Extended Data Fig. 8: Diagnostic rate after analysis of 80 distinct cases.
From: Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
a, Overview of cases. Solved: causal gene found and further validated. Strong candidate: Strong candidate after RNA-seq analysis (out of a subset of 30 affected individuals for which we have prior candidate genes information from literature). Unsolved: Other cases for which further investigation is needed. b, Percentage of cases for which prior candidate gene is in final set of filtered genes (outlier with deleterious rare variant in a gene linked to symptoms). Analysis was performed only on a subset of 30 cases for which we have prior candidate gene information and for which we have genetic information. Shuffling candidates corresponds to the percentage of cases for which we observe a prior candidate genes in the most stringent gene list when shuffling gene lists across individuals (10,000 permutations). On average, no match is found. Shuffling genes correspond to the percentage of prior candidate genes we observed within the final set of DNA-only filters when sampling from this list a matched number of genes corresponding to the expression filters. Average matched percentage is 4.1% after 10,000 permutations. Real data corresponds to the percentage of cases for which we found a candidate gene in the most stringent RNA-based filter set. We find a match for 7 affected samples out of 30, that is, 25.9 % of cases. There is significantly more match in real data in comparison to permuted data (two-sided Wilcoxon rank sum test, P value < 10–5). Boxplots represent median value, with lower and upper hinges corresponding to the 25th and 75th percentiles, and lower and upper whiskers extend from the hinge to the smallest and largest value at most 1.5× interquartile range of the hinge, respectively.
