User: miyakokodama

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Posts by miyakokodama

<prev • 9 results • page 1 of 1 • next >
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snp.plotter - GWAS results and linkage disequilibrium matrix as input
... Hi, I'd like to run snp.plotter - I have two input files to do so: 1) GWAS results and 2) linkage disequilibrium matrix. ##### 1) GWAS results chromosome position p_value NC_030381.1 595 6.31E-01 NC_030381.1 617 2.07E-01 NC_030381.1 625 ...
snp.plotter written 2.1 years ago by miyakokodama0
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Comment: C: KEGG pathway analysis on a predefined set of genes (with my own annotation)?
... Hi Gordon, Thanks so much for your reply. I think my wording was unclear - I work on a non-model plant species, and I have an input, which is something like this: GeneID KEGG_ID 108225144 K00121 ...
written 2.9 years ago by miyakokodama0
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KEGG pathway analysis on a predefined set of genes (with my own annotation)?
... I have a predefined set of interesting genes, along with their corresponding GO IDs and KEGG terms. According to the tutorial, I used TopGO and obtained significantly enriched GO terms using the Fisher's exact tests.  I am hoping to do something similar to perform KEGG pathway analysis, however I h ...
limma kegga written 2.9 years ago by miyakokodama0 • updated 2.9 years ago by Gordon Smyth38k
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Comment: C: Multifactor design using DESeq2 - unpaired samples
... Thanks so much for your help, Michael! ...
written 3.0 years ago by miyakokodama0
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Multifactor design using DESeq2 - unpaired samples
... Hi, I am using DESeq2 to identify DE genes across two color types. I have two columns – color and sample ID. As you can see, my samples are unpaired: Color Sample_ID S 1 S 2 B 3 B 4 B 5 B 6 According to the ...
deseq2 written 3.0 years ago by miyakokodama0 • updated 3.0 years ago by Michael Love25k
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Comment: C: EdgeR glmLRT vs glmQL - hundreds of DE genes with glmLRT, almost none with glmQL
... Sorry - I was rather unfamiliar with the logistics here, I will keep that in mind for my future posts :) I have added the sample effect along with the tissue type - I'll move on with QL instead of LRT then, especially given the low prior d.f. Just as a side note, QL gave out 29 genes at FDR<0.1 ...
written 3.1 years ago by miyakokodama0
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Answer: A: EdgeR glmLRT vs glmQL - hundreds of DE genes with glmLRT, almost none with glmQL
... Hi, Thanks so much for explaining it all in detail, Aaron - it's so helpful!  You're right, my prior degrees of freedom is less than 5 (they're around 4). I did make a MDS plot with plotMDS(), however did not see any batch effect (I have attached the image below); in short, biological sample 1 and ...
written 3.1 years ago by miyakokodama0
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Comment: C: EdgeR glmLRT vs glmQL - hundreds of DE genes with glmLRT, almost none with glmQL
... I just corrected it - thank you for pointing that out :) ...
written 3.1 years ago by miyakokodama0
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EdgeR glmLRT vs glmQL - hundreds of DE genes with glmLRT, almost none with glmQL
... Hi, I am trying to find DE genes using two groups (4 biological samples with two different types of tissues) using RNAseq. I obtained a raw gene count table from FeatureCount. I am using both  glmLRT and glmQF. glmLRT identified ~600 DE genes, while glmQF identified only 3. What was also surprisin ...
edger written 3.1 years ago by miyakokodama0

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