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two channel data normalization limma

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Maite Iriondo ▴ 30

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Dear Bioconductor Community, I am Maite Iriondo and I am currently finishing a MSc programme, doing my thesis in microarray data analysis even though I lack of bioinformatic background as I come from Food Science. I am trying to understand the different options for normalizing two channel microarray data, and I have very basic questions that I would appreciate if they could be answered. 1- I have read in the literature that two channel data can be analized by single channel and two channel normalization approaches (using log intensities and log ratios respectively) (Yang and Thorne, 2003). However, I do not understand how these approaches are applied in the limma package (Bioconductor). For two channel normalization you use a within array and between array normalization and for single channel analysis you use just the options of the between array normalization function? 2- My data was partially analised with one scanner and then changed to another, which gives huge differences on the widths of the boxplots. I read in Smyth and Speed (2003) that scale normalization between arrays is recommended. Which function in limma does this calculation? is it the normalizeBetweenArrays (method= scale)? 3- My data consists of a series of microarrays from P.putida growth experiments at different temperatures, taking samples at different time points for each temperature. Also, a second experiment was carried doing microarrays using adapted and non adapted cells to low temperatures of P. putida at different temperatures and again different time points for each temperature. As a summary: A) Microarrays at 30, 10 and 5ºC with 5 time point samples (eg. At 30ºC I have data from 5 microarrays that correspond to 5 time points in which the cells were taken) B) Microarrays at 5 and 10ºC using adapted and non adapted cells with 5 time point samples In the beginning I normalized all the data together using different options of normalizeWithinArrays() and normalizeBetweenArrays(), but the resulting MAplots and boxplots dont look too good. I was wondering if I should separate experiments A and B. Also, I read that for time series experiments you should do single channel analysis. But for comparing gene expression between different temperatures I should use two channel analysis. This means that I should analyse each temperature separately using a single channel approach and then use a two channel approach for all the data to compare gene expression between temperatures? Thank you for your time and effort in advanced. I know that these questions are very basic but I am trying to put my concepts in order. Maite [[alternative HTML version deleted]]

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ADD COMMENT • link updated 11.8 years ago by Guest User ★ 13k • written 11.8 years ago by Maite Iriondo ▴ 30

score 0 · Answer 1 · 2012-07-11

Dear Bioconductor Community, I am Maite Iriondo and I am currently finishing a MSc programme, doing my thesis in microarray data analysis even though I lack of bioinformatic background as I come from Food Science. I am trying to understand the different options for normalizing two channel microarray data, and I have very basic questions that I would appreciate if they could be answered. 1- I have read in the literature that two channel data can be analized by single channel and two channel normalization approaches (using log intensities and log ratios respectively) (Yang and Thorne, 2003). However, I do not understand how these approaches are applied in the limma package (Bioconductor). For two channel normalization you use a within array and between array normalization and for single channel analysis you use just the options of the between array normalization function? 2- My data was partially analised with one scanner and then changed to another, which gives huge differences on the widths of the boxplots. I read in Smyth and Speed (2003) that scale normalization between arrays is recommended. Which function in limma does this calculation? is it the normalizeBetweenArrays (method= scale)? 3- My data consists of a series of microarrays from P.putida growth experiments at different temperatures, taking samples at different time points for each temperature. Also, a second experiment was carried doing microarrays using adapted and non adapted cells to low temperatures of P. putida at different temperatures and again different time points for each temperature. As a summary: A) Microarrays at 30, 10 and 5??C with 5 time point samples (eg. At 30??C I have data from 5 microarrays that correspond to 5 time points in which the cells were taken) B) Microarrays at 5 and 10??C using adapted and non adapted cells with 5 time point samples In the beginning I normalized all the data together using different options of normalizeWithinArrays() and normalizeBetweenArrays(), but the resulting MAplots and boxplots dont look too good. I was wondering if I should separate experiments A and B. Also, I read that for time series experiments you should do single channel analysis. But for comparing gene expression between different temperatures I should use two channel analysis. This means that I should analyse each temperature separately using a single channel approach and then use a two channel approach for all the data to compare gene expression between temperatures? Thank you for your time and effort in advanced. I know that these questions are very basic but I am trying to put my concepts in order. Maite -- output of sessionInfo(): . -- Sent via the guest posting facility at bioconductor.org.