Adaptive threshold to detect biologically meaningful changes in microarray data.
To detect changes in gene expression data from DNA microarrays, a fixed threshold value is widely used. However, it is not always guaranteed that a threshold value which is appropriate for highly expressed genes is suitable for genes with low expression. In this study, aiming at detecting biologically meaningful changes from a wide range of expression levels, we proposed an adaptive threshold method. The performance of the proposed method was investigated using publicly available expression data.
Fukuoka
Yutaka
Y
School of Biomedical Science, Tokyo Medical and Dental University, Japan. fukuoka.bsm@tmd.ac.jp
Inaoka
Hidenori
H
Noshiro
Makoto
M
D000465:Algorithms; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted