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Old 04-10-2018, 09:47 AM   #1
yu_chem
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Location: Japan

Join Date: Mar 2015
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Default How to use SVA for removing noise from WGBS data

Hello
I'm analyzing WGBS methylome data (tissue sample) and I would like to remove noise (batch effect and blood contamination).
I read some papers about reference-free deconvolution for removing noise and I knew that SVA (surrogate variant analysis) has good performance. So I will use sva package of R https://bioconductor.org/packages/re.../html/sva.html.

However, WGBS data has problem. When I extracted CpG sites having >10 depth. A few CpG sites having 10>depth on all samples. So SVA can not apply WGBS data. In this case, imputation methods can not be used, because that CpG sites requiring imputation, are too numerous

I have two questions.
1. How do many researchers remove noise (batch effect and blood contamination) from sparse WGBS data using SVA?
2. by what criterion, many researchers select samples for one time noise removing process? e.g. Is not it no problem to apply SVA into liver-derived samples with hurt-derived samples?

I would like to know source code or detail protocol, paper for noise removal from WGBS. and above criterion.

I hope your help
Thank you
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