ABSTRACT
RNA-mediated oligonucleotide Annealing, Selection, and Ligation (RASL-seq) is a method to measure the expression of hundreds of genes in thousands of samples for a fraction of the cost of competing methods. However, enzymatic inefficiencies of the original protocol and the lack of open source software to design and analyze RASL-seq experiments have limited its widespread adoption. We recently reported an Rnl2-based RASL-seq protocol (RRASL-seq) that offers improved ligation efficiency and a probe decoy strategy to optimize sequencing usage. Here, we describe an open source software package, RASLseqTools, that provides computational methods to design and analyze RASL-seq experiments. Furthermore, using data from a large RRASL-seq experiment, we demonstrate how normalization methods can be used for characterizing and correcting experimental, sequencing, and alignment error. We provide evidence that the three principal predictors of RRASL-seq reproducibility are barcode/probe sequence dissimilarity, sequencing read depth, and normalization strategy. Using dozens of technical and biological replicates across multiple 384-well plates, we find simple normalization strategies yield similar results to more statistically complex methods.