The dissimilarity analysis between samples meas- uring population composition (beta-diversity) has been evaluated using QIIME weighted Unifrac distances between samples at a sub-sampling depth of 100 se- quences
probability of occurrence to each query based on the selected similarity parameter and dissimilarity parameter. 15.The computer-readable medium of claim 14 containing further computer executable code for performing the following steps:partitioning the database into regions based on the expected workload ...
To further investigate shape-of-curve similarity, we defined a symmetric distance measure (see Methods part 2 for analytical details; Fig.1bshowing the full dissimilarity matrix). Our comparison across the whole disease spectrum and two countries (US and Denmark) identified five clusters (see Suppl...
The degree of similarity between pairwise molecular sequences reflects the amount of mutation events that occurred since they split from their common ancestor. Quantifying such similarity constitutes the first step in the phylogenetic estimation process [11]. The task involves the investigation and the ...
The goal of the SCADIE framework is to estimate matchedW1,H1andW2,H2from bulk dataY1,Y2and then perform hypothesis tests to identify cell type-specific DEGs. In the most common deconvolution scenario, onlyY1,Y2and a shared signature matrixW_are provided, going from sharedWsubwith only signa...
The Jaccard index is a measure of similarity between sets and is defined by equation (1). Jaccard distance, a measure of dissimilarity between sets, is obtained by subtracting the Jaccard index from 1. In the case of genomic sequences, your set is comprised of words length k (i.e. kmer...
the model makes predictions without revealing that it predicts into untrained predictor combinations. To examine the climatic dissimilarity between Europe’s current climate with the used future climate data the multivariate environmental similarity surface (MESS) analysis [59] was applied. The unrepresente...