User: davide risso

gravatar for davide risso
davide risso380
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380
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Trusted
Location:
Weill Cornell Medicine
Twitter:
drisso1893
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48 minutes ago
Joined:
5 years, 6 months ago
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r***********@gmail.com

Posts by davide risso

<prev • 71 results • page 1 of 8 • next >
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Comment: C: What to use: PCA or tSNE dimension reduction in DESeq2 analysis?
... Since Mike mentioned the ZINB-WaVE approach, I will add a few more things to my comment on twitter. The advantage of PCA or ZINB-WaVE is that these are factor analysis models, hence there is a clear interpretation of the reduced space in which you do the clustering (in the case of ZINB-Wave, the ma ...
written 26 days ago by davide risso380
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Answer: A: RNAseq Analysis using RUVs
... Hi, it is definitely best to combine all the data into one matrix, normalize, and test for differential expression in one go. This will allow you to estimate the variance across all of your samples, which should give you more power. Note that since you are interested in the pairwise differences, y ...
written 26 days ago by davide risso380
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Answer: A: Decide normalisation method in RUVseq for RNAseq data
... Hi, which is the "best" normalization is not easy to say, since we don't know the ground truth and in most cases the answer will be dataset dependent. However, there is extensive literature on comparison of normalization approaches, just looking for "RNA-seq normalization" will return many hits in ...
written 4 weeks ago by davide risso380
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Comment: C: BiocParallel::bplapply() performance with MulticoreParam() is worse than mclappl
... Thanks Martin and Johannes! Both of your suggestions are appreciated! I agree with Martin's point on vectorizing operations, but I came across this behavior and wanted to get your opinion on this. ...
written 6 weeks ago by davide risso380
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BiocParallel::bplapply() performance with MulticoreParam() is worse than mclapply()
... Dear all, I'm having some performance issues with BiocParallel::bplapply that I think are somewhat related to this old post: https://support.bioconductor.org/p/75945/ I have started a new post because I'm using a much newer version of BiocParallel here (1.11.2), but I will use the same example: ...
biocparallel parallel written 6 weeks ago by davide risso380
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Answer: A: Fundamental questions about DESeq2 and RUVs in targeted gene set of 500
... Hi, I will let Mike chime in for the DESeq2 specific questions, but here are my two cents. > should we be using any particular normalization options in DESeq2, given that there is no group of genes for which we expect no change at all? In other words, what are the implications of using a target ...
written 10 weeks ago by davide risso380
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Answer: A: How to determine a set of empirical control 'genes' using RUVSeq
... Of course 5000 should not be considered as a one-fits-all number. We just empirically found that that number of genes was OK in that dataset. The first question is whether there are stable repeats to start with. Could it be that all the repeats are influenced by the KO? Assuming the answer is no, ...
written 4 months ago by davide risso380
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Answer: A: Can FPKM or TPM values be used as RUVs input ?
... Hi Wei, RUVSeq is designed to work with gene-level counts. If you are working with TPM or FPKM quantities, you may want to use the ruv package on CRAN or the RUVnormalize package in Bioconductor, depending if you have a supervised or unsupervised problem. Although these packages were designed for ...
written 5 months ago by davide risso380
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Answer: A: Appropriate to apply RUVSeq to exon bin counts for DEXSeq?
... Hi Adam, sorry for the late response. Provided that you can identify negative control exons, I don't see any problem with applying RUVSeq to exon data. You should be able to pass the factors of unwanted variation to DEXSeq in the design matrix, in a similar way as you would do with DESeq. We had s ...
written 5 months ago by davide risso380
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Answer: A: Raw read count Vs EdgeR normzlized read count for RUVg normalization
... Dear Venu, please note that in our paper (and experience) we see that often normalizing the data using the ERCC spike ins as negative controls does not work as well as using endogenous genes, so it's not surprising that your RLE plots don't look great after RUVg with ERCC as negative controls. Do ...
written 8 months ago by davide risso380

Latest awards to davide risso

Scholar 4 months ago, created an answer that has been accepted. For A: RUVseq PCA on raw data, whereas DESeq suggests stabilization
Scholar 15 months ago, created an answer that has been accepted. For A: Normalisation before RUVg and RUV2?
Scholar 15 months ago, created an answer that has been accepted. For A: Issue with RUVs
Scholar 15 months ago, created an answer that has been accepted. For A: effect of polyploidy level on RUVs normalisation
Scholar 15 months ago, created an answer that has been accepted. For A: RUVseq using RUVg most non-differential expressed genes
Scholar 15 months ago, created an answer that has been accepted. For A: RUVseq PCA on raw data, whereas DESeq suggests stabilization
Teacher 15 months ago, created an answer with at least 3 up-votes. For A: RUVseq PCA on raw data, whereas DESeq suggests stabilization
Scholar 20 months ago, created an answer that has been accepted. For A: Normalisation before RUVg and RUV2?
Teacher 20 months ago, created an answer with at least 3 up-votes. For A: RUVseq PCA on raw data, whereas DESeq suggests stabilization
Scholar 20 months ago, created an answer that has been accepted. For A: Normalisation before RUVg and RUV2?
Scholar 2.2 years ago, created an answer that has been accepted. For A: Normalisation before RUVg and RUV2?

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