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8 views

regression test or two bloc PLS model to prove a gene expression matrix relationship

I have two gene expression matrices, matrix A coming from a set of two hypothetically different cells while matrix B is coming (for certain) from only one of them. The structure of a gene expression ...
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31 views

Preparing microarray data for batch effect detection by anova

I am working on a meta-analysis of clear-cell renal cell carcinoma data. The data are gene expression values obtained out of Affymetrix Human Genome U133 Plus 2.0 arrays. Currently, I am trying to ...
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16 views

counfounded batch effects in microarray dataset - can I do partial experiment redesign?

I'm working with a microarray data set where the batches are completely confounded treatment time, i.e. time t1 is all in batches b1 and b2, and time t2 is all in batches b3, b4, and b5. I know this ...
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22 views

Understanding Differential Expression Analysis in Microarray Experiments

Can someone please provide me a simple explanation of how differential gene expression analysis works? I know that this method is described in [1] and used in the R package limma. [1] Smyth, Gordon ...
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1answer
38 views

Calculating variance for microarray data?

I have microarray data in which there are three biological replicates for each of the conditions. I am interested in a numerical estimate of how well the replicates correspond with one another, so I ...
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20 views

Selecting genes more affected in treatment A than treatment B

We are trying to test the hypothesis that a mild mutation of a gene has few effects on the expression of the transcriptome than complete deletion. Further we wish to test the hypothesis that the genes ...
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31 views

How to assess variance in whole genome biological data?

I am a biologist by training and have started a project assessing “variability” using microarray data. The microarray takes a measurement (expression level) of ~20,000 genes for each sample, and I ...
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1answer
35 views

Selecting gene list for subsequent analysis in problematic microarray experiement

I have an experimental design problem and I'm not sure which would the best way to proceed. We have a micro-array experiment in which we compare gene expression profiles between 2 groups of patients. ...
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34 views

Simulate microarray technical error

I need to simulate some microarray experiment datasets. I have the levels of expression of a set of synthetic genes in different experimental conditions. For simplicity of the method this levels are ...
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3answers
62 views

Is this really suited for 2-way ANOVA?

My dataset is a biological analysis of a disease which takes 3 months to develop, and we're looking at treatment of that disease. The data is gene expression data and we want to identify changes in ...
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44 views

Dealing with perfectly confounded microarray experiment

I need to compare microarray data, where all of the "cases" were hybridized in one batch and all of the "controls" in another, so I have no way of removing this batch effect. What would be the best ...
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1answer
70 views

Suitable analysis for my data…?

everyone, I'm new at the statistical analysis so I need some help from more experienced people. I'm working with biological data from gene expression analysis. I have 5 treatments (1 parental toxin; 3 ...
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225 views

Why my MA plot shows a pattern/trend while the normalized expression values not?

I am doing microarray analysis using bioconductor. I first performed the quality checks which was ok according to recommendations. I created an MA plot after normalizing the AffyBatch data. My MA ...
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2answers
141 views

A way to test for enrichment of differentially expressed genes in a genomic location

I have an experiment where I expect a certain genomic location to influence gene expression levels of nearby genes. I have data for expression levels (Agilent 4x44 microarrays, Drosophila) in two ...
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1answer
119 views

Limit of quantile normalization

Is quantile normalization adequate for normalizing data with very few samples? For example this microarray data. Typically after normalization we'd like to compare ...
2
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0answers
193 views

Simulated Microarray data

I would like to generate synthetic microarray data sets for simulation purposes. The web and literature search so far returned the following: Microarray Simulator - It provides Matlab skripts to ...
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1answer
134 views

Denoising of microarray data using PCA

I'm looking for references and comments regarding the validaty of the following method for data denoising, which I found while reading a code doing analysis of some gene expression dataset. The ...
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2answers
149 views

Should false discovery be controlled at the data acquisition level, or should this be at the data interpretation level?

Should false discovery be controlled at the data acquisition level, or should this be at the data interpretation level? I have an experiment in which microarrays were used to quantify the expression ...
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2answers
346 views

Interpret Silhouette plot for large microarray dataset

For a microarray experiment with ~40,000 probes and ~30 samples I used the clara function from R to cluster my expression matrix. How do I interpret this silhouette plot? Firstly, I don't ...
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103 views

shorth function in R and microarray analysis

I'm trying to reproduce an analysis (a transcriptomic analysis) that I found in a research paper. The methods section says: After normalization an expression threshold for each cell line was ...
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2answers
2k views

Is the overlap between two gene expression samples significant?

I have performed an experiment to study the response of a yeast (that contains 5000 genes) to stress caused by heat shock. I have one list of 48 genes that are overexpressed at 37ºC and another list ...
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2answers
562 views

Is cross-validation an effective approach for feature/model selection for microarray data?

I've been working with WEKA to build class predictors using this (rather old..) breast cancer dataset. The dataset is divided into a training and a test set. I've been testing different learning ...
3
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1answer
449 views

Testing for equality of variance in permutations (microarray analysis with bioconductor)

I have measured whole-genome gene expression in two groups of animals, n=6 in each group. My goal is to detect differentially expressed genes - pretty standard analysis. The typical thing to do, and ...
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1answer
3k views

How to highlight predefined groups in PCA individual map?

This has a simple answer but it has been eluding me nonetheless. I have been trying to build a PCA plot from scratch with the ability to plot predefined groups in different colors. I can plot PCA ...
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85 views

Using background genes to evaluate gene expression level

I have some gene measurements from a microarray experiment. On each array, I have a set of "non expressed" background genes. I have three replicate measurements for some tissues. How to use the ...
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2answers
5k views

Calculating the probability of gene list overlap between an RNA seq and a ChIP-chip data set

Hopefully someone on these forums can help me out with this basic problem in gene expression studies. I did deep sequencing of an experimental and a control tissue. I then obtained fold enrichment ...
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111 views

What does the gene set score tell in GSA analysis?

I carrying out a gene set analysis to investigate if a list of genes are differentially expressed before and after a medical treatment (paired analysis). The list of genes was made (a priori) by a ...
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79 views

microRNA analysis statistical methodology review

I am doing a review of statistical methodology used for microRNA data obtained from Affymetrix platform. I have data from 178 patients and their prognosis information as well as recurrence of disease ...
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1answer
96 views

Comparing numbers of p-values from many linear models

My current dataset has three conditions, and we've measured the activity levels of 10,000 genes in each condition. Replicated 8 times. Using 10,000 linear models, we determine for each pair of ...
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1answer
3k views

How does quantile normalization work?

In gene expression studies using microarrays, intensity data has to be normalized so that intensities can be compared between individuals, between genes. Conceptually, and algorithmically, how does ...
5
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2answers
171 views

Adding high-dimensional data to mutivariate Cox model

I have a survival cancer clinical trials dataset from which I have generated Cox models using forward likelihood ratio testing within R. These models are based on 'traditional' cancer variables (eg. ...
2
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1answer
392 views

How to do weighted pair hierarchical clustering in R?

Here is an example of hierarchical clustering of genes in the microarray data using the weighted pair gene method in Spotfire. I am not sure how to do this in ...
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5answers
2k views

Clustering genes in a time course experiment

I have seen a few queries on clustering in time series and specifically on clustering, but I don't think they answer my question. Background: I want to cluster genes in a time course experiment in ...
32
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3answers
13k views

Best way to present a random forest in a publication?

I am using the random forest algorithm as a robust classifier of two groups in a microarray study with 1000s of features. What is the best way to present the random forest so that there is enough ...
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3answers
145 views

Correcting experiment results

We have performed a microarray screening of about 200 samples. In each sample we measure about 100 different variables. For technical reasons the screening of these 200 samples was divided into two ...