BedTool.cut(indexes, stream=False)[source]

Analagous to unix cut.

Similar to unix cut except indexes are 0-based, must be a list and the columns are returned in the order requested.

This method returns a BedTool of results, which means that the indexes returned must be valid GFF/GTF/BED/SAM features.

If you would like arbitrary columns – say, just chrom and featuretype of a GFF, which would not comprise a valid feature – then instead of this method, simply use indexes on each feature, e.g,

>>> gff = pybedtools.example_bedtool('d.gff')
>>> results = [(f[0], f[2]) for f in gff]

In addition, indexes can contain keys of the GFF/GTF attributes, in which case the values are returned. e.g. ‘gene_name’ will return the corresponding name from a GTF, or ‘start’ will return the start attribute of a BED Interval.