User: DSP

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DSP0
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Posts by DSP

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Comment: C: Limma for paired and unpaired analysis with adjustment for categorical and conti
... Thank you so much for the details. I've estimated cell counts using estimateCellCounts function from minfi: cell_counts <- estimateCellCounts(RGSet.raw, compositeCellType = "Blood",processMethod = "preprocessNoob", probeSelect = "auto",cellTypes = c("CD8T","CD4T", "NK","Bcell","Mono","Gran"),re ...
written 2.6 years ago by DSP0 • updated 2.6 years ago by Ryan C. Thompson7.3k
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Comment: C: Limma for paired and unpaired analysis with adjustment for categorical and conti
... Dear Dr Thompson. Thanks for the suggestion. I have done analysis on my paired data (pre-post comparison) using duplicate correlation function and modelling batch effects in the design matrix. I have done sequential adjustment for covariates: 1) Unadjusted data 2) Adjusted for batch effects:chip ...
written 2.6 years ago by DSP0
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Comment: C: Limma for paired and unpaired analysis with adjustment for categorical and conti
... Dear Dr Thompson, Thanks for correcting the code, it seems to be working fine now. I was wondering what would be a better strategy to adjust for batch effects 1) Apply combat and use batch corrected values for differential methylation analysis  2) Use batch variables in the design matrix My data ...
written 2.6 years ago by DSP0
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Comment: C: Limma for paired and unpaired analysis with adjustment for categorical and conti
... Also I need to the same adjustments for another study design, where I have data from same individual at two timepoints. Baseline samples are all at stage 1 who either reach Stage 2 or Stage 3 at follow up timepoint. I wish to capture differentially methylated CpGs resulting in transition from Stage ...
written 2.6 years ago by DSP0
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Limma for paired and unpaired analysis with adjustment for categorical and continuous variables
... Dear Gordon and all, I'm analyzing Illumina 450K methylation data with following study design: Study design:  I have individuals at a given time-point from three different stages: Stage 1, 2 and 3 and I wish to identify differentially methylated CpGs in these groups. Stage 1 vs Stage 2; Stage 1 vs ...
limma lmfit illumina450k written 2.6 years ago by DSP0 • updated 2.6 years ago by Ryan C. Thompson7.3k
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Comment: C: Analyzing pre/post (longitudinal) data using limma/lme4 with adjustment for cont
... Hi Aaron, Apologies for delay in response. 1) Thanks for the correction. I have transformed my beta values to M-values for downstream analysis 2) The intervention here is a qualitative, life style intervention and the difference is captured in the outcome. Moreover, systematic differences in samp ...
written 2.6 years ago by DSP0
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Comment: C: ComBat: Adjustment for 3experimental variables
... Also, with my data, adjustment for Sentrix ID alone removed the batch effects coming from Sentrix ID, Experimental batch and BCD batch!! So I've adjusted my data just for Sentrix ID.   ...
written 2.9 years ago by DSP0
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Comment: C: ComBat: Adjustment for 3experimental variables
... Hi Chris, Thanks for your inputs.  I have done batch adjustment by combat.mc function from ENmix using individual batches and also all possible permutation combinations with different orders. At least with my data, final results (beta/M values after combat) did not differ with respect to the metho ...
written 2.9 years ago by DSP0
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ComBat: Adjustment for 3experimental variables
... Hi! I'm working on dataset with 100 samples run on Illumina Infinium HumanMethylation450 BeadChip array. I've performed PCA on all samples using all the QC passed probes before and after normalization and tested for association between each PC and independent experimental variables like BCD batch ...
illumina450k combat sva enmix combat.mc written 2.9 years ago by DSP0
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Comment: C: Analyzing pre/post (longitudinal) data using limma/lme4 with adjustment for cont
... Yes, but I have very few samples, around 25 pairs per group-which are sub-divided by their class. Since I'm primarily interested in class and not group, I've not included group.  Can I directly include it in the model by: model.matrix(~SibShip+Treat+targets$group+targets$age+targets$BMI+targets$CD ...
written 3.1 years ago by DSP0

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