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Splice_sim: a nucleotide conversion-enabled RNA-seq simulation and evaluation framework
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DOI：10.1186/s13059-024-03313-8.png)
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Abstract
En 中文
Nucleotide conversion RNA sequencing techniques interrogate chemical RNA modifications in cellular transcripts, resulting in mismatch-containing reads. Biases in mapping the resulting reads to reference genomes remain poorly understood. We present splice_sim, a splice-aware RNA-seq simulation and evaluation pipeline that introduces user-defined nucleotide conversions at set frequencies, creates mixture models of converted and unconverted reads, and calculates mapping accuracies per genomic annotation. By simulating nucleotide conversion RNA-seq datasets under realistic experimental conditions, including metabolic RNA labeling and RNA bisulfite sequencing, we measure mapping accuracies of state-of-the-art spliced-read mappers for mouse and human transcripts and derive strategies to prevent biases in the data interpretation.
Keywords:
Nucleotide conversion sequencing
Metabolic RNA labeling
SLAMseq
RNA-BS-seq
3 ' end sequencing
Spliced read mapping
Read mapping accuracy
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