Ran code from dev/04_update.R

DESCRIPTION

@@ -46,5 +46,5 @@ Encoding: UTF-8
 LazyData: true
 URL: https://github.com/LieberInstitute/jaffelab
 BugReports: https://github.com/LieberInstitute/jaffelab/issues
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Roxygen: list(markdown = TRUE)

R/agePlotter.R

@@ -83,12 +83,11 @@
 #'
 #'
 #' par(def.par) #- reset to default
-agePlotter <- function(
-        y, age, mod = matrix(rep(1, length(y)), ncol = 1),
-        mainText, smoothIt = TRUE, jitter = TRUE, ageLabel = "bottom",
-        orderByAge = TRUE, ylim = NULL, ageBreaks = c(-1, 0, 1, 10, 100),
-        ylab = "Adjusted Expression", pointColor = 2, lineColor = 1,
-        alreadyFitted = NULL, ...) {
+agePlotter <- function(y, age, mod = matrix(rep(1, length(y)), ncol = 1),
+    mainText, smoothIt = TRUE, jitter = TRUE, ageLabel = "bottom",
+    orderByAge = TRUE, ylim = NULL, ageBreaks = c(-1, 0, 1, 10, 100),
+    ylab = "Adjusted Expression", pointColor = 2, lineColor = 1,
+    alreadyFitted = NULL, ...) {
     stopifnot(length(ageBreaks) >= 4)
     stopifnot(ageLabel %in% c("bottom", "top"))
     stopifnot(length(lineColor) == length(unique(pointColor)))

R/expression_cutoff.R

@@ -64,9 +64,8 @@
 #'
 #' ## View the pdf with the following code
 #' utils::browseURL("test_expression_cutoff.pdf")
-expression_cutoff <- function(
-        expr, max_cut = 1, seed = NULL, n.boot = 2000,
-        k = 2) {
+expression_cutoff <- function(expr, max_cut = 1, seed = NULL, n.boot = 2000,
+    k = 2) {
     meanExpr <- rowMeans(expr)
 
 

R/junctionCount.R

@@ -36,11 +36,10 @@
 #' ## TODO (need some data)
 #' ## See https://github.com/LieberInstitute/RNAseq-pipeline/blob/ab71dedb36bcc3dad57233e645fabd5deb96d446/sh/create_count_objects-human.R#L633-L643
 #' ## for an example of how it's being using the the RNA-seq pipeline code
-junctionCount <- function(
-        junctionFiles, sampleNames = names(junctionFiles),
-        output = c("Count", "Rail"), minOverhang = 0,
-        strandSpecific = FALSE, illuminaStranded = FALSE,
-        minCount = 1, maxCores = 1, skipLines = ifelse(output == "Count", 0, 1)) {
+junctionCount <- function(junctionFiles, sampleNames = names(junctionFiles),
+    output = c("Count", "Rail"), minOverhang = 0,
+    strandSpecific = FALSE, illuminaStranded = FALSE,
+    minCount = 1, maxCores = 1, skipLines = ifelse(output == "Count", 0, 1)) {
     stopifnot(length(junctionFiles) == length(sampleNames))
     stopifnot(output %in% c("Count", "Rail"))
 

R/lab_presenters.R

@@ -43,9 +43,8 @@
 #'     ## If it's a new sheet, we recommend sharing an editable link so other
 #'     ## lab members can swap out as necessary.
 #' }
-lab_presenters <- function(
-        presenters, start_date = "2019-09-18",
-        sheet_name = "Jaffelab research presenters", n = 2, repeat_day = 7) {
+lab_presenters <- function(presenters, start_date = "2019-09-18",
+    sheet_name = "Jaffelab research presenters", n = 2, repeat_day = 7) {
     ## Check inputs
     if (!is.character(presenters)) {
         stop("'presenters' should be a character vector.", call. = FALSE)

R/merge_rse_metrics.R

@@ -96,7 +96,6 @@
 #'     summary(mean_ERCCsumLogErr - ERCCsumLogErr)
 #' )
 #'
-
 merge_rse_metrics <- function(rse) {
     stopifnot(is(rse, "RangedSummarizedExperiment"))
     stopifnot(
@@ -138,7 +137,7 @@ merge_rse_metrics <- function(rse) {
     rse$mitoMapped <- sapply(rse$mitoMapped, sum)
     rse$totalMapped <- sapply(rse$totalMapped, sum)
 
-    if("ERCCsumLogErr" %in% colnames(colData(rse))) {
+    if ("ERCCsumLogErr" %in% colnames(colData(rse))) {
         message(Sys.time(), " attempting to approximate ERCCsumLogErr.")
         stopifnot(is(rse$ERCCsumLogErr, "NumericList"))
 
@@ -161,9 +160,9 @@ merge_rse_metrics <- function(rse) {
 
         ## Then compute the approximate result starting from a NumericList input
         rse$ERCCsumLogErr <- sapply(rse$ERCCsumLogErr, function(sumlogerr) {
-            log2(mean((2 ^ (
+            log2(mean((2^(
                 sumlogerr + ercc_expected_conc
-            )) ^ (1 / n_erccs)) ^ n_erccs) - ercc_expected_conc
+            ))^(1 / n_erccs))^n_erccs) - ercc_expected_conc
         })
     }