TY - JOUR AU - Ryan, Colm AU - Greene, Derek AU - Cagney, Gerard AU - Cunningham, Pádraig PY - 2010 DA - 2010/04/20 TI - Missing value imputation for epistatic MAPs JO - BMC Bioinformatics SP - 197 VL - 11 IS - 1 AB - Epistatic miniarray profiling (E-MAPs) is a high-throughput approach capable of quantifying aggravating or alleviating genetic interactions between gene pairs. The datasets resulting from E-MAP experiments typically take the form of a symmetric pairwise matrix of interaction scores. These datasets have a significant number of missing values - up to 35% - that can reduce the effectiveness of some data analysis techniques and prevent the use of others. An effective method for imputing interactions would therefore increase the types of possible analysis, as well as increase the potential to identify novel functional interactions between gene pairs. Several methods have been developed to handle missing values in microarray data, but it is unclear how applicable these methods are to E-MAP data because of their pairwise nature and the significantly larger number of missing values. Here we evaluate four alternative imputation strategies, three local (Nearest neighbor-based) and one global (PCA-based), that have been modified to work with symmetric pairwise data. SN - 1471-2105 UR - https://doi.org/10.1186/1471-2105-11-197 DO - 10.1186/1471-2105-11-197 ID - Ryan2010 ER -