greenelab / 2022-cf-sputum Goto Github PK

• eADAGE/ADAGEpath normalization in function load_dataset():
  • isRNAseq: a logical value indicating whether the processed input_data is RNAseq data. If TRUE, the processed RNAseq data will be normalized to a comparable range with the microarray-based compendium using TDM. If FALSE, the processed input_data is considered a microarray dataset and will be quantile normalized to be comparable to the compendium.
  • What is the appropriate input, and the appropriate behavior?
    • MRnormalized and isRNAseq = F?
    • Raw counts and isRNAseq = T?
    • ...? (e.g. write new internal function options?)

BiocManager changed the env

Downloading GitHub repo greenelab/ADAGEpath@HEAD
TDM          (NA     -> b04180783...) [GitHub]
impute       (1.64.0 -> 970b2c28d...) [Bioc]
preproces... (1.52.1 -> 2995e3e1a...) [Bioc]
affy         (1.68.0 -> 2266c4a46...) [Bioc]
affyio       (1.60.0 -> 3a0b90704...) [Bioc]
limma        (3.46.0 -> b0b1b7c93...) [Bioc]
later        (1.2.0  -> 1.3.0       ) [CRAN]
terra        (1.5-21 -> 1.6-7       ) [CRAN]
gert         (1.5.0  -> 1.8.0       ) [CRAN]
BiocGenerics (0.36.0 -> 0.36.1      ) [CRAN]
raster       (3.5-21 -> 3.5-29      ) [CRAN]

Full env attached
env.txt

https://saket-choudhary.me/pysradb/commands/srx-to-srr.html

It's essentially the same as sophie.snakefile, but needs to be run after sophie.pub because it relies on some of the file outputs made by that workflow. It was easier to just put these public samples as a separate snakefile even with the weird dependency instead of refactoring everything.