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TSSi-an R package for transcription start site identification from 5' mRNA tag data

机译:TSSi-R软件包,用于从5'mRNA标签数据中识别转录起始位点

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摘要

High-throughput sequencing has become an essential experimental approach for the investigation of transcriptional mechanisms. For some applications like ChIP-seq, several approaches for the prediction of peak locations exist. However, these methods are not designed for the identification of transcription start sites (TSSs) because such datasets contain qualitatively different noise. In this application note, the R package TSSi is presented which provides a heuristic framework for the identification of TSSs based on 5' mRNA tag data. Probabilistic assumptions for the distribution of the data, i.e. for the observed positions of the mapped reads, as well as for systematic errors, i.e. for reads which map closely but not exactly to a real TSS, are made and can be adapted by the user. The framework also comprises a regularization procedure which can be applied as a preprocessing step to decrease the noise and thereby reduce the number of false predictions.
机译:高通量测序已成为研究转录机制的重要实验方法。对于ChIP-seq等某些应用,存在几种预测峰位置的方法。但是,这些方法不适用于识别转录起始位点(TSS),因为此类数据集包含定性不同的噪声。在本应用笔记中,提出了R包TSSi,它提供了一种启发式框架,用于基于5'mRNA标签数据识别TSS。做出了数据分布的概率假设,即对于所映射的读段的观察位置,以及对于系统错误,即对于紧密但不精确地映射到实际TSS的读段的概率假设,并且用户可以对其进行调整。该框架还包括可作为预处理步骤应用的正则化过程,以减少噪声并由此减少错误预测的数量。

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