TWIRLS, an automated topic-wise inference method based on massive literature, suggests a possible mechanism via ACE2 for the pathological changes in the human host after coronavirus infection

Xiaoyang Ji; Chunming Zhang; Yubo Zhai; Zhonghai Zhang; Chunli Zhang; Yiqing Xue; Guangming Tan; Gang Niu

The relative position of any CSHG to a certain CSSE can be estimated by TWIRLS (see Table S1 , the ranking matrix in Sheet 1). As each category contains different entities, we can determine whether a certain CSHG is significantly closer to each entity in the current category based on the ranking matrix between CSHG and CSSE. For example, the average distance between ACE2 and the 92 entities in category C5 is first calculated, then a random distribution model of the average distance between ACE2 and any of the 92 entities (3000-5000 times) is built, and finally, we determine if the average distance between ACE2 and entities in category C5 is significantly less than and deviates from the mean of the random distribution (Z score = -5.8416). The significance of each category associated with each CSHG is then scored by TWIRLS ranging between -10 and +10, with a smaller score indicating the current CSHG is more relevant to the current category (see the Z-score matrix in Table S1 , sheet 2). For an entity category, the associated CSHGs (e.g., Ci CSHGs, where i represents the category number) can thus be selected by a Z score <-3 (the Z scores describing the association between CSHG and any category is summarized in Sheet2 of Table S1 , and the category labels of all CSHGs are provided in Sheet 3).