Objective(s): Alternative normalization methods were proposed to solve the biased information of SPM in the study of neurodegenerative disease. The objective of this study was to determine the most suitable count normalization method for SPM analysis of a neurodegenerative disease based on the results of different count normalization methods applied on a prepared digital phantom similar to one ...

We proposed and optimized a simple method of temporal subtraction image between successive bone single photon emission computed tomography (SPECT) images for supporting interpretation of temporal changes, and we evaluated its clinical utility. This method consisted of image registration, count normalization, and image subtraction. For image registration, we used a BEAT-Tl software. For count no...

INTRODUCTION Despite normalization of total CD4 counts, ongoing immune dysfunction is noted amongst those on antiretroviral therapy (ART). Low CD4/CD8 ratio is associated with a high risk of AIDS and non-AIDS events and may act as a marker of immune senescence [1]. This ratio is improved by ART although normalization is uncommon (~7%) [2]. The probability of normalization of CD4 count is improv...

The R/Bioconductor package, TCC, provides users with a robust and accurate framework to perform differential expression (DE) analysis of tag count data. We recently developed a multi-step normalization method (TbT; Kadota et al., 2012 [3]) for two-group RNA-seq data. The strategy (called DEGES) is to remove data that are potential differentially expressed genes (DEGs) before performing the data...

December 22, 2016 Type Package Title TCC: Differential expression analysis for tag count data with robust normalization strategies Version 1.14.0 Author Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota Maintainer Jianqiang Sun , Tomoaki Nishiyama Description This package provides a series of functions for performing ...

April 26, 2017 Type Package Title TCC: Differential expression analysis for tag count data with robust normalization strategies Version 1.16.0 Author Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota Maintainer Jianqiang Sun , Tomoaki Nishiyama Description This package provides a series of functions for performing dif...

We examined RNA-Seq data on 211 biological samples from 24 different Arabidopsis experiments carried out by different labs. We grouped the samples according to tissue types, and in each of the groups, we identified genes that are stably expressed across biological samples, treatment conditions, and experiments. We fit a Poisson log-linear mixed-effect model to the read counts for each gene and ...

BACKGROUND Differential expression analysis on the basis of RNA-Seq count data has become a standard tool in transcriptomics. Several studies have shown that prior normalization of the data is crucial for a reliable detection of transcriptional differences. Until now it has not been clear whether and how the transcriptomic approach can be used for differential expression analysis in metatranscr...