readGFF {rtracklayer} | R Documentation

## Reads a file in GFF format

### Description

Reads a file in GFF format and creates a data frame or DataFrame object from it. This is a low-level function that should not be called by user code.

### Usage

    readGFF(filepath, version=0,
            columns=NULL, tags=NULL, filter=NULL, nrows=-1,
            raw_data=FALSE)

    GFFcolnames(GFF1=FALSE)

### Arguments

`filepath` | A single string containing the path or URL to the file to read. Alternatively can be a connection.
`version` | `readGFF` should do a pretty descent job at detecting the GFF version. Use this argument only if it doesn't or if you want to force it to parse and import the file as if its 9-th column was in a different format than what it really is (e.g. specify `version=1` on a GTF or GFF3 file to interpret its 9-th column as the `"group"` column of a GFF1 file). Supported versions are 1, 2, and 3.
`columns` | The standard GFF columns to load. All of them are loaded by default.
`tags` | The tags to load. All of them are loaded by default.
`filter` |
`nrows` | `-1` or the maximum number of rows to read in (after filtering).
`raw_data` |
`GFF1` |

### Value

A DataFrame with columns corresponding to those in the GFF.

### Author(s)

H. Pages

### See Also

- `import` for importing a GFF file as a GRanges object.

- `makeGRangesFromDataFrame` in the GenomicRanges package for making a GRanges object from a data frame or DataFrame object.

- `makeTxDbFromGFF` in the GenomicFeatures package for importing a GFF file as a TxDb object.

- The DataFrame class in the S4Vectors package.

### Examples

    ## Standard GFF columns.
    GFFcolnames()
    GFFcolnames(GFF1=TRUE)  # "group" instead of "attributes"

    tests_dir <- system.file("tests", package="rtracklayer")
    test_gff3 <- file.path(tests_dir, "genes.gff3")

    ## Load everything.
    df0 <- readGFF(test_gff3)
    head(df0)

    ## Load some tags only (in addition to the standard GFF columns).
    my_tags <- c("ID", "Parent", "Name", "Dbxref", "geneID")
    df1 <- readGFF(test_gff3, tags=my_tags)
    head(df1)

    ## Load no tags (in that case, the "attributes" standard column
    ## is loaded).
    df2 <- readGFF(test_gff3, tags=character(0))
    head(df2)

    ## Load some standard GFF columns only (in addition to all tags).
    my_columns <- c("seqid", "start", "end", "strand", "type")
    df3 <- readGFF(test_gff3, columns=my_columns)
    df3
    table(df3$seqid, df3$type)
    makeGRangesFromDataFrame(df3, keep.extra.columns=TRUE)

    ## Combine use of 'columns' and 'tags' arguments.
    readGFF(test_gff3, columns=my_columns, tags=c("ID", "Parent", "Name"))
    readGFF(test_gff3, columns=my_columns, tags=character(0))

    ## Use the 'filter' argument to load only features of type "gene"
    ## or "mRNA" located on chr10.
    my_filter <- list(type=c("gene", "mRNA"), seqid="chr10")
    readGFF(test_gff3, filter=my_filter)
    readGFF(test_gff3, columns=my_columns, tags=character(0), filter=my_filter)

[Package rtracklayer version 1.48.0 Index]