Research Article

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03/28/2016
Differentially expressed gene; False discovery rate; Multiple testing

Control of the false discovery rate is a statistical method that is widely used when identifying differentially expressed genes in high-throughput sequencing assays. It is often calculated using an adaptive linear step-up procedure in which the number of non-differentially expressed genes should be estimated accurately. In this paper, we discuss the estimation of this parameter and point ... more

J. Wu; C.Y. Liu; W.T. Chen; W.Y. Ma; Y. Ding; J. Wu; C.Y. Liu; W.T. Chen; W.Y. Ma; Y. Ding; J. Wu; C.Y. Liu; W.T. Chen; W.Y. Ma; Y. Ding
07/02/2014
c-kit; c-kit expression; Cashmere goat; Polyclonal antibody; Testis

The c-kit protein plays a major role in the regulation of germ cell development. Its expression and distribution in rodent testes have been widely reported. However, research regarding c-kit expression in domestic animals is scarce, and the expression pattern and distribution of c-kit in germ cells have not been clearly defined. In this study, a specific antigenic region for goat c-kit ... more

S.C.L. Wu; F.H. Luo; Q.F. Kong; Y.J. Wu
12/22/2015
Cashmere goat; Gene expression; Hair growth cycle; Transcriptome

Previous molecular genetic studies of the goat hair life cycle have focused primarily on a limited number of genes and proteins. To identify additional genes that may play important roles in hair follicle cycle regulation, Illumina sequencing technology was used to catalog differential gene expression profiles in the hair growth cycle (anagen to catagen) of goat, comparing the primary ... more

Y.X. Fan; R.B. Wu; X. Qiao; Y.J. Zhang; R.J. Wang; R. Su; J.H. Wu; Y. Dong; J.Q. Li
09/09/2015
Differentially expressed gene; Gene chip; Pathological scar tissue

Pathological scar tissues and normal skin tissues were differentiated by screening for differentially expressed genes in pathologic scar tissues via gene expression microarray. The differentially expressed gene data was analyzed by gene ontology and pathway analyses. There were 5001 up- or down-regulated genes in 2-fold differentially expressed genes, 956 up- or down-regulated genes in 5 ... more

L.P. Huang; Z. Mao; L. Zhang; X.X. Liu; C. Huang; Z.S. Jia
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Differentially expressed gene; MicroRNA; Pancreatic adenocarcinoma

The main aim of this study was to explore the underlying molecular mechanisms and potential target molecules of pancreatic adenocarcinoma. The miRNA (GSE32678) and mRNA (GSE32676) expression profiles of patients with pancreatic ductal adenocarcinoma and healthy controls were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNA and differentially expressed genes ... more

P.F. Liu; W.H. Jiang; Y.T. Han; L.F. He; H.L. Zhang; H. Ren
07/14/2015
Differentially expressed gene; Grain filling stage; Heterosis; Hybrid millet

Heterosis has been widely used in crop breeding and production. However, a shortage of genes known to function in heterosis significantly limits our understanding of the molecular basis underlying heterosis. Here, we report 740 differentially expressed genes (DEGs) in the leaves of the hybrid millet Zhang No.5 and its parents at the grain filling stage determined using Solexa Illumina ... more

Z.H. Liu; H.M. Zhang; G.L. Li; Y.M. Zhang; H.C. Li; X.L. Guo
06/03/2016
Bias curve; Isoform expression level; Multi-sample; RNA-seq; Structured sparse regression

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we ... more

L. Zhang; X.J. Liu; L. Zhang; X.J. Liu