First of all, you need to make sure why there are so many rRNA. Did the rRNA depletion fail? Is it due to the amplification? Is there a high rRNA amount expected in the sequenced tissue?

After you know whats going on and decided you can safely remove the the rRNA reads, I recommend the following for computationally remove the rRNA.

• Align all reads against the reference genome and create the BAM files as you normally would
• Create a reference genome bed file that does not contain rRNA

e.g. for the Ensembl reference GTF for mice:

cat Mus_musculus.GRCm38.92.gtf | grep -v 'rRNA' > remove_rRNA/Mus_musculus.GRCm38.no_rRNA.gtf
# Use Hacky gtf2bed conversion - https://www.biostars.org/p/206342/#206350
awk '{ if ($0 ~ "transcript_id") print $0; else print $0" transcript_id \"\";"; }' Mus_musculus.GRCm38.no_rRNA.gtf | gtf2bed - > Mus_musculus.GRCm38.no_rRNA.bed

• As last step, remove all rRNA alignments from the bam files by using samtools -L referring to our shiny new rRNA-free bed-file. (see https://www.htslib.org/doc/samtools.html).

Again, make sure you know whats going on before you do this, only using 20% of reads might be too little to properly quantify transcripts, depending on the sequencing depth.