MAJIQ V3 发布：引入剪接图代数并改进内含子保留建模
MAJIQ V3: Scalable and accurate RNA splicing analysis with splicegraph algebra and improved intron retention modeling
MAJIQ V3 发布，在 V1、V2 基础上新增剪接图代数功能，并重写量化算法以提升速度和准确性。新版本支持合并剪接图、按剪接图对 RNA-seq 实验做剪接定量，以及比较两个剪接图，从而支持新的 RNA 剪接分析模式。内含子保留检测改用新的概率模型，纠正了此前启发式方法带来的偏差。该版本还完整重写了 I/O 模式、数据结构和算法。作者用 GTEx 和 LRGASP 数据在不同数据集规模的分析场景中展示了新版本的表现。
来源：NAR Genomics and Bioinformatics · doi.org
RNA splicing plays important roles in cell-type-specific expression of gene isoforms and is causally linked to numerous diseases. Previously, our group developed Modeling Alternative Junction Inclusion Quantification (MAJIQ) V1 and V2 for RNA splicing detection, quantification, and visualization from RNA sequencing. Here we report an update, MAJIQ V3, that offers critical new functionality together with faster and more accurate quantification algorithms. MAJIQ V3 enables users to combine splicegraphs, quantify splicing from an RNA-seq experiment with respect to a splicegraph, and compare one splicegraph to another, enabling new patterns of performant RNA splicing analyses from RNA-seq. MAJIQ V3 utilizes a new probabilistic model for detecting intron retention, correcting a bias that resulted from previous heuristics. MAJIQ V3 benefits from a full re-implementation utilizing more performant I/O patterns, data structures, and algorithms. We demonstrate the benefits of MAJIQ V3 using GTEx and LRGASP data for different analysis scenarios involving different dataset sizes.