Moderator: Sean Davis

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Sean Davis23k
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National Institutes of Health, Bethesda, MD
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http://watson.nci.nih....
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Posts by Sean Davis

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Comment: C: Calculation of number of raw reads, Q30, GC content for raw data QC
... These numbers are functionally the same. No, I would not merge the fastq files. I would report two Q30 numbers and two GC numbers. In all cases where the experiment "worked" as expected, the numbers for read 1 and read 2 will be quite similar. If they are not, you NEED to know that. ...
written 9 days ago by Sean Davis23k
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Comment: C: Calculation of number of raw reads, Q30, GC content for raw data QC
... I'd report both forward and reverse Q30 and GC from FastQC, so four numbers. This is for quality control, so having all values available will avoid "hiding" bad data. ...
written 9 days ago by Sean Davis23k
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Answer: A: How to perform GSEA analysis with survival phenotype?
... Your approach of using cox regression to get an ordered list of genes is fine. From there, you can proceed to threshold based on some cutoff for significance or use a rank-based GSEA approach. ...
written 13 days ago by Sean Davis23k
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Answer: A: Add GenomicRanges to SummarizedExperiment
... Using resGR <- results(RAW_DESeq2AF, lfcThreshold = 1, format = "GRangesList") or resGR <- results(RAW_DESeq2AF, lfcThreshold = 1, format = "DataFrame") should address the issue. ...
written 13 days ago by Sean Davis23k
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Answer: A: Viewing CNV read depth data along multiple chromosomes in a single plot via R
... Take a look at ggbio. https://bioconductor.org/packages/ggbio https://www.google.com/search?q=ggbio&tbm=isch ...
written 13 days ago by Sean Davis23k
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Answer: A: Install DESeq2 and edgeR with Anaconda
... The Bioconductor project does not support bioconda directly, so your mileage may vary when using bioconda. The recommended way to install Bioconductor packages is from within R using: source("https://bioconductor.org/biocLite.R") biocLite("DESeq2") biocLite("edgeR") ...
written 13 days ago by Sean Davis23k
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Comment: C: how to extract highly correlated genes in interaction network ?
... It sounds like you'll need to learn some R before proceeding. Being able to select subsets of data in R is a skill that will serve you well. You can still use WGCNA after subsetting your data if it suits your needs. ...
written 13 days ago by Sean Davis23k
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Answer: A: how to extract highly correlated genes in interaction network ?
... You may not need the WGCNA package at all if you simply want to get correlations. Take a look at the `cor` function in R. That said, no matter what you end up doing, you will definitely want to filter your genes before doing the correlation. Only about 50% of the genes are likely expressed in eac ...
written 15 days ago by Sean Davis23k
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Answer: A: somatic variant calling with no germline sample
... If your goal is to discover new somatic variants, I am afraid that might be quite challenging because the VAST majority of variants in any sample will actually be polymorphisms and not somatic variants. Use of a set of databases of "normal" variation to remove as many germline variants as possible ...
written 3 months ago by Sean Davis23k
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News: Bioconductor 2017 Conference, Boston, July 26-28
... Join us for our annual conference! Dates: July 26 (Developer Day) - 28 Location: Dana-Farber Cancer Institute, Boston, MA, USA Registration: now open. Scholarships available. More information: https://bioconductor.org/BioC2017 The main conference (27 - 28 July) consists of morning scientific talks ...
R bioconductor conference news written 3 months ago by Sean Davis23k

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