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Move analysis into the package

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Elias Projahn 2022-11-30 14:32:40 +01:00
parent d25bb424b1
commit 698ea5086a
5 changed files with 105 additions and 69 deletions
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69
scripts/analyze.R
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@ -8,72 +8,5 @@ library(here)
i_am("scripts/input.R")
data <- fread(here("scripts", "input", "data_long.csv"))
data[, `:=`(
expression_median = median(expression),
expression_95 = quantile(expression, probs = 0.95)
), by = sample]
# Transform the expression logarithmically. The samples that don't express a
# gene at all will be left out intentionally.
data[expression > 0, expression_log := log2(expression)]
results <- data[, .(
median_expression = median(expression[expression > 0]),
iqr_expression = IQR(expression[expression > 0]),
mean_expression = mean(expression[expression > 0]),
sd_expression = sd(expression[expression > 0]),
median_expression_normalized = median(expression_log, na.rm = TRUE),
iqr_expression_normalized = IQR(expression_log, na.rm = TRUE),
mean_expression_normalized = mean(expression_log, na.rm = TRUE),
sd_expression_normalized = sd(expression_log, na.rm = TRUE),
above_zero = mean(expression > 0.0),
above_threshold = mean(expression > 50.0),
above_median = mean(expression > expression_median),
above_95 = mean(expression > expression_95)
), by = "gene"]
results[, `:=`(
qcv_expression = iqr_expression / median_expression,
qcv_expression_normalized =
iqr_expression_normalized / median_expression_normalized,
cv_expression = sd_expression / mean_expression,
cv_expression_normalized =
sd_expression_normalized / mean_expression_normalized
)]
# Normalize values to the range of 0.0 to 1.0.
results[, `:=`(
median_expression_normalized =
(median_expression_normalized -
min(median_expression_normalized, na.rm = TRUE)) /
(max(median_expression_normalized, na.rm = TRUE) -
min(median_expression_normalized, na.rm = TRUE)),
iqr_expression_normalized =
(iqr_expression_normalized -
min(iqr_expression_normalized, na.rm = TRUE)) /
(max(iqr_expression_normalized, na.rm = TRUE) -
min(iqr_expression_normalized, na.rm = TRUE)),
qcv_expression_normalized =
(qcv_expression_normalized -
min(qcv_expression_normalized, na.rm = TRUE)) /
(max(qcv_expression_normalized, na.rm = TRUE) -
min(qcv_expression_normalized, na.rm = TRUE)),
mean_expression_normalized =
(mean_expression_normalized -
min(mean_expression_normalized, na.rm = TRUE)) /
(max(mean_expression_normalized, na.rm = TRUE) -
min(mean_expression_normalized, na.rm = TRUE)),
sd_expression_normalized =
(sd_expression_normalized -
min(sd_expression_normalized, na.rm = TRUE)) /
(max(sd_expression_normalized, na.rm = TRUE) -
min(sd_expression_normalized, na.rm = TRUE)),
cv_expression_normalized =
(cv_expression_normalized -
min(cv_expression_normalized, na.rm = TRUE)) /
(max(cv_expression_normalized, na.rm = TRUE) -
min(cv_expression_normalized, na.rm = TRUE))
)]
results <- ubigen::analyze(data)
fwrite(results, file = here("scripts", "output", "results.csv"))