Identification of Differentially Expressed Genes in RNA-seq Data of <i>Arabidopsis thaliana</i>: A Compound Distribution Approach

Anjum, Arfa; Jaggi, Sidharth; Varghese, Eldho; Lall, Shwetank; Bhowmik, Arpan; Rai, Anil

doi:10.1089/cmb.2015.0205

Cited by 58 publications

(45 citation statements)

References 20 publications

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“…Separating samples by sex changed the data distribution from Poisson to Negative Binomial (Fig. 1 ), an observation that is in line with RNA-seq data distributions observed in other eukaryotes 24 , 31 . The shift in data distribution reduced skew and increased statistical power leading to the identification of more DE genes.…”

Section: Discussionsupporting

confidence: 84%

Cross platform analysis of transcriptomic data identifies ageing has distinct and opposite effects on tendon in males and females

Pease¹,

Clegg

Proctor

et al. 2017

Sci Rep

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The development of tendinopathy is influenced by a variety of factors including age, gender, sex hormones and diabetes status. Cross platform comparative analysis of transcriptomic data elucidated the connections between these entities in the context of ageing. Tissue-engineered tendons differentiated from bone marrow derived mesenchymal stem cells from young (20–24 years) and old (54–70 years) donors were assayed using ribonucleic acid sequencing (RNA-seq). Extension of the experiment to microarray and RNA-seq data from tendon identified gender specific gene expression changes highlighting disparity with existing literature and published pathways. Separation of RNA-seq data by sex revealed underlying negative binomial distributions which increased statistical power. Sex specific de novo transcriptome assemblies generated fewer larger transcripts that contained miRNAs, lincRNAs and snoRNAs. The results identify that in old males decreased expression of CRABP2 leads to cell proliferation, whereas in old females it leads to cellular senescence. In conjunction with existing literature the results explain gender disparity in the development and types of degenerative diseases as well as highlighting a wide range of considerations for the analysis of transcriptomic data. Wider implications are that degenerative diseases may need to be treated differently in males and females because alternative mechanisms may be involved.

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Section: Discussionsupporting

confidence: 84%

Cross platform analysis of transcriptomic data identifies ageing has distinct and opposite effects on tendon in males and females

Pease¹,

Clegg

Proctor

et al. 2017

Sci Rep

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“…A gene is considered to be differentially expressed if the observed difference between two experimental conditions is statistically significant. 59 The exact definition of significant differential expression depends on the underlying mathematical model and assumptions used, which are summarized in Table 2 . The methods can be broadly categorised into two types: those that consider a single gene's expression values, such as fold change and rank product methods, and those that utilise the gene expression values’ entire distribution, such as Bayesian and counting methods.…”

Section: Current Systems Biology Methods Used In Toxicogenomicsmentioning

confidence: 99%

Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data

et al. 2018

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“…Poisson distribution has been widely used to estimate the background level of gene expression [18-20]. In this work, we used Poisson distribution to model the background expression level (x) for each patient.…”

Section: Methodsmentioning

confidence: 99%

Transmission Expression Signature in NascentPlasmodium vivaxBlood Stage Infection

Adapa

Taylor

Wang

et al. 2017

Preprint

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The lack of a continuous in vitro culture system for Plasmodium vivax severely limits our knowledge of 1 1 pathophysiology of the most widespread malaria parasite. To gain direct understanding of P. vivax 1 2 human infections, we used Next Generation Sequencing data mining to unravel parasite in vivo 1 3 expression profiles for P. vivax, and P. falciparum as comparison. We performed cloud and local 1 4 computing to extract parasite transcriptomes from publicly available raw data of human blood samples. 5We developed a Poisson Modelling (PM) method to confidently identify parasite derived transcripts in mixed RNAseq signals of infected host tissues. We successfully retrieved and reconstructed parasite We discovered that P. vivax in vivo parasitemia is associated with gametocytogenesis expression 2 6 signature within the first blood stage cycle, that is, eight days from a mosquito bite. Our results 7suggest that asexual-to-sexual commitment may happen with first generation merozoite infection. 8This allows for the possibility of transmission at this early stage, much earlier than for P. falciparum. 9Our novel mathematical model accounts for multiple unique aspects of P. vivax biology to advance 3 0 our understanding of expected disease prevalence, and compares the results to those of P. falciparum. We demonstrate that given the presence of asymptotical carriers and the possibility of cycle, which will drive enhanced propagation of the disease during the transmission season and clinical relapses.

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Identification of Differentially Expressed Genes in RNA-seq Data of Arabidopsis thaliana: A Compound Distribution Approach

Cited by 58 publications

References 20 publications

Cross platform analysis of transcriptomic data identifies ageing has distinct and opposite effects on tendon in males and females

Cross platform analysis of transcriptomic data identifies ageing has distinct and opposite effects on tendon in males and females

Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data

Transmission Expression Signature in NascentPlasmodium vivaxBlood Stage Infection

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