RNA-Seq methods for imperfect samples: development, evaluation and applications

Abstract

Deep exome resequencing is a powerful approach for delineating patterns of protein-coding variation among genes, pathways, individuals and populations. We analyzed exome data from 2,440 individuals of European and African ancestry as part of the National Heart, Lung, and Blood Institute's Exome Project, the aim of which is to discover novel genes and mechanisms that contribute to heart, lung and blood disorders. Each exome was sequenced to a mean coverage of 116×, allowing detailed inferences about the population genomic patterns of both common variation and rare coding variation. We identifi ed more than 500,000 single nucleotide variations, the majority of which were novel and rare (76% of variants had a minor allele frequency of less than 0.1%), refl ecting the recent dramatic increase in the size of the human population. The unprecedented magnitude of this dataset allowed us to rigorously characterize the large variation in nucleotide diversity among genes (ranging from 0 to 1.32%), as well as the role of positive and purifying selection in shaping patterns of proteincoding variation and the diff erential signatures of population structure from rare and common variation. This dataset provides a framework for personal genomics and is an important resource that will allow inferences of broad importance to human evolution and health.

Bacterial Diversity of Intestinal Microbiota in Patients with Substance Use Disorders Revealed by 16S rRNA Gene Deep Sequencing

“…The upper limit of rarefaction depths (−e 39810) was used as the cut-off value. Metagenomic biomarker discovery use the online LEfSe program (http://huttenhower.sph.harvard.edu/galaxy/root/index) 29 . The function of intestinal microbiota was performed by online phylogenetic investigation of communities by reconstruction of unobserved states program (PICRUSt, http://picrust.github.io/picrust/).…”

Soil nutritional status and biogeography influence rhizosphere microbial communities associated with the invasive tree Acacia dealbata

“…First, we identified rhizosphere bacterial and fungal taxa that were present in all eight locations. We then performed linear discriminant analysis (LDA) effect size (LEfSe) 76 to discriminate between microbial markers of the rhizosphere and bulk soil. We hypothesised that if microorganisms are selected within a given habitat on the basis of their functional capacities, microbial markers should be among the most influential microbial taxa in their respective habitat.…”

The mycobiome of root canal infections is correlated to the bacteriome

“…Compositional differences between groups were determined using one-way permutational multivariate analysis of variance (PERMANOVA) on the Bray-Curtis similarity indices of between-sample diversity. If significant, these differences were further analyzed by the linear discriminant analysis (LDA) effect size (LEfSe; version 1.0) method to identify the OTUs responsible for segregation into distinct groups [39]. The cutoff LDA value was kept at the default of 2.0.…”