readTxResults {scater} | R Documentation |
After generating transcript/feature abundance results using kallisto, Salmon,
Sailfish or RSEM for a batch of samples, read these abundance values into an
SCESet
object.
readTxResults(samples = NULL, files = NULL, log = NULL, type = "kallisto", txOut = TRUE, logExprsOffset = 1, verbose = TRUE, ...)
samples |
character vector providing a set of sample names to use for the abundance results. |
files |
character vector providing a set of filenames containing kallisto abundance results to be read in. |
log |
list (optional), generated by |
type |
character, the type of software used to generate the abundances.
Options are "kallisto", "salmon", "sailfish", "rsem". This argument is passed
to |
txOut |
logical, whether the function should just output transcript-level (default TRUE) |
logExprsOffset |
numeric scalar, providing the offset used when doing
log2-transformations of expression data to avoid trying to take logs of zero.
Default offset value is |
verbose |
logical, should function provide output about progress? |
... |
optional parameters passed to |
Note: tximport does not import bootstrap estimates from kallisto,
Salmon, or Sailfish. If you want bootstrap estimates use the
readKallistoResults
or readSalmonResults
functions.
an SCESet
object containing the abundance, count and feature
length data from the supplied samples.
Soneson C, Love MI, Robinson MD. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Res. 2015;4: 1521.
## Not run: ## this example requires installation of the tximportData package from ## Bioconductor library(tximportData) dir <- system.file("extdata", package = "tximportData") list.files(dir) samples <- read.table(file.path(dir, "samples.txt"), header = TRUE) samples directories <- file.path(dir, "kallisto", samples$run) names(directories) <- paste0("sample", 1:6) files <- file.path(directories, "abundance.tsv") sce_example <- readTxResults(samples = names(directories), files = files, type = "kallisto") ## for faster reading of results use the read_tsv function from the readr pkg library(readr) sce_example <- readTxResults(samples = names(directories), files = files, type = "kallisto", reader = read_tsv) ## End(Not run)