User: Beginner

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Beginner50
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Posts by Beginner

<prev • 25 results • page 1 of 3 • next >
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Comment: C: DNA methylation analysis without raw data IDAT files
... Hi James, I tried reading the methylation data with readTCGA. But it is not working. May be I'm wrong somewhere The methylation data is in a dataframe "df" with rows as probes and columns like Chromosome, Start position, End position, Gene and Samples like mentioned in my question.  library(minf ...
written 24 days ago by Beginner50
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Comment: C: DNA methylation analysis without raw data IDAT files
... yes, I didn't find anything to read methylation data from matrix with champ. Any idea about any other functions? ...
written 24 days ago by Beginner50
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DNA methylation analysis without raw data IDAT files
... Hi, I'm interested in working on DNA methylation data. I have downloaded TCGA data from GDC harmonised archive. There are no IDAT files.  IDAT files are available only for GDC legacy archive.  Dataframe "data" is with 485577 probes as rows and 439 columns. There are columns like Chromosome, Start ...
minfi champ R tcga illimina 450k methylation written 29 days ago by Beginner50 • updated 29 days ago by Yuan Tian40
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Comment: C: Possible ways to select differential expressed genes using DeSeq2 or edgeR
... Hi Klenk, The one which you posted above  write.csv(as.data.frame(res[!is.na(res$padj) & res$padj < 0.1 & res$log2FoldChange > log2(1.5),]), file="DEGs.csv") is not the right one to select DEG's based on FC > 1.5 and FDR < 0.1. From this [https://support.bioconductor.org/p/867 ...
written 10 weeks ago by Beginner50
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Comment: C: Possible ways to select differential expressed genes using DeSeq2 or edgeR
... Yes, this worked. A question about the PCA plot I posted. Is the sample behaviour is due to batch effect? If yes how can I remove that and proceed to differential analysis? ...
written 10 weeks ago by Beginner50
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Comment: C: Possible ways to select differential expressed genes using DeSeq2 or edgeR
... But this gave an error. Error: logical subscript contains NAs​ ...
written 10 weeks ago by Beginner50
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Comment: C: Possible ways to select differential expressed genes using DeSeq2 or edgeR
... So, you mean to select candidates for wet lab experiments going with fold change > 1.5 and p.value < 0.05 not a bad idea? In my analysis I would also like to select candidates for experiments so I feel like following their way. ...
written 10 weeks ago by Beginner50
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Comment: C: Possible ways to select differential expressed genes using DeSeq2 or edgeR
... @Michael Love A small question.  I selected DEGs with res <- results(dds, lfcThreshold = log2(1.5), alpha = 0.1) summary(res) out of 11949 with nonzero total read count adjusted p-value < 0.1 LFC > 0.58 (up) : 15, 0.13% LFC < -0.58 (down) : 5, 0.042% outliers [1] : 81, 0.68% ...
written 10 weeks ago by Beginner50
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Comment: C: Possible ways to select differential expressed genes using DeSeq2 or edgeR
... Thanks a lot for the answers. But in one of the nature paper I see that they have selected differential genes based on foldchange > 5 and p.value < 0.05. Check Figure1a legend in this paper [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4927085/] ...
written 10 weeks ago by Beginner50
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Possible ways to select differential expressed genes using DeSeq2 or edgeR
... I'm working with RNA-seq data. I have 40 tumor samples and 5 Normal samples. Differential analysis with Deseq2 based on Fold change > 1.2 and alpha < 0.05 gave very low number of differentially expressed genes. Only 2 upregulated genes.      res <- results(dds, lfcThreshold = log2(1.2), al ...
edger deseq2 R differential gene expression fold change written 10 weeks ago by Beginner50 • updated 10 weeks ago by Axel Klenk920

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