id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
10_1101-2021_02_10_430623	Aberasturi, Dillon	“Single-subject studies”-derived analyses unveil altered biomechanisms between very small cohorts: implications for rare diseases	2021	9	.pdf	application/pdf	9478	748	58	published S3-type N-of-1-pathways MixEnrich to two paired samples (e.g., diseased vs unaffected tissues) for determining patient-specific enriched genes sets: Odds Ratios (S3-OR) and S3-variance using these models to derive effect sizes and statistical significance in singlesubject studies of transcriptomes, these samples are isogenic or quasi-isogenic, and thus do not necessarily generalize to a group of subjects (cohort-level signal). The novel bioinformatic method identifies meaningful biomechanism differences between very small cohorts by using single-subject-study-derived effect sizes for gene sets. (B) For the generalized linear model-based analyses, we applied a different filtering process to the raw data where we eliminated all the transcripts with 0 counts for each subject and then calculated the coefficient 2.3 Description of the Generalized Linear Models and application of Inter-N-of-1 methods for small cohort comparison and their evaluation in the Breast Cancer Data the analysis of subsets of the TCGA Breast Cancer data, genes were declared differentially expressed if their abs(log2FC) > log2(1.2) and their FDR-adjusted p-value < 	./cache/10_1101-2021_02_10_430623.pdf	./txt/10_1101-2021_02_10_430623.txt