diff --git a/R/ts_anom_detection.R b/R/ts_anom_detection.R
index 9571523..61c14ea 100644
--- a/R/ts_anom_detection.R
+++ b/R/ts_anom_detection.R
@@ -83,6 +83,9 @@ AnomalyDetectionTs <- function(x, max_anoms = 0.10, direction = 'pos',
     colnames(x) <- c("timestamp", "count")
   }
   
+  # extract original timezone attr
+  tz <- attr(x$timestamp, "tzone")
+  
   if (!is.logical(na.rm)) {
     stop("na.rm must be either TRUE (T) or FALSE (F)")
   }
@@ -165,6 +168,7 @@ AnomalyDetectionTs <- function(x, max_anoms = 0.10, direction = 'pos',
   if (gran == "sec") {
     x <- format_timestamp(aggregate(x[2], format(x[1], "%Y-%m-%d %H:%M:00"), 
                                     eval(parse(text = "sum"))))
+    gran <- "min"
   }
 
   period = switch(gran,
@@ -323,7 +327,7 @@ AnomalyDetectionTs <- function(x, max_anoms = 0.10, direction = 'pos',
       week_rng <- get_range(x_subset_week, index = 2, y_log = y_log)
       day_rng <- get_range(x_subset_single_day, index = 2, y_log = y_log)
       yrange <- c(min(week_rng[1], day_rng[1]), max(week_rng[2], day_rng[2]))
-      xgraph <- add_day_labels_datetime(xgraph, breaks = breaks, start = as.POSIXlt(min(x_subset_week[[1]]), tz = "UTC"), end = as.POSIXlt(max(x_subset_single_day[[1]]), tz = "UTC"), days_per_line = num_days_per_line)
+      xgraph <- add_day_labels_datetime(xgraph, breaks = breaks, start = as.POSIXlt(min(x_subset_week[[1]]), tz = tz), end = as.POSIXlt(max(x_subset_single_day[[1]]), tz = tz), days_per_line = num_days_per_line)
       xgraph <- xgraph + 
         ggplot2::labs(x = xlabel, y = ylabel, title = plot_title)
     } else {
@@ -337,7 +341,7 @@ AnomalyDetectionTs <- function(x, max_anoms = 0.10, direction = 'pos',
         ggplot2::geom_line(data = x, ggplot2::aes_string(colour = color_name), alpha = alpha)
       yrange <- get_range(x, index = 2, y_log = y_log)
       xgraph <- xgraph + 
-        ggplot2::scale_x_datetime(labels = function(x) ifelse(as.POSIXlt(x, tz = "UTC")$hour != 0, strftime(x, format = "%kh", tz = "UTC"), strftime(x, format = "%b %e", tz = "UTC")),
+        ggplot2::scale_x_datetime(labels = function(x) ifelse(as.POSIXlt(x, tz = tz)$hour != 0, strftime(x, format = "%kh", tz = tz), strftime(x, format = "%b %e", tz = tz)),
                                                   expand = c(0,0))
       xgraph <- xgraph + 
         ggplot2::labs(x = xlabel, y = ylabel, title = plot_title)
@@ -363,15 +367,14 @@ AnomalyDetectionTs <- function(x, max_anoms = 0.10, direction = 'pos',
   # Store expected values if set by user
   if (e_value) {
     anoms <- data.frame(timestamp = all_anoms[[1]], anoms = all_anoms[[2]], 
-                        expected_value = subset(seasonal_plus_trend[[2]], as.POSIXlt(seasonal_plus_trend[[1]], tz = "UTC") %in% all_anoms[[1]]),
+                        expected_value = subset(seasonal_plus_trend[[2]], as.POSIXlt(seasonal_plus_trend[[1]], tz = tz) %in% all_anoms[[1]]),
                         stringsAsFactors = FALSE)
   } else {
     anoms <- data.frame(timestamp = all_anoms[[1]], anoms = all_anoms[[2]], stringsAsFactors = FALSE)
   }
 
   # Make sure we're still a valid POSIXct datetime.
-  # TODO: Make sure we keep original datetime format and timezone.
-  anoms$timestamp <- as.POSIXct(anoms$timestamp, tz = "UTC")
+  anoms$timestamp <- as.POSIXct(anoms$timestamp, tz = tz)
 
   # Lastly, return anoms and optionally the plot if requested by the user
   if (plot) {
diff --git a/tests/testthat/test-edge.R b/tests/testthat/test-edge.R
index 475a04d..77cb730 100644
--- a/tests/testthat/test-edge.R
+++ b/tests/testthat/test-edge.R
@@ -4,16 +4,15 @@ context("Testing edge cases")
 
 test_that("checking for errors if time series has constant value for all values", {
     data <- rep(1,1000)
-    expect_true({AnomalyDetectionVec(data, period=14, plot=T, direction='both'); TRUE})
-
+    expect_true({AnomalyDetectionVec(data, period = 14, plot = T, direction = 'both'); TRUE})
 })
 
 test_that("checking that midnight dates get H%M%S format applied", {
-    data_file <- system.file("extdata", "data.csv", package="AnomalyDetection")
+    data_file <- system.file("extdata", "data.csv", package = "AnomalyDetection")
     data <- read.csv(data_file)
     data$date <- as.POSIXct(strptime(data$date, "%Y-%m-%d %H:%M", tz = "UTC"))
-    anomalyDetectionResult <- AnomalyDetectionTs(data, max_anoms=0.2, threshold = "None", 
-                                                 direction='both', plot=FALSE, 
+    anomalyDetectionResult <- AnomalyDetectionTs(data, max_anoms = 0.2, threshold = "None", 
+                                                 direction = 'both', plot = FALSE, 
                                                  only_last = "day", e_value = TRUE)
     
     expect_equal(length(anomalyDetectionResult$anoms$anoms), length(anomalyDetectionResult$anoms$expected_value))