Biomedical subjects

Ji-Gang Zhang

Publications and source records attributed to Ji-Gang Zhang.

3 recordsLinked to original sources

PubMed2006

A non-transformation method for identifying differentially expressed genes from cDNA microarrays.

cDNA microarray data are subject to many sources of variation that have to be removed before statistical tests can be applied for identifying genes that are expressed differentially. Background correction, log-ratio transformation, and normalization, referred as the log-ratio approach, have been widely used for this purpose. However, there are some problems associated with this procedure. In this study, we proposed an alternative approach that obviates the log-ratio transformation step and goes directly to normalization after background correction. The method can estimate the "noise" effect by utilizing the information more effectively. Simulation studies were carried out to compare the feasibility and efficiency of this approach for detecting the specifically and differentially expressed genes under various conditions with the log-ratio approach. The results showed that our approach worked well and was more robust and powerful than the log-ratio approach.

Algorithms↗

PubMed2005

[Methodology of mapping quantitative trait loci for discrete traits using maximum likelihood].

The maximum likelihood method was used to compare the efficiency of interval mapping with either the threshold model or the linear model. The irfluencing factors of quantitative trait loci (QTL) detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the number of segregating population was 500. The results showed that the threshold model was superior in terms of parameter estimation. It was a more efficient and accurate model of QTL mapping for discrete traits. In addition, the accuracy of QTL mapping depended on the effect of the putative QTL, the value of heritability and incidence directly. With an increase of QTL effect, heritability and incidence of categories, the accuracy of QTL mapping improved correspondingly.

Algorithms↗

PubMed2005

Methodology of mapping quantitative trait loci for ordinal traits of disease resistance in livestock.

Methodology of QTL mapping for ordinal traits of disease resistance based on the framework of a generalized linear model (GLM) was presented. The location and effect parameters of putative QTL were estimated using maximum likelihood method. The efficiency and power were compared with the linear model (LM). The factors influencing QTL detection efficiency (e.g. QTL effect and heritability) were simulated in our study too. Daughter design with multiple families was applied,and the number of segregating population was 500. Results showed that the threshold model has a certain advantage in location estimation and power of QTL mapping, and has efficiency and accuracy for ordinal traits. In addition,the accuracy of QTL mapping depends on the effect of putative quantitative trait loci and the value of heritability. With the increase of QTL effect and heritability, the accuracy of QTL mapping improves slightly.

Animals↗