Gene dispersion is the key determinant of the read count bias in differential expression analysis of RNA-seq data

Background: In differential expression analysis of RNA-sequencing (RNA-seq) read count data for two sample groups, it is known that highly expressed genes (or longer genes) are more likely to be differentially expressed which is called read count bias (or gene length bias). This bias had great effect on the downstream Gene Ontology over-representation analysis. However, such a bias has not been systematically analyzed for different replicate types of RNA-seq data. Results: We show that the dispersion coefficient of a gene in the negative binomial modeling of read counts is the critical determinant of the read count bias (and gene length bias) by mathematical inference and tests for a number of simulated and real RNA-seq datasets. We demonstrate that the read count bias is mostly confined to data with small gene dispersions (e.g., technical replicates and some of genetically identical replicates such as cell lines or inbred animals), and many biological replicate data from unrelated samples do not suffer from such a bias except for genes with some small counts. It is also shown that the sample-permuting GSEA method yields a considerable number of false positives caused by the read count bias, while the preranked method does not. Conclusion: We showed the small gene variance (similarly, dispersion) is the main cause of read count bias (and gene length bias) for the first time and analyzed the read count bias for different replicate types of RNA-seq data and its effect on gene-set enrichment analysis

Pathogenesis of progressive scarring trachoma in Ethiopia and Tanzania and its implications for disease control: two cohort studies.

BACKGROUND: Trachoma causes blindness through a conjunctival scarring process initiated by ocular Chlamydia trachomatis infection; however, the rates, drivers and pathophysiological determinants are poorly understood. We investigated progressive scarring and its relationship to conjunctival infection, inflammation and transcript levels of cytokines and fibrogenic factors. METHODOLOGY/PRINCIPAL FINDINGS: We recruited two cohorts, one each in Ethiopia and Tanzania, of individuals with established trachomatous conjunctival scarring. They were followed six-monthly for two years, with clinical examinations and conjunctival swab sample collection. Progressive scarring cases were identified by comparing baseline and two-year photographs, and compared to individuals without progression. Samples were tested for C. trachomatis by PCR and transcript levels of S100A7, IL1B, IL13, IL17A, CXCL5, CTGF, SPARCL1, CEACAM5, MMP7, MMP9 and CD83 were estimated by quantitative RT-PCR. Progressive scarring was found in 135/585 (23.1%) of Ethiopian participants and 173/577 (30.0%) of Tanzanian participants. There was a strong relationship between progressive scarring and increasing inflammatory episodes (Ethiopia: OR 5.93, 95%CI 3.31-10.6, p<0.0001. Tanzania: OR 5.76, 95%CI 2.60-12.7, p<0.0001). No episodes of C. trachomatis infection were detected in the Ethiopian cohort and only 5 episodes in the Tanzanian cohort. Clinical inflammation, but not scarring progression, was associated with increased expression of S100A7, IL1B, IL17A, CXCL5, CTGF, CEACAM5, MMP7, CD83 and reduced SPARCL1. CONCLUSIONS/SIGNIFICANCE: Scarring progressed in the absence of detectable C. trachomatis, which raises uncertainty about the primary drivers of late-stage trachoma. Chronic conjunctival inflammation appears to be central and is associated with enriched expression of pro-inflammatory factors and altered expression of extracellular matrix regulators. Host determinants of scarring progression appear more complex and subtle than the features of inflammation. Overall this indicates a potential role for anti-inflammatory interventions to interrupt progression and the need for trichiasis disease surveillance and surgery long after chlamydial infection has been controlled at community level