Additional file 1: Table S1. of Longitudinal analysis of the lung microbiota of cynomolgous macaques during long-term SHIV infection

Estimates from a linear mixed model comparing taxa abundance between COPD+ and COPD− samples. Fold change estimates and basic statistics of several OTUs comparing COPD+ and COPD− samples 20 days after infection. In the linear mixed model, we accounted for individual monkey effects, days sampled, and included normalization factors. We filtered OTUs to those with at least 100 counts and declared OTUs significant if lower and upper log fold change estimates agreed in directionality. Row colors represent enrichment, green in COPD− and red in COPD+ samples. Table S2 Smoothing Spline ANOVA estimates comparing COPD+ and COPD− taxa abundances through time. Smoothing Spline ANOVA estimates of the difference in genera abundances between COPD+ and COPD− groups through time. To test for differentially abundant time intervals, we fit a smoothing spline and calculated 95 % Bayesian confidence intervals under the SSANOVA framework. The SSANOVA procedure also included time, obstruction status and their interaction. We estimate significance using a permutation procedure and calculate significance with area under the curve as our test statistic. Row colors represent enrichment, green in COPD− and red in COPD+ samples. (XLSX 52 kb)

本研究基于线性混合模型（linear mixed model），对慢性阻塞性肺疾病（Chronic Obstructive Pulmonary Disease, COPD）阳性（COPD+）与慢性阻塞性肺疾病阴性（COPD−）样本的微生物类群丰度开展比较分析。本研究针对感染后20天的COPD+与COPD−样本，对若干操作分类单元（Operational Taxonomic Units, OTU）的倍数变化估计值及基础统计量进行了对比。在线性混合模型中，我们控制了个体猕猴的个体效应与采样天数，并纳入标准化因子。我们将OTU筛选为计数至少达100的类群，当对数倍数变化估计值的置信区间上下限方向一致时，即判定该OTU具有统计学显著性。行颜色代表类群富集情况：绿色代表在COPD−样本中富集，红色代表在COPD+样本中富集。

表S2：平滑样条方差分析（Smoothing Spline ANOVA, SSANOVA）针对不同时间点COPD+与COPD−样本的微生物类群丰度比较所得的估计结果。该表呈现了平滑样条方差分析对COPD+与COPD−组间属水平微生物类群丰度随时间变化的差异估计结果。为检验存在丰度差异的时间区间，我们拟合了平滑样条模型，并在SSANOVA框架下计算了95%贝叶斯置信区间。该SSANOVA分析同时纳入了时间、阻塞状态及其交互项作为协变量。我们采用置换检验法估计统计学显著性，并以曲线下面积作为检验统计量计算显著性水平。行颜色代表类群富集情况：绿色代表在COPD−样本中富集，红色代表在COPD+样本中富集。（XLSX格式，大小52 KB）