Distributional fold change test - a statistical approach for detecting differential expression in microarray experiments.
Distributional fold change test - a statistical approach for detecting differential expression in microarray experiments.
复制标题
DOI：
10.1186/1748-7188-7-29
复制
发表时间：
2012-11-02
期刊：
影响因子：
--
通讯作者：
McDyer F
中科院分区：
文献类型：
--
作者：
Farztdinov V;McDyer F
由于在基因芯片实验中观察到的数据量大且数据强度的内在变化，不同的统计方法被用来系统地提取生物信息并量化相关的不确定性。识别差异表达基因的最简单方法是评估两种不同条件下平均强度的比率，并认为所有差异超过任意截止值的基因都是差异表达的。这种过滤方法不是一种统计检验，也没有相关的值可以表明将基因指定为差异表达或非差异表达的置信度水平。同时，折叠变化本身提供了有价值的信息，重要的是找到在表达数据处理中使用这些信息的明确方法。介绍了一种寻找差异表达基因的新方法，即分布折叠变化(DFC)检验。该方法基于对映射到三维特征空间的所有微阵列探针集的强度分布的分析，该特征空间由平均表达水平、基因表达的平均差异和总方差组成。该方法允许人们根据信噪比对每个特征进行排序，并为每个特征确定用于差分表示的置信度和功率。使用接收器工作曲线下的总面积和部分面积对新方法的性能进行了评估，并在基因总括数据库中具有独立验证的差异表达基因的11个数据集上进行了测试，并与t检验和收缩t检验进行了比较。总体而言，DFC测试表现最好--平均而言，它具有更高的敏感度和部分AUC，其升高在差异表达特征的低范围内最为突出，这对于福尔马林固定的石蜡包埋样本集来说是典型的。分布折叠变化测试是发现和排序微阵列上差异表达的命题集的一种有效方法。这种测试的应用对使用福尔马林固定石蜡包埋样本的数据集或其他系统是有利的，在这些系统中，退化效应降低了相关性调整方法对整个特征集的适用性。
Because of the large volume of data and the intrinsic variation of data intensity observed in microarray experiments, different statistical methods have been used to systematically extract biological information and to quantify the associated uncertainty. The simplest method to identify differentially expressed genes is to evaluate the ratio of average intensities in two different conditions and consider all genes that differ by more than an arbitrary cut-off value to be differentially expressed. This filtering approach is not a statistical test and there is no associated value that can indicate the level of confidence in the designation of genes as differentially expressed or not differentially expressed. At the same time the fold change by itself provide valuable information and it is important to find unambiguous ways of using this information in expression data treatment. A new method of finding differentially expressed genes, called distributional fold change (DFC) test is introduced. The method is based on an analysis of the intensity distribution of all microarray probe sets mapped to a three dimensional feature space composed of average expression level, average difference of gene expression and total variance. The proposed method allows one to rank each feature based on the signal-to-noise ratio and to ascertain for each feature the confidence level and power for being differentially expressed. The performance of the new method was evaluated using the total and partial area under receiver operating curves and tested on 11 data sets from Gene Omnibus Database with independently verified differentially expressed genes and compared with the t-test and shrinkage t-test. Overall the DFC test performed the best – on average it had higher sensitivity and partial AUC and its elevation was most prominent in the low range of differentially expressed features, typical for formalin-fixed paraffin-embedded sample sets. The distributional fold change test is an effective method for finding and ranking differentially expressed probesets on microarrays. The application of this test is advantageous to data sets using formalin-fixed paraffin-embedded samples or other systems where degradation effects diminish the applicability of correlation adjusted methods to the whole feature set.
登录
查看更多内容
从微阵列数据中检测出差异表达基因的加权平均差异方法。
影响因子：
1
作者：
Kadota, Koji;Nakai, Yuji;Shimizu, Kentaro
通讯作者：
Shimizu, Kentaro
影响因子：
5.8
作者：
Hubbell, E;Liu, WM;Mei, R
通讯作者：
Mei, R
影响因子：
3
作者：
Dalman MR;Deeter A;Nimishakavi G;Duan ZH
通讯作者：
Duan ZH
影响因子：
3.8
作者：
Burleigh, D. W.;Kendziorski, C. M.;Golos, T. G.
通讯作者：
Golos, T. G.
影响因子：
2.1
作者：
Irizarry, RA;Hobbs, B;Speed, TP
通讯作者：
Speed, TP