Hi,
In the lab we are analyzing tRNA-derived RNA fragments. My boss needs to quantify these fragments in different conditions (Presymptomatic ALS and Symptomatic ALS) to check if there are some fragments differentially expressed.
The model is Mus musculus (mm10).
The main problem is that most of the tRNA genes are redundants. Therefore, when the reads that were generated from these genes are mapped, the program (bowtie) assigns them randomly, or reports all the sites (depending on the configuration), causing bias in the cuatification.
Is there a less biased way for quantifying tRNA-derived RNA fragments?
Thanks in advance!!
In the lab we are analyzing tRNA-derived RNA fragments. My boss needs to quantify these fragments in different conditions (Presymptomatic ALS and Symptomatic ALS) to check if there are some fragments differentially expressed.
The model is Mus musculus (mm10).
The main problem is that most of the tRNA genes are redundants. Therefore, when the reads that were generated from these genes are mapped, the program (bowtie) assigns them randomly, or reports all the sites (depending on the configuration), causing bias in the cuatification.
Is there a less biased way for quantifying tRNA-derived RNA fragments?
Thanks in advance!!
Comment