We introduce a method for approximating posterior probabilities of phylogenetic trees and reconstructing ancestral sequences under models of sequence evolution with site-dependence, where standard phylogenetic likelihood computations (pruning) fail. Our approach uses a combined data-augmentation and importance sampling scheme. A key advantage of our approach is the ability to leverage existing highly optimized phylogenetic software. We apply our approach to the reconstruction of B cell receptor affinity maturation lineages from high-throughput repertoire sequencing data and evaluate the impact of incorporating site-dependence on the reconstruction accuracy of both trees and ancestral sequences. We show that accounting for context-dependence during inference always improves the estimates of both ancestral sequences and lineage trees on simulated datasets. We also examine the impact of incorporating priors based on VDJ recombination models, and find that they significantly improve ancestral sequence reconstruction in germline-encoded regions, but increase errors in non-templated nucleotides. We propose a modified, piecewise prior to address this demonstrate that it improves empirical reconstruction accuracy. We apply our approach to the analysis of the HIV broadly neutralizing antibodies DH270 and CH235 which are important targets of current vaccine design efforts.

翻译：我们提出了一种在具有位点依赖性的序列进化模型下近似系统发育树后验概率并重建祖先序列的方法，该模型下标准的系统发育似然计算（剪枝算法）会失效。我们的方法采用数据增强与重要性采样相结合的策略。该方法的一个关键优势在于能够利用现有高度优化的系统发育软件。我们将此方法应用于从高通量受体库测序数据重建B细胞受体亲和力成熟谱系，并评估纳入位点依赖性对系统发育树和祖先序列重建准确性的影响。我们证明在推断过程中考虑上下文依赖性始终能提升模拟数据集中祖先序列和谱系树估计的准确性。我们还研究了整合基于VDJ重组模型先验分布的影响，发现其能显著提升胚系编码区的祖先序列重建精度，但会增加非模板化核苷酸区域的误差。为此我们提出一种改进的分段先验分布，并证明其能提升实际重建精度。我们将该方法应用于分析HIV广谱中和抗体DH270和CH235，这些抗体是当前疫苗设计工作的重要靶标。