User: mforde84

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mforde84810
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Posts by mforde84

<prev • 172 results • page 1 of 18 • next >
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Answer: A: Time point microarray data correcting for batch effects
... If you know the batches you can use ComBat from the sva R package or the removeBatchEffects() function in the limma R package. If you don't know the batches, I think sva has additional options for you. Also, I've seen people control for batch by including it as a coefficient in a linear model. For ...
written 21 hours ago by mforde84810
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Answer: A: Too many significant genes?
... It's extremely unlikely that 10k genes are being actively regulated in the first place, let alone differentially expressed. Something is wrong with your data, normalization, and or analysis pipeline. ...
written 23 hours ago by mforde84810
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Comment: C: DE gene analysis
... Yes. The package has plenty of documentation and working code samples. ...
written 23 hours ago by mforde84810
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Comment: C: Help: RNA-seq analysis
... bam files are compressed alignment files and bai files are indices on those files. you shouldn't really have to work directly with bai, though occasionally you will have to generate them explicitly for other programs to use (e.g., IGV). Bed files are interval files which group alignments and read pi ...
written 6 days ago by mforde84810
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spike-in based normalization of microarray
... Hello, I have CEL files from GeneChip miRNA v4.0. I would like to generate normalized data using a Loess curve subset with only spike-in probesets. Package affy has a function normalize.loess(mat, subset=...) which can accomplish the subseting portion, however after importing the CEL data using the ...
microarray written 6 days ago by mforde84810
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Comment: C: Meta analysis of microarray data merits and demerits
... meta analysis of microarray data is really hard, especially when you have different platforms. Here's some resources: https://omictools.com/meta-analysis-category ...
written 6 days ago by mforde84810
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Comment: C: genes that are declared DE in the meta-analysis
... There's a lot of reasons why this might be the case. Maybe you just have more inferential power with the additional samples. Maybe you didn't correct for batch effects. etc. ...
written 6 days ago by mforde84810
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Answer: A: Help: RNA-seq analysis
... https://www.bioconductor.org/help/workflows/rnaseqGene/ ...
written 7 days ago by mforde84810
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Comment: C: expression to networking
... There's like 40+ pages of documentation on WGCNA... You can do it! I have faith in you! ...
written 7 days ago by mforde84810
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Comment: C: edgeR RNA-seq Results Across Conditions
... It's already taken care of in the code. Specifically, the number of instances a gene / transcript feature has a sample count greater than 0 and the average CPM across all samples is atleast 1. Usually, if you used the same seq machine to run all of your samples, you will use the sequencing lane as f ...
written 7 days ago by mforde84810

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Scholar 6 days ago, created an answer that has been accepted. For A: SNP analysis based on RNAseq data using GATK PIPELINE
Scholar 5 weeks ago, created an answer that has been accepted. For A: SNP analysis based on RNAseq data using GATK PIPELINE
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Scholar 3 months ago, created an answer that has been accepted. For A: SNP analysis based on RNAseq data using GATK PIPELINE
Scholar 3 months ago, created an answer that has been accepted. For A: SNP analysis based on RNAseq data using GATK PIPELINE
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