The Experts below are selected from a list of 39 Experts worldwide ranked by ideXlab platform
Daniel Tranchina - One of the best experts on this subject based on the ideXlab platform.
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MA Plot for dilution study.
2019Co-Authors: Rodoniki Athanasiadou, Benjamin Neymotin, Nathan Brandt, Wei Wang, Lionel Christiaen, David Gresham, Daniel TranchinaAbstract:MA Plot for mean RNA abundance (z-values) for libraries prepared with high- and low-dilution spike-in aliquots. The abundance zi,j corresponding to count yi,j was obtained by the MAximum likelihood norMAlization zi,j = yi,j/νj in Eq (2). The ordinates of the scatter Plot (one point for each transcript) should be centered around zero, which corresponds to equal inferred transcript abundance for libraries prepared with high- and low-dilution spike-in aliquots.
Zhang Guo-fen - One of the best experts on this subject based on the ideXlab platform.
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NorMAlization for microarray data:the weight function of local weight regression
2010Co-Authors: Zhang Guo-fenAbstract:Local weight regression (Lowess) is a kind of widely used method,which need used to be given a lot of parameters and weight function. When this method is used to norMAlize data,thrice weight function is always used. So we want to know about the situation in which the noise of data obeys a distribution with heavy tail occurs what kind of weight function should we select. First the simulation data and the noise obeys t distribution with different degree of freedom are given,then the data by the Lowess method with different weight function is norMAlized,and finally sum of residual,the correlation between M after norMAlization and A,MA-Plot are used to evaluate the weight function,and their relationship is gained.
Rodoniki Athanasiadou - One of the best experts on this subject based on the ideXlab platform.
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MA Plot for dilution study.
2019Co-Authors: Rodoniki Athanasiadou, Benjamin Neymotin, Nathan Brandt, Wei Wang, Lionel Christiaen, David Gresham, Daniel TranchinaAbstract:MA Plot for mean RNA abundance (z-values) for libraries prepared with high- and low-dilution spike-in aliquots. The abundance zi,j corresponding to count yi,j was obtained by the MAximum likelihood norMAlization zi,j = yi,j/νj in Eq (2). The ordinates of the scatter Plot (one point for each transcript) should be centered around zero, which corresponds to equal inferred transcript abundance for libraries prepared with high- and low-dilution spike-in aliquots.
David Gresham - One of the best experts on this subject based on the ideXlab platform.
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MA Plot for dilution study.
2019Co-Authors: Rodoniki Athanasiadou, Benjamin Neymotin, Nathan Brandt, Wei Wang, Lionel Christiaen, David Gresham, Daniel TranchinaAbstract:MA Plot for mean RNA abundance (z-values) for libraries prepared with high- and low-dilution spike-in aliquots. The abundance zi,j corresponding to count yi,j was obtained by the MAximum likelihood norMAlization zi,j = yi,j/νj in Eq (2). The ordinates of the scatter Plot (one point for each transcript) should be centered around zero, which corresponds to equal inferred transcript abundance for libraries prepared with high- and low-dilution spike-in aliquots.
Lionel Christiaen - One of the best experts on this subject based on the ideXlab platform.
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MA Plot for dilution study.
2019Co-Authors: Rodoniki Athanasiadou, Benjamin Neymotin, Nathan Brandt, Wei Wang, Lionel Christiaen, David Gresham, Daniel TranchinaAbstract:MA Plot for mean RNA abundance (z-values) for libraries prepared with high- and low-dilution spike-in aliquots. The abundance zi,j corresponding to count yi,j was obtained by the MAximum likelihood norMAlization zi,j = yi,j/νj in Eq (2). The ordinates of the scatter Plot (one point for each transcript) should be centered around zero, which corresponds to equal inferred transcript abundance for libraries prepared with high- and low-dilution spike-in aliquots.
