Makowski Mateusz, Archer Kellie J
Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA.
Cancer Inform. 2015 Apr 29;14(Suppl 2):97-105. doi: 10.4137/CIN.S17278. eCollection 2015.
The cytokinesis-block micronucleus (CBMN) assay can be used to quantify micronucleus (MN) formation, the outcome measured being MN frequency. MN frequency has been shown to be both an accurate measure of chromosomal instability/DNA damage and a risk factor for cancer. Similarly, the Agilent 4×44k human oligonucleotide microarray can be used to quantify gene expression changes. Despite the existence of accepted methodologies to quantify both MN frequency and gene expression, very little is known about the association between the two. In modeling our count outcome (MN frequency) using gene expression levels from the high-throughput assay as our predictor variables, there are many more variables than observations. Hence, we extended the generalized monotone incremental forward stagewise method for predicting a count outcome for high-dimensional feature settings.
胞质分裂阻滞微核（CBMN）试验可用于量化微核（MN）的形成，所测量的结果是MN频率。MN频率已被证明是染色体不稳定/DNA损伤的准确指标，也是癌症的一个风险因素。同样，安捷伦4×44k人类寡核苷酸微阵列可用于量化基因表达变化。尽管存在公认的量化MN频率和基因表达的方法，但对于两者之间的关联却知之甚少。在用高通量试验中的基因表达水平作为预测变量来建模我们的计数结果（MN频率）时，变量比观测值多得多。因此，我们扩展了广义单调递增前向逐步法，以预测高维特征设置下的计数结果。
