User: keith.hughitt
keith.hughitt • 280
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Posts by keith.hughitt
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... Greetings!
I was wondering what people's thoughts are on performing a preranked GSEA type analysis on unsigned / one-sided gene statistics are?
[Most of the](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0079217) [literature](https://bmcbioinformatics.biomedcentral.com/articles ...
written 10 months ago by
keith.hughitt • 280
• updated
10 months ago by
Biostar ♦♦ 20
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... Greetings,
I would like to share a small tool I developed during my graduate work over the past couple years. The software is called "[labnote][1]" and is a simple python-based tool for scanning a Unix-based directory structure and generating a HTML table of contents page for various research outpu ...
written 3.3 years ago by
keith.hughitt • 280
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... I suspect you are seeing a batch effect. It is not uncommon for differences in batches to explain more of the variance in your data than the biological effects of interest. The fact that there are also differences in the total expression levels differentiating the two groups also supports that idea. ...
written 4.1 years ago by
keith.hughitt • 280
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... From [The NCBI Handbook, ch18][1]: (via [this answer][2])
**NC** - "Complete genomic molecule, usually reference assembly"
**NZ** - "Unfinished WGS"
[1]: http://www.ncbi.nlm.nih.gov/books/NBK21091/table/ch18.T.refseq_accession_numbers_and_mole/
[2]: https://www.biostars.org/p/105529/ ...
written 4.1 years ago by
keith.hughitt • 280
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Comment:
C: Error in SAMseq analysis with R
... Since the error appears to result from some non-numeric or non-finite values, first thing you might want to try is to check for those in your input counts, e.g.: `sapply(RNA_seq_DNAm, function(x) { sum(is.na(x)) })` for NAs. You can modify this to check for NaN's (`is.nan`) or Infs (`abs(x) == Inf`) ...
written 4.1 years ago by
keith.hughitt • 280
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... The [Distance][1] library for Python also has an implementation of hamming distance and some other metrics which I've found useful in the past.
[1]: https://pypi.python.org/pypi/Distance/ ...
written 4.1 years ago by
keith.hughitt • 280
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... You might want to start by checking out the Bioconductor microarray analysis guide: https://www.bioconductor.org/help/workflows/arrays/ ...
written 4.1 years ago by
keith.hughitt • 280
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... What is the structure of your data, e.g. #samples, #conditions, #replicates/condition? And are you attempting to find clusters of samples? Or genes? Depending on what you are interested in, using z-scores may not be necessary. ...
written 4.1 years ago by
keith.hughitt • 280
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... Then WouterDeCoster is correct - experiment and cell type are confounded and you cannot reliably detect differences between them. This would only work if you had both cell types for both studies. ...
written 4.1 years ago by
keith.hughitt • 280
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... You can use the `table` function in R to get the count of each duplicated gene.
For example, if the gene IDs are stored in a column `gene_id`, you could do:
> dat <- data.frame(gene_id=sample(1:3, 20, replace=TRUE), other_col='foo')
> table(dat$gene_id)
1 2 3
5 6 9
...
written 4.1 years ago by
keith.hughitt • 280
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For labnote: A light-weight HTML lab notebook generator
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