TROM: A Testing-based Method for Finding Transcriptomic Similarity of Biological Samples

Comparative transcriptomics has gained increasing popularity in genomic research thanks to the development of high-throughput technologies including microarray and next-generation RNA sequencing that have generated numerous transcriptomic data. An important question is to understand the conservation and differentiation of biological processes in different species. We propose a testing-based method TROM (Transcriptome Overlap Measure) for comparing transcriptomes within or between different species, and provide a different perspective to interpret transcriptomic similarity in contrast to traditional correlation analyses. Specifically, the TROM method focuses on identifying associated genes that capture molecular characteristics of biological samples, and subsequently comparing the biological samples by testing the overlap of their associated genes. We use simulation and real data studies to demonstrate that TROM is more powerful in identifying similar transcriptomes and more robust to stochastic gene expression noise than Pearson and Spearman correlations. We apply TROM to compare the developmental stages of six Drosophila species, C. elegans, S. purpuratus, D. rerio and mouse liver, and find interesting correspondence patterns that imply conserved gene expression programs in the development of these species. The TROM method is available as an R package on CRAN (http://cran.r-project.org/) with manuals and source codes available at http://www.stat.ucla.edu/ jingyi.li/software-and-data/trom.html

MSIQ: Joint Modeling of Multiple RNA-seq Samples for Accurate Isoform Quantification

Next-generation RNA sequencing (RNA-seq) technology has been widely used to assess full-length RNA isoform abundance in a high-throughput manner. RNA-seq data offer insight into gene expression levels and transcriptome structures, enabling us to better understand the regulation of gene expression and fundamental biological processes. Accurate isoform quantification from RNA-seq data is challenging due to the information loss in sequencing experiments. A recent accumulation of multiple RNA-seq data sets from the same tissue or cell type provides new opportunities to improve the accuracy of isoform quantification. However, existing statistical or computational methods for multiple RNA-seq samples either pool the samples into one sample or assign equal weights to the samples when estimating isoform abundance. These methods ignore the possible heterogeneity in the quality of different samples and could result in biased and unrobust estimates. In this article, we develop a method, which we call "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ), for more accurate and robust isoform quantification by integrating multiple RNA-seq samples under a Bayesian framework. Our method aims to (1) identify a consistent group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples by allowing for higher weights on the consistent group. We show that MSIQ provides a consistent estimator of isoform abundance, and we demonstrate the accuracy and effectiveness of MSIQ compared with alternative methods through simulation studies on D. melanogaster genes. We justify MSIQ's advantages over existing approaches via application studies on real RNA-seq data from human embryonic stem cells, brain tissues, and the HepG2 immortalized cell line

Issues arising from benchmarking single-cell RNA sequencing imputation methods

On June 25th, 2018, Huang et al. published a computational method SAVER on Nature Methods for imputing dropout gene expression levels in single cell RNA sequencing (scRNA-seq) data. Huang et al. performed a set of comprehensive benchmarking analyses, including comparison with the data from RNA fluorescence in situ hybridization, to demonstrate that SAVER outperformed two existing scRNA-seq imputation methods, scImpute and MAGIC. However, their computational analyses were based on semi-synthetic data that the authors had generated following the Poisson-Gamma model used in the SAVER method. We have therefore re-examined Huang et al.'s study. We find that the semi-synthetic data have very different properties from those of real scRNA-seq data and that the cell clusters used for benchmarking are inconsistent with the cell types labeled by biologists. We show that a reanalysis based on real scRNA-seq data and grounded on biological knowledge of cell types leads to different results and conclusions from those of Huang et al.Comment: 5 page

Modeling and analysis of RNA-seq data: a review from a statistical perspective

Background: Since the invention of next-generation RNA sequencing (RNA-seq) technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels (samples, genes, transcripts, and exons) involve multiple statistical and computational questions, some of which remain challenging up to date. Results: We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusion: The development of statistical and computational methods for analyzing RNA- seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statical models and exhibit different performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development

EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences.

The availability of genome-wide epigenomic datasets enables in-depth studies of epigenetic modifications and their relationships with chromatin structures and gene expression. Various alignment tools have been developed to align nucleotide or protein sequences in order to identify structurally similar regions. However, there are currently no alignment methods specifically designed for comparing multi-track epigenomic signals and detecting common patterns that may explain functional or evolutionary similarities. We propose a new local alignment algorithm, EpiAlign, designed to compare chromatin state sequences learned from multi-track epigenomic signals and to identify locally aligned chromatin regions. EpiAlign is a dynamic programming algorithm that novelly incorporates varying lengths and frequencies of chromatin states. We demonstrate the efficacy of EpiAlign through extensive simulations and studies on the real data from the NIH Roadmap Epigenomics project. EpiAlign is able to extract recurrent chromatin state patterns along a single epigenome, and many of these patterns carry cell-type-specific characteristics. EpiAlign can also detect common chromatin state patterns across multiple epigenomes, and it will serve as a useful tool to group and distinguish epigenomic samples based on genome-wide or local chromatin state patterns

Two Years versus One Year of Tianjiu Therapy in Sanfu Days for Chronic Asthma: A Clinical Efficacy Observation Trial

Background. Tianjiu therapy has established efficacy against chronic asthma with related symptoms or the medication need during asthma attack. This study aimed to explore the optimal duration of Tianjiu therapy for asthma. Methods. This study was a self-comparison-to-the-baseline study, which comparing treatment with Tianjiu therapy for 1 year and 2 years in the same 102 chronic asthma patients. Totally 6 sessions of Tianjiu treatment were provided, 3 sessions in a year as a course of treatment and totally two years treatment. The primary endpoint was the number of asthma related symptoms which frequently appeared in asthma patients and the frequency of bronchodilator used during asthma attack. Results. The frequency of bronchodilator used during asthma attack significantly improved (χ2=46.276, P=0.000). But the number of asthma related symptoms which frequently appeared in asthma patients added by 1.38 points (95% CI, 0.25 to 2.51), 2.93±0.41 in 1-year group and 4.31±0.41 in the 2-years group (P<0.05). Conclusions. The effect of 2 years Tianjiu therapy was not as effective as 1 year such treatment for asthma, but the second year Tianjiu therapy was still needed because it has a role to consolidate the curative effect of Tianjiu therapy for asthma

Understanding health and social challenges for aging and long-term care in China

The second King’s College London Symposium on Ageing and Long-term Care in China was convened from 4 to 5th July 2019 at King’s College London in London. The aim of the Symposium was to have a better understanding of health and social challenges for aging and long-term care in China. This symposium draws research insights from a wide range of disciplines, including economics, public policy, demography, gerontology, public health and sociology. A total of 20 participants from eight countries, seek to identify the key issues and research priorities in the area of aging and long-term care in China. The results published here are a synthesis of the top four research areas that represent the perspectives from some of the leading researchers in the field. © The Author(s) 2020

The Effectiveness of Pay-It-Forward in Addressing HPV Vaccine Delay and Increasing Uptake Among 15–18-Year-Old Adolescent Girls Compared to User-Paid Vaccination: A Study Protocol for a Two-Arm Randomized Controlled Trial in China

Background Human papillomavirus (HPV) vaccination could prevent cervical and other HPV-associated cancers attributable to vaccine-associated HPV types. However, HPV vaccination coverage among women aged 9–18 years old is low in China. Common barriers include poor financial affordability, minimal public engagement, and low confidence in domestically produced HPV vaccines. Pay-it-forward offers an individual a free or subsidized service then an opportunity to voluntarily donate and/or create a postcard message to support future people. This study aims to assess the effectiveness of pay-it-forward as compared to standard-of-care self-paid vaccination to improve HPV vaccine uptake among adolescent girls aged 15–18 years, who are left out in the current pilot free HPV vaccination task force in some parts of China. Methods This is a two-arm randomized controlled trial in Chengdu, China. Eligible adolescent girls (via caregivers) will be randomly selected and recruited through four community health centers (one in the most developed urban areas, one in higher middle-income and one in lower middle-income suburban areas, and one in the least developed rural areas) using the resident registration list. A total of 320 participants will be randomized into two study arms (user-paid versus pay-it-forward vaccination) in a 1:1 ratio. The intervention assignment will be blinded to recruiters and participants using envelop concealment until the research assistants open the envelop to determine which treatment to deliver to each individual. The primary outcome of the study will be HPV vaccine uptake by administrative data. Secondary outcomes include costs, vaccine hesitancy, and the completion rates of the 3-dose HPV vaccination series. Discussion This study will investigate an innovative pay-it-forward strategy’s effectiveness and economic costs to improve HPV vaccination among 15–18-year-old adolescent girls. Study findings will have implications for increasing HPV vaccine uptake in places where HPV vaccines are provided for a fee