is required for gene-level summarization for methods that provides transcript-level estimates only (kallisto, Salmon, Sailfish)
reader
a function to replace read.delim in the pre-set importer functions, for example substituting read_tsv from the readr package will substantially speed up tximport
geneIdCol
name of column with gene id. if missing, the gene2tx argument can be used
txIdCol
name of column with tx id
abundanceCol
name of column with abundances (e.g. TPM or FPKM)
countsCol
name of column with estimated counts
lengthCol
name of column with feature length information
importer
a function used to read in the files
collatedFiles
a character vector of filenames for software which provides abundances and counts in matrix form (e.g. Cufflinks). The files should be, in order, abundances, counts, and a third file with length information
ignoreTxVersion
logical, whether to split the tx id on the '.' character to remove version information, for easier matching with the tx id in gene2tx (default FALSE)
txi
list of matrices of trancript-level abundances, counts, and lengths produced by tximport, only used by summarizeToGene

Value

a simple list with matrices: abundance, counts, length. A final element 'countsFromAbundance' carries through the character argument used in the tximport call. The length matrix contains the average transcript length for each gene which can be used as an offset for gene-level analysis. Note: tximport does not import bootstrap estimates from kallisto, Salmon, or Sailfish.

Functions

  • tximport: Import tx-level quantifications and summarize abundances, counts and lengths to gene-level (default) or simply output tx-level matrices
  • summarizeToGene: Summarize tx-level matrices to gene-level

Details

Solutions to the error "tximport failed at summarizing to the gene-level":

  1. provide a tx2gene data.frame linking transcripts to genes (more below)
  2. avoid gene-level summarization by specifying txOut=TRUE
  3. set geneIdCol to an appropriate column in the files

See vignette('tximport') for example code for generating a tx2gene data.frame from a TxDb object. Note that the keys and select functions used to create the tx2gene object are documented in the man page for AnnotationDb-class objects in the AnnotationDbi package (TxDb inherits from AnnotationDb). For further details on generating TxDb objects from various inputs see vignette('GenomicFeatures') from the GenomicFeatures package.

Version support: The last known supported versions of the external quantifiers are: kallisto 0.42.4, Salmon 0.6.0, Sailfish 0.9.0, RSEM 1.2.11.

References

Charlotte Soneson, Michael I. Love, Mark D. Robinson (2015): Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Research. http://dx.doi.org/10.12688/f1000research.7563.1

Examples

Run this code

# load data for demonstrating tximport
# note that the vignette shows more examples
# including how to read in files quickly using the readr package

library(tximportData)
dir <- system.file("extdata", package="tximportData")
samples <- read.table(file.path(dir,"samples.txt"), header=TRUE)
files <- file.path(dir,"salmon", samples$run, "quant.sf")
names(files) <- paste0("sample",1:6)

# tx2gene links transcript IDs to gene IDs for summarization
tx2gene <- read.csv(file.path(dir, "tx2gene.csv"))

txi <- tximport(files, type="salmon", tx2gene=tx2gene)

Run the code above in your browser using DataLab