RTCpredictor: identification of read-through chimeric RNAs from RNA sequencing data.
Sandeep SinghXinrui ShiSamuel HaddoxJustin ElfmanSyed Basil AhmadSarah LynchTommy ManleyClaire PiczakChristopher PhungYunan SunAadi SharmaHui LiPublished in: Briefings in bioinformatics (2024)
Read-through chimeric RNAs are being recognized as a means to expand the functional transcriptome and contribute to cancer tumorigenesis when mis-regulated. However, current software tools often fail to predict them. We have developed RTCpredictor, utilizing a fast ripgrep tool to search for all possible exon-exon combinations of parental gene pairs. We also added exonic variants allowing searches containing common SNPs. To our knowledge, it is the first read-through chimeric RNA specific prediction method that also provides breakpoint coordinates. Compared with 10 other popular tools, RTCpredictor achieved high sensitivity on a simulated and three real datasets. In addition, RTCpredictor has less memory requirements and faster execution time, making it ideal for applying on large datasets.
Keyphrases
- cell therapy
- rna seq
- genome wide
- single cell
- single molecule
- copy number
- papillary thyroid
- stem cells
- mesenchymal stem cells
- gene expression
- dna methylation
- working memory
- transcription factor
- squamous cell
- big data
- squamous cell carcinoma
- machine learning
- lymph node metastasis
- artificial intelligence
- bioinformatics analysis