Investigation and comparison of the preprocessing algorithms for microarrayanalysis for robust gene expression calculation and performance analysis of technical replicates

2006-04-19
İLK, HAKKI GÖKHAN
İlk Dağ, Özlem
KONU KARAKAYALI, ÖZLEN
ÖZDAĞ, Hilal
Preprocessing of microarray data involves the necessary steps of background correction, normalization and summarization of the raw intensity data obtained from cDNA or oligo-arrays before statistical analysis. Several algorithms, namely RMA, dChip, and MAS5 exist for the preprocessing of Affymetrix microarray data. Previous studies have identified RMA as one of most accurate algorithms while MAS5 was characterized with lower accuracy and sensitivity levels. In this study, performance of different preprocessing algorithms have been compared in terms of ROC characteristics of pairwise intensity differences of microarray replicates. Our findings indicated that all three algorithms predicted in similar order the quality of the technical replicates obtained from a selected set of latin square experiments [1]. On the other hand, RMA exhibited higher performance in terns of accuracy by maximizing the area under the receiver operating curve. The proposed method also is useful for detection of global and/or local artifacts associated within the technical replicas of a microarray experiment. Therefore this study is unique in the sense that it provides an extensive investigation and comparison of preprocessing algorithms and proposes a novel method for the detection and identification of fine technical replicate pair.
IEEE 14th Signal Processing and Communications Applications

Suggestions

Determination of the effect of polyadenylation SLR values on microarray data classification
Aslan, Ümit; Can, Tolga; Department of Computer Engineering (2014)
Microarray data classification is generally used to predict unknown sample outcomes by the help of models created using the preprocessed and categorized microarray data that includes gene expression values. Preparation of microarray experiments, design of Affymetrix chips and availability of previous microarray experiments give the opportunity to extract a new kind of data; differential expressions of proximal and distal probes (Short to Long Ratio -SLR- values), which is used to predict the alternative pol...
Investigation of Stationarity for Graph Time Series Data Sets
Güneyi, Eylem Tuğçe; Vural, Elif (2021-01-07)
Graphs permit the analysis of the relationships in complex data sets effectively. Stationarity is a feature that facilitates the analysis and processing of random time signals. Since graphs have an irregular structure, the definition of classical stationarity does not apply to graphs. In this study, we study how stationarity is defined for graph random processes and examine the validity of the stationarity assumption with experiments on synthetic and real data sets.
Evaluation of discrete ordinates method for radiative transfer in rectangular furnaces
Selçuk, Nevin (1997-01-01)
The discrete ordinates method (DOM) and discrete transfer method (DTM) were evaluated from the viewpoints of both predictive accuracy and computational economy by comparing their predictions with exact solutions available from a box-shaped enclosure problem with steep temperature gradients. Comparative testing shows that the S-4 approximation produces better accuracy in radiative energy source term than in flux density in three orders of magnitude less CPU time than that required by the DTM. The S-4 approxi...
Evaluation of the site amplification factors estimated by equivalent linear site response analysis using time series and random vibration theory based approaches
Stanko, Davor; Gülerce, Zeynep; Markusic, Snjeana; Salic, Radmila (2019-02-01)
The objective of this study is to estimate and compare the site amplification factors (AFs) using two different one dimensional (1-D) equivalent-linear (EQL) site response analysis approaches: the time series (TS) approach and the random vibration theory (RVT) based method. For this purpose, random soil profiles combined with different soil types, EQL soil properties, and unit weights are tested at several input ground motion levels. Analysis results showed that the AFs estimated by the TS-approach are syst...
Analysis and Further Improvement of Fine Resolution Frequency Estimation Method From Three DFT Samples
Candan, Çağatay (Institute of Electrical and Electronics Engineers (IEEE), 2013-09-01)
The bias and mean square error (MSE) analysis of the frequency estimator suggested in [1] is given and an improved version of the estimator, with the removal of estimator bias, is suggested. The signal-to-noise ratio (SNR) threshold above which the bias removal is effective is also determined.
Citation Formats
H. G. İLK, Ö. İlk Dağ, Ö. KONU KARAKAYALI, and H. ÖZDAĞ, “Investigation and comparison of the preprocessing algorithms for microarrayanalysis for robust gene expression calculation and performance analysis of technical replicates,” presented at the IEEE 14th Signal Processing and Communications Applications, Antalya, Turkey, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54832.