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Beomseok Kim, Eunmin Lee, Jong Kyoung Kim
Profiling the transcriptomes of individual cells with single-cell RNA sequencing (scRNA-seq) has been widely applied to provide a detailed molecular characterization of cellular heterogeneity within a population of cells. Despite recent technological advances of scRNA-seq, technical variability of gene expression in scRNA-seq is still much higher than that in bulk RNA-seq. Accounting for technical variability is therefore a prerequisite for correctly analyzing single-cell data. This chapter describes a computational pipeline for detecting highly variable genes exhibiting higher cell-to-cell variability than expected by technical noise...
2019: Methods in Molecular Biology
Rhonda Bacher
In this chapter, we describe a robust normalization method for single-cell RNA sequencing data. The procedure, SCnorm, is implemented in R and is part of Bioconductor. Also included in the package are diagnostic functions to visualize normalization performance. This chapter provides an overview of the methodology and provides example work-flows.
2019: Methods in Molecular Biology
Minoo Ashtiani, Payman Nickchi, Soheil Jahangiri-Tazehkand, Abdollah Safari, Mehdi Mirzaie, Mohieddin Jafari
BACKGROUND: Reconstruction of protein-protein interaction networks (PPIN) has been riddled with controversy for decades. Particularly, false-negative and -positive interactions make this progress even more complicated. Also, lack of a standard PPIN limits us in the comparison studies and results in the incompatible outcomes. Using an evolution-based concept, i.e. interolog which refers to interacting orthologous protein sets, pave the way toward an optimal benchmark. RESULTS: Here, we provide an R package, IMMAN, as a tool for reconstructing Interolog Protein Network (IPN) by integrating several Protein-protein Interaction Networks (PPINs)...
February 12, 2019: BMC Bioinformatics
Jordi Martorell-Marugán, Víctor González-Rumayor, Pedro Carmona-Sáez
Motivation: The identification of differentially methylated regions (DMRs) among phenotypes is one of the main goals of epigenetic analysis. Although there are several methods developed to detect DMRs, most of them are focused on detecting relatively large differences in methylation levels and fail to detect moderate, but consistent, methylation changes that might be associated to complex disorders. Results: We present mCSEA, an R package that implements a Gene Set Enrichment Analysis method to identify differentially methylated regions from Illumina450K and EPIC array data...
February 12, 2019: Bioinformatics
Rachel Jeitziner, Mathieu Carrière, Jacques Rougemont, Steve Oudot, Kathryn Hess, Cathrin Brisken
Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. To overcome these shortcomings we used topological data analysis, an emerging field of mathematics that can discerns additional feature and discover hidden insights on data sets and has a wide application range. Results: We have developed a topology-based clustering method called Two-Tier Mapper (TTMap) for enhanced analysis of global gene expression datasets...
February 7, 2019: Bioinformatics
Estefanía Cortés-Pereira, Juan Fernández-Tajes, Mercedes Fernández-Moreno, María E Vázquez-Mosquera, Sara Relaño, Paula Ramos-Louro, Alejandro Durán-Sotuela, Andrea Dalmao-Fernández, Natividad Oreiro, Francisco J Blanco, Ignacio Rego-Pérez
OBJECTIVE: To analyse the influence of mitochondrial genome variation on the DNA methylome of articular cartilage. METHODS: DNA methylation profiling was performed from data deposited in the NCBI Gene Expression Omnibus (GEO) database (accession number GSE43269) consisted in the data of 14 haplogroup J cartilages and 20 H cartilages. Subsequent validation was performed in an independent subset of 7 haplogroup J cartilages and 9 H cartilages by RNA-seq. Correlated genes were validated by real-time PCR in an independent cohort of 12 J cartilages and 12 H cartilages...
February 12, 2019: Arthritis & Rheumatology
Robert B Bentham, Kevin Bryson, Gyorgy Szabadkai
Transcription of a large set of nuclear-encoded genes underlies biogenesis of mitochondria, regulated by a complex network of transcription factors and co-regulators. A remarkable heterogeneity can be detected in the expression of these genes in different cell types and tissues, and the recent availability of large gene expression compendiums allows the quantification of specific mitochondrial biogenesis patterns. We have developed a method to effectively perform this task. Massively correlated biclustering (MCbiclust) is a novel bioinformatics method that has been successfully applied to identify co-regulation patterns in large genesets, underlying essential cellular functions and determining cell types...
2019: Methods in Molecular Biology
Danyue Dong, Yuan Tian, Shijie C Zheng, Andrew E Teschendorff
Motivation: The biological interpretation of differentially methylated sites derived from Epigenome-Wide-Association Studies remains a significant challenge. Gene Set Enrichment Analysis (GSEA) is a general tool to help aid biological interpretation, yet its correct and unbiased implementation in the EWAS context is difficult due to the differential probe representation of Illumina Infinium DNA methylation beadchips. Results: We present a novel GSEA method, called ebGSEA, which ranks genes, not CpGs, according to the overall level of differential methylation, as assessed using all the probes mapping to the given gene...
January 31, 2019: Bioinformatics
Konstantin Okonechnikov, Serap Erkek, Jan O Korbel, Stefan M Pfister, Lukas Chavez
BACKGROUND: High-throughput technologies for analyzing chromosome conformation at a genome scale have revealed that chromatin is organized in topologically associated domains (TADs). While TADs are relatively stable across cell types, intra-TAD activities are cell type specific. Epigenetic profiling of different tissues and cell-types has identified a large number of non-coding epigenetic regulatory elements ('enhancers') that can be located far away from coding genes. Linear proximity is a commonly chosen criterion for associating enhancers with their potential target genes...
January 31, 2019: BMC Bioinformatics
Ioannis Vardaxis, Finn Drabløs, Morten B Rye, Bo Henry Lindqvist
We present model-based analysis for ChIA-PET (MACPET), which analyzes paired-end read sequences provided by ChIA-PET for finding binding sites of a protein of interest. MACPET uses information from both tags of each PET and searches for binding sites in a two-dimensional space, while taking into account different noise levels in different genomic regions. MACPET shows favorable results compared with MACS in terms of motif occurrence and spatial resolution. Furthermore, significant binding sites discovered by MACPET are involved in a higher number of significant three-dimensional interactions than those discovered by MACS...
January 30, 2019: Biostatistics
Johannes Rainer, Laurent Gatto, Christian X Weichenberger
Summary: Bioinformatics research frequently involves handling gene-centric data such as exons, transcripts, proteins, and their positions relative to a reference coordinate system. The ensembldb Bioconductor package retrieves and stores Ensembl-based genetic annotations and positional information, and furthermore offers identifier conversion and coordinate mappings for gene-associated data. In support of reproducible research, data are tied to Ensembl releases and are kept separately from the software...
January 25, 2019: Bioinformatics
Levi Waldron, Lucas Schiffer, Rimsha Azhar, Marcel Ramos, Ludwig Geistlinger, Nicola Segata
No abstract text is available yet for this article.
January 23, 2019: American Journal of Epidemiology
Raik Otto, Jan-Niklas Rössler, Christine Sers, Soulafa Mamlouk, Ulf Leser
Cancer cell lines (CCL) are an integral part of modern cancer research but are susceptible to misidentification. The increasing popularity of sequencing technologies motivates the in-silico identification of CCLs based on their mutational fingerprint, but care must be taken when identifying heterogeneous data. We recently developed the proof-of-concept Uniquorn 1 method which could reliably identify heterogeneous sequencing data from selected sequencing technologies. Here we present Uniquorn 2, a generic and robust in-silico identification method for CCLs with DNA/RNA-seq and panel-seq information...
January 23, 2019: Scientific Reports
Jing Lv, Lei Guo, Ji-Han Wang, Yu-Zhu Yan, Jun Zhang, Yang-Yang Wang, Yan Yu, Yun-Fei Huang, He-Ping Zhao
BACKGROUND: Esophageal adenocarcinoma (EAC) is an aggressive disease with high mortality and an overall 5-year survival rate of less than 20%. Barrett's esophagus (BE) is the only known precursor of EAC, and patients with BE have a persistent and excessive risk of EAC over time. Individuals with BE are up to 30-125 times more likely to develop EAC than the general population. Thus, early detection of EAC and BE could significantly improve the 5-year survival rate of EAC. Due to the limitations of endoscopic surveillance and the lack of clinical risk stratification strategies, molecular biomarkers should be considered and thoroughly investigated...
January 14, 2019: World Journal of Gastroenterology: WJG
Konstantinos A Kyritsis, Bing Wang, Julie Sullivan, Rachel Lyne, Gos Micklem
Summary: InterMineR is a package designed to provide a flexible interface between the R programming environment and biological databases built using the InterMine platform. The package offers access to the flexible query builder and the library of term enrichment tools of the InterMine framework, as well as interoperability with other Bioconductor packages. This facilitates automation of data retrieval tasks as well as downstream analysis with existing statistical tools in the R environment...
January 22, 2019: Bioinformatics
John C Stansfield, Kellen G Cresswell, Mikhail G Dozmorov
Motivation: With the development of chromatin conformation capture technology and its high-throughput derivative Hi-C sequencing, studies of the three-dimensional (3D) interactome of the genome that involve multiple Hi-C datasets are becoming available. To account for the technology-driven biases unique to each dataset, there is a distinct need for methods to jointly normalize multiple Hi-C datasets. Previous attempts at removing biases from Hi-C data have made use of techniques which normalize individual Hi-C datasets, or, at best, jointly normalize two datasets...
January 22, 2019: Bioinformatics
Guifu Ma, Chao Zhang, Wenyuan Luo, Jia-Li Zhao, Xuebin Wang, Yaowen Qian
Osteosarcoma is the most common bone tumor in children and young adults. Although the microRNAs (miRNA) expression analyses of osteosarcoma have been performed previously, the construction of miRNA-messenger RNA (mRNA) networks for osteosarcoma is needed. This study aimed to identify osteosarcoma-related miRNAs through analyzing the microarray datasets and to construct the regulatory network of miRNA-mRNA for human osteosarcoma. The datasets were extracted from the Gene Expression Omnibus and the differentially expressed miRNAs were screened through the limma package in Bioconductor...
January 21, 2019: Journal of Cellular Physiology
Nathalie Fuentes, Patricia Silveyra
MicroRNA (miRNA) profiling has become of interest to researchers working in various research areas of biology and medicine. Current studies show a promising future of using miRNAs in the diagnosis and care of lung diseases. Here, we define a protocol for miRNA profiling to measure the relative abundance of a group of miRNAs predicted to regulate inflammatory genes in the lung tissue from of an ozone-induced airway inflammation mouse model. Because it has been shown that circulating sex hormone levels can affect the regulation of lung innate immunity in females, the purpose of this method is to describe an inflammatory miRNA profiling protocol in female mice, taking into consideration the estrous cycle stage of each animal at the time of ozone exposure...
January 7, 2019: Journal of Visualized Experiments: JoVE
Monica Golumbeanu, Sébastien Desfarges, Céline Hernandez, Manfredo Quadroni, Sylvie Rato, Pejman Mohammadi, Amalio Telenti, Niko Beerenwinkel, Angela Ciuffi
Throughout the HIV-1 replication cycle, complex host-pathogen interactions take place in the infected cell, leading to the production of new virions. The virus modulates the host cellular machinery in order to support its life cycle, while counteracting intracellular defense mechanisms. We investigated the dynamic host response to HIV-1 infection by systematically measuring transcriptomic, proteomic, and phosphoproteomic expression changes in infected and uninfected SupT1 CD4+ T cells at five time points of the viral replication process...
January 18, 2019: Scientific Reports
Amrit Singh, Casey P Shannon, Benoît Gautier, Florian Rohart, Michaël Vacher, Scott J Tebbutt, Kim-Anh Lê Cao
Motivation: In the continuously expanding omics era, novel computational and statistical strategies are needed for data integration and identification of biomarkers and molecular signatures. We present DIABLO, a multi-omics integrative method that seeks for common information across different data types through the selection of a subset of molecular features, while discriminating between multiple phenotypic groups. Results: Using simulations and benchmark multi-omics studies, we show that DIABLO identifies features with superior biological relevance compared to existing unsupervised integrative methods, while achieving predictive performance comparable to state-of-the-art supervised approaches...
January 18, 2019: Bioinformatics
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