User: Mª José Nueda

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Spain
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Posts by Mª José Nueda

<prev • 12 results • page 1 of 2 • next >
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Answer: A: maSigPro genes from clusters
... Hello, Function see.genes() gives two outputs: graphical and console outputs. Lists of the genes in each group can be obtained with these instructions: H <- see.genes(...) names(which(H$cut==1)) # for first cluster. ...   ...
written 16 months ago by Mª José Nueda90
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Answer: A: maSigPro help- p. vector error
... Hi! This error is due to rownames(design) and colnames(data) must be identical vectors and indicate array naming, as it's literaly in the details of p.vector help file. min.obs is an argument to remove genes with a lot of missing value, genes with less than this number of true numerical values wil ...
written 2.1 years ago by Mª José Nueda90
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Answer: A: row with zeros
... Hi, As you say, the error is due to there are a lot of ceros in a row (for a gene). min.obs is a parameter that controls the missing data but it doesn't control the cero values. Actually maSigPro doesn't have any argument to control de ceros. I think it is a good idea to consider this in p.vector ...
written 2.1 years ago by Mª José Nueda90
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Answer: A: maSigPro RNAseq data (counts=TRUE will not work for negative binomial)
... Hi Audra, This error is due to there are some case with a lot of zeros. Before applying maSigPro, these data must be removed. And remember that data must be normalized. Regards, Mar?a J. Nueda -----Mensaje original----- From: Audra Andrew [guest] Sent: Saturday, March 08, 2014 12:37 AM To: bioco ...
written 3.7 years ago by Mª José Nueda90
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Comment: C: maSigPro and "vars" argument
... Hi Andrea, In the regression model of each gene you will have included the "statistically significant" variables that are the variables that make change the response (gene-expression). For each gene you can have several significant variables. Examples: - A gene with flat profile for group1 and lin ...
written 6.2 years ago by Mª José Nueda90
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Answer: A: maSigPro and "vars" argument
... Dear Andrea, 1) Your experimental design is correct. 2) Your explanation about the 2 groups you have when vars="groups" is also correct. Normally the first group is a reference (the control group) and maSigPro looks for genes that have differences between other treatments and the control. If you wa ...
written 6.2 years ago by Mª José Nueda90
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Answer: A: [maSigPro] T.fit - Error in rownames(coefficients)
... Dear Maciej, This error is related to the rownames of your data. Maybe there are genes without name. Regards, Mar?a. -------------------------------------------------- From: "Maciej Jo?czyk" Sent: Wednesday, November 10, 2010 3:37 PM To: Cc: "Maciej Jo?czyk" Subject: [BioC] [maSigPro] T.fit - ...
written 7.0 years ago by Mª José Nueda90
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Answer: A: [maSigPro] Error in T.fit - NAs introduced by coercion
... Dear Maciej, This warning is not a problem. The output of T.fit function is a list. One object of this list, named "sol", contains the p-vaules of the variables that the stepwise strategy decides to include in the model. So the variables that are not considered don't have any p-value to show and we ...
written 7.6 years ago by Mª José Nueda90
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Answer: A: [maSigPro] How to analyze 2-colour microarrays?
... Dear Maciej, You can apply maSigPro with 7 time-points without splitting the data. The method is going to work well. You must split the data if the obtained models don't fit very well. Splitting the data is not implemented automatically in the maSigPro R-program and you have to elaborate a more com ...
written 7.6 years ago by Mª José Nueda90
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Answer: A: MaSigPro
... Hello, We have an adaptation of maSigPro that applies the method to groups of genes classified in similar categories. If you are interested in applying this adaptation we can send you the script . But if you apply the method to heterogeneous groups, the fitted model is not going to be a good fit. ...
written 10.1 years ago by Mª José Nueda90

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