Harmanci Arif, Rozowsky Joel, Gerstein Mark
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.
Genome Biol. 2014;15(10):474. doi: 10.1186/s13059-014-0474-3.
We present MUSIC, a signal processing approach for identification of enriched regions in ChIP-Seq data, available atmusic.gersteinlab.org. MUSIC first filters the ChIP-Seq read-depth signal for systematic noise from non-uniformmappability, which fragments enriched regions. Then it performs a multiscale decomposition, using median filtering, identifying enriched regions at multiple length scales. This is useful given the wide range of scales probed in ChIP-Seq assays. MUSIC performs favorably in terms of accuracy and reproducibility compared with other methods.In particular, analysis of RNA polymerase II data reveals a clear distinction between the stalled and elongating forms of the polymerase.
我们展示了MUSIC,一种用于识别ChIP-Seq数据中富集区域的信号处理方法,可在music.gersteinlab.org上获取。MUSIC首先对ChIP-Seq读深度信号进行滤波,以去除来自非均匀映射性的系统噪声,这种噪声会使富集区域碎片化。然后,它使用中值滤波进行多尺度分解,在多个长度尺度上识别富集区域。鉴于ChIP-Seq分析中探测的尺度范围很广,这一点很有用。与其他方法相比,MUSIC在准确性和可重复性方面表现良好。特别是,对RNA聚合酶II数据的分析揭示了该聚合酶停滞形式和延伸形式之间的明显区别。