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The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization [article]

Roman Mezencev, Scott S Auerbach
2019 bioRxiv   pre-print
In this study we evaluate the influence of microarray normalization methods on the transcriptomic BMDs.  ...  In addition, we found that normalization can have a considerable effect (as much as ~30-fold in this study) on estimation of the minimum biological potency (transcriptomic point of departure).  ...  The purpose of this study was to examine sensitivity of transcriptomics BMD modeling to some frequently used methods for microarray data normalization.  ... 
doi:10.1101/781567 fatcat:zxiqroqaa5aspnwxzs2ioi5jgi

A Multivariate Poisson-Log Normal Mixture Model for Clustering Transcriptome Sequencing Data [article]

Anjali Silva, Steven J. Rothstein, Paul D. McNicholas, Sanjeena Subedi
2017 arXiv   pre-print
A mixture of multivariate Poisson-Log Normal (MPLN) model is proposed for clustering of high-throughput transcriptome sequencing data.  ...  As data visualization techniques become cumbersome for higher dimensions and unconvincing when there is no clear separation between homogeneous subgroups within the data, cluster analysis provides an intuitive  ...  The transcriptome data analysis showed the applicability of mixtures of MPLN distribution on RNA-seq data.  ... 
arXiv:1711.11190v1 fatcat:u4ible5bvjh6ridej6xu3zzvva

Normalization Methods for the Analysis of Unbalanced Transcriptome Data: A Review

Xueyan Liu, Nan Li, Sheng Liu, Jun Wang, Ning Zhang, Xubin Zheng, Kwong-Sak Leung, Lixin Cheng
2019 Frontiers in Bioengineering and Biotechnology  
To our best knowledge, this is the most comprehensive review of available preprocessing algorithms for the unbalanced transcriptome data.  ...  From the perspective of reference selection, we classified the normalization methods for skewed expression data into three categories, data-driven reference, foreign reference, and entire gene set.  ...  TABLE 1 | 1 A summary of 23 normalization methods developed for unbalanced transcriptome data. No.  ... 
doi:10.3389/fbioe.2019.00358 pmid:32039167 pmcid:PMC6988798 fatcat:jqv3ey6kkjf55ofb35ncute7nq

A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data

Anjali Silva, Steven J. Rothstein, Paul D. McNicholas, Sanjeena Subedi
2019 BMC Bioinformatics  
Results: A mixture of multivariate Poisson-log normal (MPLN) model is developed for clustering of high-throughput transcriptome sequencing data.  ...  As data visualization techniques become cumbersome for higher dimensions and unconvincing when there is no clear separation between homogeneous subgroups within the data, cluster analysis provides an intuitive  ...  Transcriptome data analysis: cranberry bean RNA-seq data In the study by Freixas-Coutin et al.  ... 
doi:10.1186/s12859-019-2916-0 fatcat:pye6ro6cmncbzfqkf2ymuiacou

A comprehensive transcriptome data of normal and Nosema ceranae-stressed midguts of Apis mellifera ligustica workers

Huazhi Chen, Yu Du, Cuiling Xiong, Yanzhen Zheng, Dafu Chen, Rui Guo
2019 Data in Brief  
Raw data were deposited in NCBI Sequence Read Archive (SRA) database under the BioProject number PRJNA406998.  ...  These data can be used for comparative analysis to identify differentially expressed coding RNAs and non-coding RNAs involved in A. m. ligustica responses to N. ceranae stress, and for investigation of  ...  Table 1 1 Quality control of transcriptome data.  ... 
doi:10.1016/j.dib.2019.104349 pmid:31516938 pmcid:PMC6727036 fatcat:xcvjulrihrgi3dw6yfxydj7fvu

The sensitivity of transcriptomics BMD modeling to the methods used for microarray data normalization

Roman Mezencev, Scott S. Auerbach, Lars Kaderali
2020 PLoS ONE  
In this study we evaluate the influence of microarray normalization methods on the transcriptomic BMDs.  ...  In addition, we found that normalization can have a considerable effect (as much as ~30-fold in this study) on estimation of the minimum biological potency (transcriptomic point of departure).  ...  The purpose of this study was to examine sensitivity of transcriptomics BMD modeling to some frequently used methods for microarray data normalization.  ... 
doi:10.1371/journal.pone.0232955 pmid:32413060 fatcat:zifikacc7vdzddpqijvglne3ty

Comprehensive transcriptome data of normal and Ascosphaera apis-infected western honeybee larval guts [article]

Yu Du, Jie Wang, Zhiwei Zhu, Haibin Jiang, Xiaoxue Fan, Yuanchan Fan, Yanzhen Zheng, Cuiling Xiong, Dafu Chen, Rui Guo
2020 bioRxiv   pre-print
The strand-specific cDNA library-based RNA sequencing data documented here will faciliate study on molecualr mechanisms underlying host immune response and host-pathogen interaction during chalkbrood disease  ...  Keywords transcriptome, RNA-seq, honeybee, larva, Apis mellifera ligustica, Ascosphaera apis, chalkbrood, non-coding RNA Value of the Data This data reported here could be used to explore circRNAs, lncRNAs  ...  Data description The share data were generated from strand-specific cDNA library-based RNA-seq of normal larval guts (AmCK1, AmCK2, and AmCK3) and Ascosphaera apis-infected (AmT1, AmT2, and AmT3) larval  ... 
doi:10.1101/2020.04.11.037598 fatcat:45lgbmhyrrhu5ialoiundehspe

Accurate quantification of transcriptome from RNA-Seq data by effective length normalization

Soohyun Lee, Chae Hwa Seo, Byungho Lim, Jin Ok Yang, Jeongsu Oh, Minjin Kim, Sooncheol Lee, Byungwook Lee, Changwon Kang, Sanghyuk Lee
2010 Nucleic Acids Research  
We propose a novel, efficient and intuitive approach of estimating mRNA abundances from the whole transcriptome shotgun sequencing (RNA-Seq) data.  ...  Our method, NEUMA (Normalization by Expected Uniquely Mappable Area), is based on effective length normalization using uniquely mappable areas of gene and mRNA isoform models.  ...  The relative expression level of each gene was normalized by that of GAPDH. Mapping of paired-end RNA-Seq data NEUMA.  ... 
doi:10.1093/nar/gkq1015 pmid:21059678 pmcid:PMC3025570 fatcat:rxuz4kmkjnetxbykcvjacyvu54

Identification of suitable reference genes for normalization of qPCR data in comparative transcriptomics analyses in the Triticeae

María J. Giménez, Fernando Pistón, Sergio G. Atienza
2010 Planta  
Wheat/ barley/rye consensus primers outperformed wheat-specific ones which indicate that consensus primers should be considered for data normalization in comparative transcriptomics.  ...  Comparative transcriptomics are useful to determine the role of orthologous genes among Triticeae species.  ...  Although comparative transcriptomics between grasses use reference genes for data normalization (Campoli et al. 2009; Gil-Humanes et al. 2009 ), these genes are selected on the basis of their good performance  ... 
doi:10.1007/s00425-010-1290-y pmid:20960006 fatcat:r74j4tf2srhgpnewrph3aoldha

Whole-transcriptome analysis of differentially expressed genes in the mutant and normal capitula of Chrysanthemum morifolium

Hua Liu, Chang Luo, Dongliang Chen, Yaqin Wang, Shuang Guo, Xiaoxi Chen, Jingyi Bai, Mingyuan Li, Xinlei Huang, Xi Cheng, Conglin Huang
2021 BMC Genomic Data  
Results We conducted a whole-transcriptome analysis of the differentially expressed genes (DEGs) in the mutant and normal capitula using third-generation and second-generation sequencing techniques.  ...  Conclusions The whole-transcriptome analysis of DEGs in mutant and normal C. morifolium capitula described herein indicates the anthocyanin deficiency of the mutant capitula may be related to the mutation  ...  The resulting data for all 16 genes were consistent with the sequencing data (Additional file 15, Fig. 9 ).  ... 
doi:10.1186/s12863-021-00959-2 pmid:33568073 pmcid:PMC7853313 fatcat:jm6vsmpudjbcbemicqxht4fiti

Normalization of gene expression data revisited: the three viewpoints of the transcriptome in human skeletal muscle undergoing load-induced hypertrophy and why they matter

Yusuf Khan, Daniel Hammarström, Stian Ellefsen, Rafi Ahmad
2022 BMC Bioinformatics  
Background The biological relevance and accuracy of gene expression data depend on the adequacy of data normalization.  ...  In this study, we highlight the consequences of using three fundamentally different modes of normalization for interpreting RNA-seq data from human skeletal muscle undergoing exercise-training-induced  ...  The present study aimed to investigate the consequences of using each of three normalization modes (per-library-size, per-total-RNA, and per-sample-size) for transcriptome profiling of RNA-seq data from  ... 
doi:10.1186/s12859-022-04791-y pmid:35717158 pmcid:PMC9206305 fatcat:cb4xky6qb5hxhbljrrrpjzgosu

Transcriptomic Data Analyses Reveal That Sow Fertility-Related lincRNA NORFA Is Essential for the Normal States and Functions of Granulosa Cells

Xing Du, Qiqi Li, Liu Yang, Qiang Zeng, Siqi Wang, Qifa Li
2021 Frontiers in Cell and Developmental Biology  
These findings present a panoramic view of the transcriptome in NORFA-reduced GCs, highlighting that NORFA, a candidate lincRNA for sow fertility, is crucial for the normal states and functions of GCs.  ...  In this study, RNA-seq was performed and we noticed that inhibition of NORFA led to dramatic transcriptomic alterations in porcine GCs.  ...  Knockdown of NORFA Impairs the Normal States and Functions of Porcine GCs Based on the transcriptomic data and bioinformatic analysis results, we hypothesized that NORFA is essential for the normal states  ... 
doi:10.3389/fcell.2021.610553 pmid:33708768 pmcid:PMC7940361 fatcat:ecpylltwnrbwzeyjwslurj5iji

Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data

Christian Müller, Arne Schillert, Caroline Röthemeier, David-Alexandre Trégouët, Carole Proust, Harald Binder, Norbert Pfeiffer, Manfred Beutel, Karl J. Lackner, Renate B. Schnabel, Laurence Tiret, Philipp S. Wild (+4 others)
2016 PLoS ONE  
In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical  ...  Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data.  ...  Regressions were performed in following subsets independently: i) quantile normalized BL data, ii) quantile normalized and ComBat corrected BL data, iii) quantile normalized FU data and iv) quantile normalized  ... 
doi:10.1371/journal.pone.0156594 pmid:27272489 pmcid:PMC4896498 fatcat:mr4uqao6wvbjlbtnaazfekh7fq

Transcriptome profiling of sorted endoreduplicated nuclei from tomato fruits: how the global shift in expression ascribed to DNA ploidy influences RNA-Seq data normalization and interpretation

Julien Pirrello, Cynthia Deluche, Nathalie Frangne, Frédéric Gévaudant, Elie Maza, Anis Djari, Mickaël Bourge, Jean-Pierre Renaudin, Spencer Brown, Chris Bowler, Mohamed Zouine, Christian Chevalier (+1 others)
2018 The Plant Journal  
Transcriptome profiling of sorted endoreduplicated nuclei from tomato fruits: how global shift in expression ascribed to DNA ploidy influences RNA-Seq data normalization and interpretation.  ...  Transcriptome profiling of sorted endoreduplicated nuclei from tomato fruits: how global shift in expression ascribed to DNA ploidy influences RNA-Seq data normalization and interpretation.  ... 
doi:10.1111/tpj.13783 pmid:29172253 fatcat:72opnnzq5jhepb2o6ro36u46f4

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data

Anita Grigoriadis, Alan Mackay, Jorge S Reis-Filho, Dawn Steele, Christian Iseli, Brian J Stevenson, C Victor Jongeneel, Haukur Valgeirsson, Kerry Fenwick, Marjan Iravani, Maria Leao, Andrew JG Simpson (+5 others)
2006 Breast Cancer Research  
COMP = cartilage oligomeric matrix protein; DTET = differential tumour epithelial transcriptome; ER = estrogen receptor; GO = Gene Ontology; GSEA = gene set enrichment analysis; HTR = human transcriptome  ...  These collectively comprised the differential normal epithelial transcriptome.  ...  In contrast to previously published SAGE data, comparing purified normal Heatmap of the top 50 genes from the luminal-specific and myoepithelial-specific transcriptomes Heatmap of the top 50 genes from  ... 
doi:10.1186/bcr1604 pmid:17014703 pmcid:PMC1779497 fatcat:7m7fgomytfg4bbxecgj2eno62q
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