GCalignR: An R package for aligning gas-chromatography data for ecological and evolutionary studies

Chemical cues are arguably the most fundamental means of animal communication and play an important role in mate choice and kin recognition. Consequently, there is growing interest in the use of gas chromatography (GC) to investigate the chemical basis of eco-evolutionary interactions. Both GC-MS (mass spectrometry) and FID (flame ionization detection) are commonly used to characterise the chemical composition of biological samples such as skin swabs. The resulting chromatograms comprise peaks that are separated according to their retention times and which represent different substances. Across chromatograms of different samples, homologous substances are expected to elute at similar retention times. However, random and often unavoidable experimental variation introduces noise, making the alignment of homologous peaks challenging, particularly with GC-FID data where mass spectral data are lacking. Here we present GCalignR, a user-friendly R package for aligning GC-FID data based on retention times. The package was developed specifically for ecological and evolutionary studies that seek to investigate similarity patterns across multiple and often highly variable biological samples, for example representing different sexes, age classes or reproductive stages. The package also implements dynamic visualisations to facilitate inspection and fine-tuning of the resulting alignments and can be integrated within a broader workflow in R to facilitate downstream multivariate analyses. We demonstrate an example workflow using empirical data from Antarctic fur seals and explore the impact of user-defined parameter values by calculating alignment error rates for multiple datasets. The resulting alignments had low error rates for most of the explored parameter space and we could also show that GCalignR performed equally well or better than other available software. We hope that GCalignR will help to simplify the processing of chemical datasets and improve the standardization and reproducibility of chemical analyses in studies of animal chemical communication and related fields.

化学信号（chemical cues）无疑是动物交流最基础的方式之一，在配偶选择与亲缘识别中发挥着关键作用。因此，学界对利用气相色谱（gas chromatography, GC）探究生态-进化互作的化学基础的兴趣与日俱增。气相色谱-质谱联用（gas chromatography-mass spectrometry, GC-MS）与火焰离子化检测（flame ionization detection, FID）均为表征皮肤拭子等生物样本化学成分的常用手段。所得色谱图（chromatogram）包含按保留时间（retention time）分离的峰，每个峰对应一种不同的物质。在不同样本的色谱图中，同源物质（homologous substances）应在相近的保留时间处洗脱（elute）。然而，随机且通常难以避免的实验误差会引入噪声，使得同源峰的对齐工作极具挑战性，尤其是在缺乏质谱数据的GC-FID数据中。本研究介绍GCalignR：一款基于保留时间对齐GC-FID数据的易用R包。该包专为生态与进化研究开发，旨在探究多样且常具有高度变异性的生物样本（例如不同性别、年龄层或生殖阶段的样本）间的相似性模式。该包还支持动态可视化功能，便于用户检视并微调所得对齐结果，同时可集成于R的更广泛工作流中，以助力后续多变量分析。我们利用南极海狗的实测数据展示了一套示例工作流，并通过计算多个数据集的对齐错误率，探究了用户自定义参数值的影响。在多数探索过的参数范围内，所得对齐结果的错误率均较低；同时我们还证实，GCalignR的表现与现有其他软件相当，甚至更优。我们期望GCalignR能够简化化学数据集的处理流程，提升动物化学交流及相关领域研究中化学分析的标准化与可重复性水平。