mirror of
https://github.com/johrpan/ubigen.git
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46 lines
1.1 KiB
R
46 lines
1.1 KiB
R
# This script uses the results (See results.csv) and computes a score for each
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# gene. This is the data that will be used in the package.
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library(data.table)
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library(here)
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i_am("scripts/input.R")
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genes <- fread(here("scripts", "input", "genes.csv"))
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data <- fread(here("scripts", "output", "results.csv"))
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data[, score := 0.5 * above_95 +
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0.25 * median_expression_normalized +
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-0.25 * qcv_expression_normalized]
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# Normalize scores to be between 0.0 and 1.0.
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data[, score := (score - min(score, na.rm = TRUE)) /
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(max(score, na.rm = TRUE) - min(score, na.rm = TRUE))]
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# These are genes that are not expressed at all or expressed just once, in case
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# the standard deviation is used in the score.
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data[is.na(score), score := 0.0]
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setorder(data, -score)
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# Reintroduce gene IDs and HGNC symbols.
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setnames(data, "gene", "id")
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data <- merge(
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data,
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genes,
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by = "id",
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all.x = TRUE,
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sort = FALSE
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)
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setnames(data, "hgnc_symbol", "hgnc_name")
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data[, id := NULL]
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# Remove duplicates. This will keep the best row for each duplicated gene.
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data <- unique(data, by = "gene")
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data[, rank := .I]
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fwrite(data, file = here("scripts", "output", "genes.csv"))
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