BACKGROUND Methylated RNA immunoprecipitation sequencing (MeRIP-Seq) is a popular sequencing method for studying RNA modifications and, in particular, for N6-methyladenosine (m6A), the most abundant RNA methylation modification found in various species. The detection of enriched regions is a main challenge of MeRIP-Seq analysis, however current tools either require a long time or do not fully utilize features of RNA sequencing such as strand information which could cause ambiguous calling. On the other hand, with more attention on the treatment experiments of MeRIP-Seq, biologists need intuitive evaluation on the treatment effect from comparison. Therefore, efficient and user-friendly software that can solve these tasks must be developed. RESULTS We developed a software named "model-based analysis and inference of MeRIP-Seq (MoAIMS)" to detect enriched regions of MeRIP-Seq and infer signal proportion based on a mixture negative-binomial model. MoAIMS is designed for transcriptome immunoprecipitation sequencing experiments; therefore, it is compatible with different RNA sequencing protocols. MoAIMS offers excellent processing speed and competitive performance when compared with other tools. When MoAIMS is applied to studies of m6A, the detected enriched regions contain known biological features of m6A. Furthermore, signal proportion inferred from MoAIMS for m6A treatment datasets (perturbation of m6A methyltransferases) showed a decreasing trend that is consistent with experimental observations, suggesting that the signal proportion can be used as an intuitive indicator of treatment effect. CONCLUSIONS MoAIMS is efficient and easy-to-use software implemented in R. MoAIMS can not only detect enriched regions of MeRIP-Seq efficiently but also provide intuitive evaluation on treatment effect for MeRIP-Seq treatment datasets.

中文翻译：

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MoAIMS：用于检测 MeRIP-Seq 富集区域的高效软件。

背景甲基化 RNA 免疫沉淀测序 (MeRIP-Seq) 是一种流行的测序方法，用于研究 RNA 修饰，尤其是 N6-甲基腺苷 (m6A)，这是在各种物种中发现的最丰富的 RNA 甲基化修饰。富集区域的检测是 MeRIP-Seq 分析的主要挑战，但是当前的工具要么需要很长时间，要么没有充分利用 RNA 测序的特征，例如链信息，这可能会导致模糊的调用。另一方面，随着对 MeRIP-Seq 处理实验的更多关注，生物学家需要从比较中直观地评估处理效果。因此，必须开发能够解决这些任务的高效且用户友好的软件。结果 我们开发了一款名为“基于模型的 MeRIP-Seq 分析和推理（MoAIMS）”的软件 检测 MeRIP-Seq 的富集区域并基于混合负二项式模型推断信号比例。MoAIMS 专为转录组免疫沉淀测序实验而设计；因此，它与不同的 RNA 测序协议兼容。与其他工具相比，MoAIMS 可提供出色的处理速度和具有竞争力的性能。当 MoAIMS 应用于 m6A 的研究时, 检测到的富集区域包含 m6A 的已知生物学特征。此外，从 MoAIMS 推断出的 m6A 处理数据集的信号比例（m6A 甲基转移酶的扰动）显示出下降趋势，这与实验观察结果一致，表明信号比例可以用作治疗效果的直观指标。结论 MoAIMS 是在 R 中实现的高效且易于使用的软件。