The Subread featureCounts functions works great for enumerating unique or multi-mapped reads to genes, but is not the best tool for estimating counts for splice variants due to the added complexity of reads aligning across and between splice junctions for splice variants that contain the same exons. Tools such as eXpress, Sailfish, Salmon, or RSEM that use an expectation-maximization algorithm to estimate counts for splice variants are probably your best bet, but those tools are outside the realm of both R and Bioconductor. If you have transcriptome aligned bam files, eXpress and RSEM will work well for you. If you have a genome aligned bam file, Salmon will serve you well. Alternatively, Sailfish can operate on unaligned fastq files and you can generate custom indexes of known and putative splice variants (splice variants reported in literature that are not present in databases such as Ensembl) as long as you have the fasta sequence. Good luck and I hope this helps.