scholarly journals A Complete Summary of Non-Parametric Statistical Methods Used For Biological Microarray Data

2019 ◽  
Vol 8 (4) ◽  
pp. 4995-5002
Keyword(s):  
Differentially Expressed Genes ◽  
Microarray Data ◽  
Statistical Tests ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Parametric Methods ◽  
Experimental Conditions ◽  
Microarray Expression Data ◽  
Microarray Expression ◽  
Non Parametric

Microarray technology is developed as a new powerful biotechnology tool, to analyze the expression profile of more than thousands of genes simultaneously. In recent times, Microarray is the most popular research topic. For extracting the differentially expressed genes from microarray data, numerous types of statistical tests are developed. The focus of microarray analysis is to predict genes that show different expression patterns under two different experimental conditions. The aim of this research paper is to explore various types of non-parametric methods proposed to analyze microarray expression data for predicting those genes which are differentially expressed, and a comparative analysis of various methods has been done. Besides, we also predicted the best condition for each method where they perform better and to investigate the disease development mechanism. Many types of statistical tests have been studied for identifying the differentially expressed genes, only very few studies have compared the performance of these methods. In our study, we extensively study and compare the different types of non-parametric methods.

scholarly journals Dynamic Changes in Gene Expression that Occur during the Period of Spontaneous Functional Regression in the Rhesus Macaque Corpus Luteum

Endocrinology ◽  
2008 ◽  
Vol 150 (3) ◽  
pp. 1521-1529 ◽  
Author(s):  
Randy L. Bogan ◽  
Melinda J. Murphy ◽  
Jon D. Hennebold
Keyword(s):  
Corpus Luteum ◽  
Rhesus Macaque ◽  
Differentially Expressed Genes ◽  
Late Stage ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Functional Regression ◽  
Luteal Regression ◽  
Protein Levels ◽  
Microarray Expression

Luteolysis of the corpus luteum (CL) during nonfertile cycles involves a cessation of progesterone (P4) synthesis (functional regression) and subsequent structural remodeling. The molecular processes responsible for initiation of luteal regression in the primate CL are poorly defined. Therefore, a genomic approach was used to systematically identify differentially expressed genes in the rhesus macaque CL during spontaneous luteolysis. CL were collected before [d 10–11 after LH surge, mid-late (ML) stage] or during (d 14–16, late stage) functional regression. Based on P4 levels, late-stage CL were subdivided into functional-late (serum P4 > 1.5 ng/ml) and functionally regressed late (FRL) (serum P4 < 0.5 ng/ml) groups (n = 4 CL per group). Total RNA was isolated, labeled, and hybridized to Affymetrix genome microarrays that contain elements representing the entire rhesus macaque transcriptome. With the ML stage serving as the baseline, there were 681 differentially expressed transcripts (>2-fold change; P < 0.05) that could be categorized into three primary patterns of expression: 1) increasing from ML through FRL; 2) decreasing from ML through FRL; and 3) increasing ML to functional late, followed by a decrease in FRL. Ontology analysis revealed potential mechanisms and pathways associated with functional and/or structural regression of the macaque CL. Quantitative real-time PCR was used to validate microarray expression patterns of 13 genes with the results being consistent between the two methodologies. Protein levels were found to parallel mRNA profiles in four of five differentially expressed genes analyzed by Western blot. Thus, this database will facilitate the identification of mechanisms involved in primate luteal regression. Genes differentially expressed during spontaneous functional regression in the rhesus macaque corpus luteum are identified, which in turn will further our understanding of primate luteolysis.

scholarly journals Microarray Gene Expression Dataset Re-Analysis Reveals Variability in Influenza Infection and Vaccination

2019 ◽  
Author(s):  
Lavida R. K. Rogers ◽  
Gustavo de los Campos ◽  
George I. Mias
Keyword(s):  
Influenza Vaccination ◽  
Differentially Expressed Genes ◽  
Influenza Infection ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
P Value ◽  
Expression Data ◽  
Microarray Expression Data ◽  
Microarray Expression ◽  
Age And Sex

ABSTRACTInfluenza, a communicable disease, affects thousands of people worldwide. Young children, elderly, immunocompromised individuals and pregnant women are at higher risk for being infected by the influenza virus. Our study aims to highlight differentially expressed genes in influenza disease compared to influenza vaccination. We also investigate genetic variation due to the age and sex of samples. To accomplish our goals, we conducted a meta-analysis using publicly available microarray expression data. Our inclusion criteria included subjects with influenza, subjects who received the influenza vaccine and healthy controls. We curated 18 microarray datasets for a total of 3,481 samples (1,277 controls, 297 influenza infection, 1,907 influenza vaccination). We pre-processed the raw microarray expression data in R using packages available to pre-process Affymetrix and Illumina microarray platforms. We used a Box-Cox power transformation of the data prior to our down-stream analysis to identify differentially expressed genes. Statistical analyses were based on linear mixed effects model with all study factors and successive likelihood ratio tests (LRT) to identify differentially-expressed genes. We filtered LRT results by disease (Bonferroni adjusted p-value < 0.05) and used a two-tailed 10% quantile cutoff to identify biologically significant genes. Furthermore, we assessed age and sex effects on the disease genes by filtering for genes with a statistically significant (Bonferroni adjusted p-value < 0.05) interaction between disease and age, and disease and sex. We identified 4,889 statistically significant genes when we filtered the LRT results by disease factor, and gene enrichment analysis (gene ontology and pathways) included innate immune response, viral process, defense response to virus, Hematopoietic cell lineage and NF-kappa B signaling pathway. Our quantile filtered gene lists comprised of 978 genes each associated with influenza infection and vaccination. We also identified 907 and 48 genes with statistically significant (Bonferroni adjusted p-value < 0.05) disease-age and disease-sex interactions respectively. Our meta-analysis approach highlights key gene signatures and their associated pathways for both influenza infection and vaccination. We also were able to identify genes with an age and sex effect. This gives potential for improving current vaccines and exploring genes that are expressed equally across ages when considering universal vaccinations for influenza.

scholarly journals Transcriptome Expression of Biomineralization Genes in Littoraria flava Gastropod in Brazilian Rocky Shore Reveals Evidence of Local Adaptation

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
Camilla A Santos ◽  
Gabriel G Sonoda ◽  
Thainá Cortez ◽  
Luiz L Coutinho ◽  
Sónia C S Andrade
Keyword(s):  
Local Adaptation ◽  
Differentially Expressed Genes ◽  
Evolutionary Biology ◽  
Rocky Shore ◽  
Expression Patterns ◽  
Purifying Selection ◽  
Marine Species ◽  
Differentially Expressed ◽  
Planktonic Larva ◽  
Structure Changes

Abstract Understanding how selection shapes population differentiation and local adaptation in marine species remains one of the greatest challenges in the field of evolutionary biology. The selection of genes in response to environment-specific factors and microenvironmental variation often results in chaotic genetic patchiness, which is commonly observed in rocky shore organisms. To identify these genes, the expression profile of the marine gastropod Littoraria flava collected from four Southeast Brazilian locations in ten rocky shore sites was analyzed. In this first L. flava transcriptome, 250,641 unigenes were generated, and 24% returned hits after functional annotation. Independent paired comparisons between 1) transects, 2) sites within transects, and 3) sites from different transects were performed for differential expression, detecting 8,622 unique differentially expressed genes. Araçá (AR) and São João (SJ) transect comparisons showed the most divergent gene products. For local adaptation, fitness-related differentially expressed genes were chosen for selection tests. Nine and 24 genes under adaptative and purifying selection, respectively, were most related to biomineralization in AR and chaperones in SJ. The biomineralization-genes perlucin and gigasin-6 were positively selected exclusively in the site toward the open ocean in AR, with sequence variants leading to pronounced protein structure changes. Despite an intense gene flow among L. flava populations due to its planktonic larva, gene expression patterns within transects may be the result of selective pressures. Our findings represent the first step in understanding how microenvironmental genetic variation is maintained in rocky shore populations and the mechanisms underlying local adaptation in marine species.

scholarly journals miRNA Expression Characterizes Histological Subtypes and Metastasis in Penile Squamous Cell Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1480
Author(s):  
Hiresh Ayoubian ◽  
Joana Heinzelmann ◽  
Sebastian Hölters ◽  
Oybek Khalmurzaev ◽  
Alexey Pryalukhin ◽  
...  
Keyword(s):  
Microarray Data ◽  
Expression Patterns ◽  
Hpv Infection ◽  
Differentially Expressed ◽  
Histological Subtypes ◽  
Specific Expression ◽  
Tissue Samples ◽  
Qrt Pcr ◽  
Differentially Expressed Mirnas ◽  
The Impact

Although microRNAs are described as promising biomarkers in many tumor types, little is known about their role in PSCC. Thus, we attempted to identify miRNAs involved in tumor development and metastasis in distinct histological subtypes considering the impact of HPV infection. In a first step, microarray analyses were performed on RNA from formalin-fixed, paraffin-embedded tumor (22), and normal (8) tissue samples. Microarray data were validated for selected miRNAs by qRT-PCR on an enlarged cohort, including 27 tumor and 18 normal tissues. We found 876 significantly differentially expressed miRNAs (p ≤ 0.01) between HPV-positive and HPV-negative tumor samples by microarray analysis. Although no significant differences were detected between normal and tumor tissue in the whole cohort, specific expression patterns occurred in distinct histological subtypes, such as HPV-negative usual PSCC (95 differentially expressed miRNAs, p ≤ 0.05) and HPV-positive basaloid/warty subtypes (247 differentially expressed miRNAs, p ≤ 0.05). Selected miRNAs were confirmed by qRT-PCR. Furthermore, microarray data revealed 118 miRNAs (p ≤ 0.01) that were significantly differentially expressed in metastatic versus non-metastatic usual PSCC. The lower expression levels for miR-137 and miR-328-3p in metastatic usual PSCC were validated by qRT-PCR. The results of this study confirmed that specific miRNAs could serve as potential diagnostic and prognostic markers in single PSCC subtypes and are associated with HPV-dependent pathways.

scholarly journals Transcriptome Analysis of Differentially Expressed mRNA Related to Pigeon Muscle Development

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2311
Author(s):  
Hao Ding ◽  
Yueyue Lin ◽  
Tao Zhang ◽  
Lan Chen ◽  
Genxi Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Differentially Expressed Genes ◽  
Growth And Development ◽  
Muscle Development ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Growth Stages ◽  
Gene Expression And Regulation

The mechanisms behind the gene expression and regulation that modulate the development and growth of pigeon skeletal muscle remain largely unknown. In this study, we performed gene expression analysis on skeletal muscle samples at different developmental and growth stages using RNA sequencing (RNA−Seq). The differentially expressed genes (DEGs) were identified using edgeR software. Weighted gene co−expression network analysis (WGCNA) was used to identify the gene modules related to the growth and development of pigeon skeletal muscle based on DEGs. A total of 11,311 DEGs were identified. WGCNA aggregated 11,311 DEGs into 12 modules. Black and brown modules were significantly correlated with the 1st and 10th day of skeletal muscle growth, while turquoise and cyan modules were significantly correlated with the 8th and 13th days of skeletal muscle embryonic development. Four mRNA−mRNA regulatory networks corresponding to the four significant modules were constructed and visualised using Cytoscape software. Twenty candidate mRNAs were identified based on their connectivity degrees in the networks, including Abca8b, TCONS−00004461, VWF, OGDH, TGIF1, DKK3, Gfpt1 and RFC5, etc. A KEGG pathway enrichment analysis showed that many pathways were related to the growth and development of pigeon skeletal muscle, including PI3K/AKT/mTOR, AMPK, FAK, and thyroid hormone pathways. Five differentially expressed genes (LAST2, MYPN, DKK3, B4GALT6 and OGDH) in the network were selected, and their expression patterns were quantified by qRT−PCR. The results were consistent with our sequencing results. These findings could enhance our understanding of the gene expression and regulation in the development and growth of pigeon muscle.

scholarly journals Analysis of Transcriptional Changes in Different Brassica napus Synthetic Allopolyploids

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 82
Author(s):  
Yunxiao Wei ◽  
Guoliang Li ◽  
Shujiang Zhang ◽  
Shifan Zhang ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Napus ◽  
Differentially Expressed Genes ◽  
Expression Patterns ◽  
Female Parent ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Transcriptional Changes ◽  
Aa Genome ◽  
High Degree

Allopolyploidy is an evolutionary and mechanistically intriguing process involving the reconciliation of two or more sets of diverged genomes and regulatory interactions, resulting in new phenotypes. In this study, we explored the gene expression patterns of eight F2 synthetic Brassica napus using RNA sequencing. We found that B. napus allopolyploid formation was accompanied by extensive changes in gene expression. A comparison between F2 and the parent shows a certain proportion of differentially expressed genes (DEG) and activation\silent gene, and the two genomes (female parent (AA)\male parent (CC) genomes) showed significant differences in response to whole-genome duplication (WGD); non-additively expressed genes represented a small portion, while Gene Ontology (GO) enrichment analysis showed that it played an important role in responding to WGD. Besides, genome-wide expression level dominance (ELD) was biased toward the AA genome, and the parental expression pattern of most genes showed a high degree of conservation. Moreover, gene expression showed differences among eight individuals and was consistent with the results of a cluster analysis of traits. Furthermore, the differential expression of waxy synthetic pathways and flowering pathway genes could explain the performance of traits. Collectively, gene expression of the newly formed allopolyploid changed dramatically, and this was different among the selfing offspring, which could be a prominent cause of the trait separation. Our data provide novel insights into the relationship between the expression of differentially expressed genes and trait segregation and provide clues into the evolution of allopolyploids.

scholarly journals Identification of Differentially Expressed Genes in Porcine Ovaries at Proestrus and Estrus Stages Using RNA-Seq Technique

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Songbai Yang ◽  
Xiaolong Zhou ◽  
Yue Pei ◽  
Han Wang ◽  
Ke He ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Patterns ◽  
Hormone Secretion ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
The Novel ◽  
Kegg Pathways ◽  
Go Enrichment ◽  
Single Organism

Estrus is an important factor for the fecundity of sows, and it is involved in ovulation and hormone secretion in ovaries. To better understand the molecular mechanisms of porcine estrus, the expression patterns of ovarian mRNA at proestrus and estrus stages were analyzed using RNA sequencing technology. A total of 2,167 differentially expressed genes (DEGs) were identified (P≤0.05, log2  Ratio≥1), of which 784 were upregulated and 1,383 were downregulated in the estrus compared with the proestrus group. Gene Ontology (GO) enrichment indicated that these DEGs were mainly involved in the cellular process, single-organism process, cell and cell part, and binding and metabolic process. In addition, a pathway analysis showed that these DEGs were significantly enriched in 33 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cell adhesion molecules, ECM-receptor interaction, and cytokine-cytokine receptor interaction. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) confirmed the differential expression of 10 selected DEGs. Many of the novel candidate genes identified in this study will be valuable for understanding the molecular mechanisms of the sow estrous cycle.

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