Training on different biological contexts #45
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gwaybio
approved these changes
Nov 29, 2018
26-describe_recount2.Rmd
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| tissue.accessions <- ConvertToRecountSampleName(tissue.samples, | ||
| conversion.df) | ||
| tissue.file <- file.path("data", "sample_info", | ||
| "recount2_tissue_accessions.tsv") |
26-describe_recount2.Rmd
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| ConvertToRecountSampleName(cancer.samples, | ||
| conversion.df) | ||
| cancer.file <- file.path("data", "sample_info", | ||
| "recount2_cancer_accessions.tsv") |
26-describe_recount2.Rmd
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| blood.samples <- names(blood.samples[which(unlist(blood.samples))]) | ||
| blood.accessions <- ConvertToRecountSampleName(blood.samples, conversion.df) | ||
| blood.file <- file.path("data", "sample_info", | ||
| "recount2_blood_accessions.tsv") |
| help = "Number of repeats to perform"), | ||
| make_option(c("-s", "--seed"), type = "integer", default = 123, | ||
| help = "Number of repeats to perform"), | ||
| make_option(c("-u", "--use_sample_list"), type = "logical", default = FALSE, |
There was a problem hiding this comment.
for a logical option, can use argument action='store_true'.
This way, when its called here all that is needed is --use_sample_list instead of --use_sample_list TRUE
scripts/subsampling_PLIER.R
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| smpl.exprs <- prepped.data[[1]][, sample.index] | ||
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| plier.results <- PLIERWrapper(exprs = smpl.exprs, | ||
| pathway.mat = prepped.data[[2]], |
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Can confirm that changes introduced with dd93688 gave me the same md5 checksum for one of the models. |
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Related to: #39
We want to train models on different biological contexts and see what pathways are recovered. Here, I modify
26-describe_recount2such that we can identify samples that are predicted to be from specific contexts in MetaSRA and convert from the identifiers used by MetaSRA (e.g.,SRSxxxxx) to the sample/column names used in recount2 (e.g.,SRPxxxxx.SRRxxxxx).Contexts are:
I've added
scripts/subsampling_PLIER.Rwhich allows us to do the subsampling experiments two ways:nnumber of samples; this is repeatedrtimes (default is 5) using different random seeds (related PR forthcoming)Finally, I'm adding
28-train_different_biological_contexts.sh-- the shell script for training all the models.