Modeling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data.

Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and its presence can hamper the detection of differentially expressed genes. Since most bulk RNA-seq methods assume equal group variances, we introduce two new approaches that account for heteroscedastic groups, namely voomByGroup and voomWithQualityWeights using a blocked design (voomQWB). Compared to current gold-standard methods that do not account for group heteroscedasticity, we show results from simulations and various experiments that demonstrate the superior performance of voomByGroup and voomQWB in terms of error control and power when group variances in pseudo-bulk single-cell RNA-seq data are unequal.

Identification of consistent post-translational regulatory triplets related to oncogenic and tumour suppressive modulators in childhood acute lymphoblastic leukemia.

Background: Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer. It can be caused by mutations that turn on oncogenes or turn off tumour suppressor genes. For instance, changes in certain genes including Rb and p53 are common in ALL cells.

Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells.

Background: The discovery that somatic cells can be reprogrammed to induced pluripotent stem cells (iPSCs) has provided a foundation for in vitro human disease modelling, drug development and population genetics studies. Gene expression plays a critical role in complex disease risk and therapeutic response. However, while the genetic background of reprogrammed cell lines has been shown to strongly influence gene expression, the effect has not been evaluated at the level of individual cells which would provide significant resolution.

Genetic links between endometriosis and cancers in women.

Endometriosis is a chronic disease occurring during the reproductive stage of women. Although there is only limited association between endometriosis and gynecological cancers with regard to clinical features, the molecular basis of the relationship between these diseases is unexplored. We conducted a systematic study by integrating literature-based evidence, gene expression and large-scale cancer genomics data in order to reveal any genetic relationships between endometriosis and cancers in women.

Integrative analysis of common genes and driver mutations implicated in hormone stimulation for four cancers in women.

Cancer is one of the leading cause of death of women worldwide, and breast, ovarian, endometrial and cervical cancers contribute significantly to this every year. Developing early genetic-based diagnostic tools may be an effective approach to increase the chances of survival and provide more treatment opportunities. However, the current cancer genetic studies are mainly conducted independently and, hence lack of common driver genes involved in cancers in women.

The pan-cancer analysis of gain-of-functional mutations to identify the common oncogenic signatures in multiple cancers.

Oncogenes can potentially cause uncontrolled cell growth, leading to cancer development, and these genes are normally mutated and over-expressed in tumor cells. Genomic alteration of oncogenes might result in oncogenesis and promotion of cancer progression. To date, researchers have focused mainly on the roles of oncogenes in particular cancers, but investigation of oncogenes with gain-of-function mutations in multiple cancer types are less represented in the literature.

The bioinformatics tools for the genome assembly and analysis based on third-generation sequencing.

The application of third-generation sequencing (TGS) technology in genetics and genomics have provided opportunities to categorize and explore the individual genomic landscapes and mutations relevant for diagnosis and therapy using whole genome sequencing and de novo genome assembly. In general, the emerging TGS technology can produce high quality long reads for the determination of overlapping reads and transcript isoforms. However, this technology still faces challenges such as the accuracy for the identification of nucleotide bases and high error rates.

A pan-cancer study of copy number gain and up-regulation in human oncogenes.

Aim: There has been limited research on CNVs in oncogenes and we conducted a systematic pan-cancer analysis of CNVs and their gene expression changes. The aim of the present study was to provide an insight into the relationships between gene expression and oncogenesis.

Main Methods: We collected all the oncogenes from ONGene database and overlapped with CNVs TCGA tumour samples from Catalogue of Somatic Mutations in Cancer database.

Identification of novel prognosis-related genes associated with cancer using integrative network analysis.

Prognosis identifies the seriousness and the chances of survival of a cancer patient. However, it remains a challenge to identify the key cancer genes in prognostic studies. In this study, we collected 2064 genes that were related to prognostic studies by using gene expression measurements curated from published literatures.