ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
Bioinformatics. 2021 Dec 11;37(24):4719-4726. doi: 10.1093/bioinformatics/btab563.
The output of electrospray ionization-liquid chromatography mass spectrometry (ESI-LC-MS) is influenced by multiple sources of noise and major contributors can be broadly categorized as baseline, random and chemical noise. Noise has a negative impact on the identification and quantification of peptides, which influences the reliability and reproducibility of MS-based proteomics data. Most attempts at denoising have been made on either spectra or chromatograms independently, thus, important 2D information is lost because the mass-to-charge ratio and retention time dimensions are not considered jointly.
This article presents a novel technique for denoising raw ESI-LC-MS data via 2D undecimated wavelet transform, which is applied to proteomics data acquired by data-independent acquisition MS (DIA-MS). We demonstrate that denoising DIA-MS data results in the improvement of peptide identification and quantification in complex biological samples.
The software is available on Github (https://github.com/CMRI-ProCan/CRANE). The datasets were obtained from ProteomeXchange (Identifiers-PXD002952 and PXD008651). Preliminary data and intermediate files are available via ProteomeXchange (Identifiers-PXD020529 and PXD025103).
Supplementary data are available at Bioinformatics online.
电喷雾电离-液相色谱质谱（ESI-LC-MS）的输出受到多种噪声源的影响，主要贡献者可大致分为基线噪声、随机噪声和化学噪声。噪声对肽的鉴定和定量有负面影响，这会影响基于 MS 的蛋白质组学数据的可靠性和可重复性。大多数去噪尝试都是在单独的光谱或色谱图上进行的，因此，由于未考虑质荷比和保留时间维度，重要的 2D 信息丢失了。
本文提出了一种通过二维非抽取小波变换对原始 ESI-LC-MS 数据进行去噪的新方法，该方法应用于数据非依赖性采集 MS（DIA-MS）获得的蛋白质组学数据。我们证明，对 DIA-MS 数据进行去噪可改善复杂生物样本中肽的鉴定和定量。
该软件可在 Github（https://github.com/CMRI-ProCan/CRANE）上获得。数据集来自 ProteomeXchange（标识符-PXD002952 和 PXD008651）。初步数据和中间文件可通过 ProteomeXchange（标识符-PXD020529 和 PXD025103）获得。
补充数据可在 Bioinformatics 在线获得。
