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EBSeq-HMM: a Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments

Ning Leng, Yuan Li, Brian E. McIntosh, Bao Kim Nguyen, Bret Duffin, Shulan Tian, James A. Thomson, Colin N. Dewey, Ron Stewart, Christina Kendziorski
2015 Bioinformatics  
Of primary interest in these experiments is identifying genes that are changing over time or space, for example, and then characterizing the specific expression changes.  ...  Motivation: With improvements in next-generation sequencing technologies and reductions in price, ordered RNA-seq experiments are becoming common.  ...  ACKNOWLEDGEMENTS The authors would like to thank Michael Newton and Ming Yuan for comments that helped improve the manuscript.  ... 
doi:10.1093/bioinformatics/btv193 pmid:25847007 pmcid:PMC4528625 fatcat:cpobwj7y2zgwlor6l2ti47vlym

Trendy: segmented regression analysis of expression dynamics in high-throughput ordered profiling experiments

Rhonda Bacher, Ning Leng, Li-Fang Chu, Zijian Ni, James A Thomson, Christina Kendziorski, Ron Stewart
2018 BMC Bioinformatics  
For each gene, Trendy finds the optimal segmented regression model and provides the location and direction of dynamic changes in expression.  ...  Trendy is a flexible R package which characterizes gene-specific expression patterns and summarizes changes of global dynamics over ordered conditions.  ...  Funding This work was funded in part by NIH U54 AI117924, GM102756, 4UH3TR000506, 5U01HL099773, the Charlotte Geyer Foundation, a grant to RS and JAT from Marv Conney, and the Morgridge Institute for Research  ... 
doi:10.1186/s12859-018-2405-x pmid:30326833 pmcid:PMC6192113 fatcat:3iybapm2kngp7laoams2m7gmwi

Dynamics in Transcriptomics: Advancements in RNA-seq Time Course and Downstream Analysis

Daniel Spies, Constance Ciaudo
2015 Computational and Structural Biotechnology Journal  
This review addresses current challenges on RNA-seq analysis and specifically focuses on new bioinformatics tools developed for time series experiments.  ...  Computational methods developed originally for microarrays analysis can now be optimized and applied to genome-wide studies in order to have access to a better comprehension of the whole transcriptome.  ...  Acknowledgments We would like to thank Tobias A. Beyer and Jian Yu for discussion and helpful comments on the manuscript.  ... 
doi:10.1016/j.csbj.2015.08.004 pmid:26430493 pmcid:PMC4564389 fatcat:r5j35ddvazcd7jr5trpz6el3ou

Temporal Dynamic Methods for Bulk RNA-Seq Time Series Data

Vera-Khlara S. Oh, Robert W. Li
2021 Genes  
To date, a number of novel methods in bulk RNA-Seq data have been developed for the various time-dependent stimuli, circadian rhythms, cell-lineage in differentiation, and disease progression.  ...  Here, we comprehensively review a key set of representative dynamic strategies and discuss current issues associated with the detection of dynamically changing genes.  ...  Here we review gene-wise methods for circadian rhythmic changes and cell-cycling genes in RNA-Seq periodical datasets (Also listed in Table 2) . A.  ... 
doi:10.3390/genes12030352 pmid:33673721 pmcid:PMC7997275 fatcat:ggelrkzvqjbmrgaw7pyicpmyyy

Differential Expression Analysis of Dynamical Sequencing Count Data with a Gamma Markov Chain [article]

Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Paul de Figueiredo, Sing-Hoi Sze, Mingyuan Zhou, Xiaoning Qian
2018 arXiv   pre-print
Extensive experiments on both simulated and real-world RNA-seq data show that GMNB outperforms existing methods in both receiver operating characteristic (ROC) and precision-recall (PR) curves of differential  ...  To capture a broader range of gene expression dynamic patterns, we develop the gamma Markov negative binomial (GMNB) model that integrates a gamma Markov chain into a negative binomial distribution model  ...  For example, EBSeq-HMM [Leng et al., 2015] takes an empirical Bayesian mixture modeling approach to compare the expression change across consecutive time points to identify genes that display significant  ... 
arXiv:1803.02527v1 fatcat:l2nh3smaq5hntlm43tm2uwofma

Comparative transcriptomics of social insect queen pheromones

Luke Holman, Heikki Helanterä, Kalevi Trontti, Alexander S. Mikheyev
2019 Nature Communications  
Pheromone-sensitive genes tend to be evolutionarily ancient, positively selected, peripheral in the gene coexpression network, hypomethylated, and caste-specific in their expression.  ...  Many genes responded consistently in multiple species, and the set of pheromone-sensitive genes was enriched for functions relating to lipid biosynthesis and transport, olfaction, production of cuticle  ...  To identify enriched GO and KEGG terms among genes whose expression was sensitive to pheromone treatment, we ranked genes by the log 10 posterior probability of differential expression (computed by EBSeq-HMM  ... 
doi:10.1038/s41467-019-09567-2 pmid:30962449 pmcid:PMC6453924 fatcat:cyzaupgotbgybm7s7ax5uvucky