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Anand Mayakonda, De-Chen Lin, Yassen Assenov, Christoph Plass, H Phillip Koeffler
Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of data from somatic mutations entails a number of computational and statistical approaches, requiring usage of independent software and numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses...
October 19, 2018: Genome Research
Bijurica Chakraborty, Payel Mondal, Pragya Gajendra, Mitashree Mitra, Chandrima Das, Sanghamitra Sengupta
BACKGROUND: Plasmodium falciparum and Plasmodium vivax are two major parasites responsible for malaria which remains a threat to almost 50% of world's population despite decade-long eradication program. One possible reason behind this conundrum is that the bases of clinical variability in malaria caused by either species are complex and poorly understood. METHODS: Whole-genome transcriptome was analyzed to identify the active and predominant pathways in the PBMC of P...
October 15, 2018: EBioMedicine
Rhonda Bacher, Ning Leng, Li-Fang Chu, Zijian Ni, James A Thomson, Christina Kendziorski, Ron Stewart
BACKGROUND: High-throughput expression profiling experiments with ordered conditions (e.g. time-course or spatial-course) are becoming more common for studying detailed differentiation processes or spatial patterns. Identifying dynamic changes at both the individual gene and whole transcriptome level can provide important insights about genes, pathways, and critical time points. RESULTS: We present an R package, Trendy, which utilizes segmented regression models to simultaneously characterize each gene's expression pattern and summarize overall dynamic activity in ordered condition experiments...
October 16, 2018: BMC Bioinformatics
Shen Sun, Yue Wang, Yue Wu, Yue Gao, Qi Li, Ayanlaja Abiola Abdulrahman, Xin-Feng Liu, Guang-Quan Ji, Jin Gao, Li Li, Fa-Ping Wan, Yun-Qing Li, Dian-Shuai Gao
Malignant astrocytoma (MA) is the most common and severe type of brain tumor. A greater understanding of the underlying mechanisms responsible for the development of MA would be beneficial for the development of targeted molecular therapies. In the present study, the upregulated differentially expressed genes (DEGs) in MA were obtained from the Gene Expression Omnibus database using R/Bioconductor software. DEGs in different World Health Organization classifications were compared using the Venny tool and 15 genes, including collagen type I α1 chain (COL1A1) and laminin subunit γ1 (LAMC1), were revealed to be involved in the malignant progression of MA...
September 21, 2018: International Journal of Oncology
Rahma Said, Yoelsis Garcia-Mayea, Nesrine Trabelsi, Nouha Setti Boubaker, Cristina Mir, Ahlem Blel, Nidhal Ati, Rosanna Paciucci, Javier Hernández-Losa, Soumaya Rammeh, Amine Derouiche, Mohamed Chebil, Matilde E LLeonart, Slah Ouerhani
Currently, microRNAs (miRs) represent great biomarkers in cancer due to their stability and their potential role in diagnosis, prognosis and therapy. This study aims to evaluate the expression levels of miRs-1260 and -1274a in prostate cancer (PC) samples and to identify their eventual targets by using bioinformatic analysis. In this project, we evaluated the expression status of miRs-1260 and -1274a in 86 PC patients and 19 controls by using real-time quantitative PCR and 2-ΔΔCt method. Moreover, we retrieved validated and predicted targets of miRs from several datasets by using the "multiMir" R/Bioconductor package...
September 24, 2018: Molecular Biology Reports
Greg Finak, Bryan Mayer, William Fulp, Paul Obrecht, Alicia Sato, Eva Chung, Drienna Holman, Raphael Gottardo
A central tenet of reproducible research is that scientific results are published along with the underlying data and software code necessary to reproduce and verify the findings. A host of tools and software have been released that facilitate such work-flows and scientific journals have increasingly demanded that code and primary data be made available with publications. There has been little practical advice on implementing reproducible research work-flows for large 'omics' or systems biology data sets used by teams of analysts working in collaboration...
July 10, 2018: Gates open research
Christian M Page, Linda Vos, Trine B Rounge, Hanne F Harbo, Bettina K Andreassen
DNA methylation plays an important role in human health and disease, and methods for the identification of differently methylated regions are of increasing interest. There is currently a lack of statistical methods which properly address multiple testing, i.e. control genome-wide significance for differentially methylated regions. We introduce a scan statistic (DMRScan), which overcomes these limitations. We benchmark DMRScan against two well established methods (bumphunter, DMRcate), using a simulation study based on real methylation data...
September 19, 2018: Statistical Applications in Genetics and Molecular Biology
Maria Belen Rabaglino, Maureen Keller-Wood, Charles E Wood
Estradiol plays a critical role in stimulating the fetal hypothalamus-pituitary-adrenal axis at the end of gestation. Estradiol action is mediated through nuclear and membrane receptors that can be modulated by ICI 182,780, a pure antiestrogen compound. The objective of this study was to evaluate the transcriptomic profile of estradiol and ICI 182,780, testing the hypothesis that ICI 182,780 antagonizes the action of estradiol in the fetal hypothalamus. Chronically catheterized ovine fetuses were infused for 48 h with: vehicle (Control, n = 6), 17β-estradiol 500 μg/kg/day (Estradiol, n = 4), ICI 182,780 5 μg/kg/day (ICI 5 μg, n = 4) and ICI 182,780 5 mg/kg/day (ICI 5 mg, n = 5)...
September 2018: Physiological Reports
S Borys, A H Ludwig-Slomczynska, M Seweryn, J Hohendorff, T Koblik, J Machlowska, B Kiec-Wilk, P Wolkow, Maciej T Malecki
AIMS: Negative pressure wound therapy (NPWT) has been successfully used as a treatment for diabetic foot ulceration (DFU). Its mechanism of action on the molecular level, however, is not fully understood. We assessed the effect of NPWT on gene expression in patients with type 2 diabetes (T2DM) and DFU. METHODS: We included two cohorts of patients-individuals treated with either NPWT or standard therapy. The assignment to NWPT was non-randomized and based on wound characteristics...
September 17, 2018: Acta Diabetologica
Huan Chen, Xiangzhen Liu, Zhenning Jin, Chenyu Gou, Minglu Liang, Li Cui, Xinyuan Zhao
Oral squamous cell carcinoma (OSCC) remains to be a global health problem. However, the underlying molecular mechanisms regulating the oral leukoplakia (OLK) to OSCC remain poorly known. MicroRNAs (miRNAs) expression profiles of GSE33299 and GSE62809 were downloaded from gene expression omnibus (GEO) respectively. R software and bioconductor packages were used to compare and identify the differentially expressed miRNAs between OLK tissues and OLK transformed OSCC (OLK-OSCC). The target genes of commonly changed miRNAs were then subjected to gene ontology (GO) enrichment analysis, pathway analysis and miRNA-target genes network analysis...
2018: American Journal of Cancer Research
Paul Brennan
Protein schematics are valuable for research, teaching and knowledge communication. However, the tools used to automate the process are challenging. The purpose of the drawProteins package is to enable the generation of schematics of proteins in an automated fashion that can integrate with the Bioconductor/R suite of tools for bioinformatics and statistical analysis. Using UniProt accession numbers, the package uses the UniProt API to get the features of the protein from the UniProt database. The features are assembled into a data frame and visualized using adaptations of the ggplot2 package...
2018: F1000Research
Yi Zhang, Fei Yang
Osteosarcoma is the most common type of primary malignant bone tumor observed in children and adolescents. The aim of the present study was to identify an osteosarcoma-related gene module (OSM) by looking for a dense module following the integration of signals from genome-wide association studies (GWAS) into the human protein-protein interaction (PPI) network. A dataset of somatic mutations in osteosarcoma was obtained from the dbGaP database and their testing P-values were incorporated into the PPI network from a recent study using the dmGWAS bioconductor package...
September 2018: Experimental and Therapeutic Medicine
Gabriele Sales, Enrica Calura, Chiara Romualdi
Motivation: Metabolomics is an emerging 'omics' science involving the characterization of metabolites and metabolism in biological systems. Few bioinformatic tools have been developed for the visualization, exploration and analysis of metabolomic data within the context of metabolic pathways: some of them became rapidly obsolete and are no longer supported, others are based on a single database. A systematic collection of existing annotations has the potential of considerably boosting the investigation and contextualization of metabolomic measurements...
September 4, 2018: Bioinformatics
Davide Risso, Liam Purvis, Russell B Fletcher, Diya Das, John Ngai, Sandrine Dudoit, Elizabeth Purdom
Clustering of genes and/or samples is a common task in gene expression analysis. The goals in clustering can vary, but an important scenario is that of finding biologically meaningful subtypes within the samples. This is an application that is particularly appropriate when there are large numbers of samples, as in many human disease studies. With the increasing popularity of single-cell transcriptome sequencing (RNA-Seq), many more controlled experiments on model organisms are similarly creating large gene expression datasets with the goal of detecting previously unknown heterogeneity within cells...
September 2018: PLoS Computational Biology
Zicheng Hu, Benjamin S Glicksberg, Atul J Butte
Motivation: Flow cytometry and mass cytometry are widely used to diagnose diseases and to predict clinical outcomes. When associating clinical features with cytometry data, traditional analysis methods require cell gating as an intermediate step, leading to information loss and susceptibility to batch effects. Here, we wish to explore an alternative approach that predicts clinical features from cytometry data without the cell-gating step. We also wish to test if such a gating-free approach increases the accuracy and robustness of the prediction...
August 31, 2018: Bioinformatics
Jayaram Kancherla, Alexander Zhang, Brian Gottfried, Hector Corrada Bravo
Interactive and integrative data visualization tools and libraries are integral to exploration and analysis of genomic data. Web based genome browsers allow integrative data exploration of a large number of data sets for a specific region in the genome. Currently available web-based genome browsers are developed for specific use cases and datasets, therefore integration and extensibility of the visualizations and the underlying libraries from these tools is a challenging task. Genomic data visualization and software libraries that enable bioinformatic researchers and developers to implement customized genomic data viewers and data analyses for their application are much needed...
2018: F1000Research
Adam McDermaid, Brandon Monier, Jing Zhao, Bingqiang Liu, Qin Ma
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many applications of RNA-seq data analysis. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE results analysis from a functional point of view for various visualizations...
August 6, 2018: Briefings in Bioinformatics
Luyi Tian, Shian Su, Xueyi Dong, Daniela Amann-Zalcenstein, Christine Biben, Azadeh Seidi, Douglas J Hilton, Shalin H Naik, Matthew E Ritchie
Single-cell RNA sequencing (scRNA-seq) technology allows researchers to profile the transcriptomes of thousands of cells simultaneously. Protocols that incorporate both designed and random barcodes have greatly increased the throughput of scRNA-seq, but give rise to a more complex data structure. There is a need for new tools that can handle the various barcoding strategies used by different protocols and exploit this information for quality assessment at the sample-level and provide effective visualization of these results in preparation for higher-level analyses...
August 2018: PLoS Computational Biology
Adithya Murali, Aniruddha Bhargava, Erik S Wright
BACKGROUND: Microbiome studies often involve sequencing a marker gene to identify the microorganisms in samples of interest. Sequence classification is a critical component of this process, whereby sequences are assigned to a reference taxonomy containing known sequence representatives of many microbial groups. Previous studies have shown that existing classification programs often assign sequences to reference groups even if they belong to novel taxonomic groups that are absent from the reference taxonomy...
August 9, 2018: Microbiome
Jack M Fu, Elizabeth J Leslie, Alan F Scott, Jeffrey C Murray, Mary L Marazita, Terri H Beaty, Robert B Scharpf, Ingo Ruczinski
Motivation: De novo copy number deletions have been implicated in many diseases, but there is no formal method to date that identifies de novo deletions in parent-offspring trios from capture-based sequencing platforms. Results: We developed Minimum Distance for Targeted Sequencing (MDTS) to fill this void. MDTS has similar sensitivity (recall), but a much lower false positive rate compared to less specific CNV callers, resulting in amuch higher positive predictive value (precision)...
August 2, 2018: Bioinformatics
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