diff --git a/reports/report.Rmd b/reports/report.Rmd
index 308a955..e36b666 100644
--- a/reports/report.Rmd
+++ b/reports/report.Rmd
@@ -19,7 +19,7 @@ params:
 ```{r setup, include=FALSE}
 
 
-MIN_COVERAGE_PERCENTAGE = 90;
+MIN_COVERAGE_PERCENTAGE = 0.90;
 MIN_MEAN_BASE_QUALITY = 15;
 MIN_MEAN_DEPTH = 50
 
@@ -36,9 +36,27 @@ knitr::opts_chunk$set(echo = FALSE)
 
 ```{r echo=FALSE, warning=FALSE, error=FALSE, include=FALSE}
 
+PRIMARY <- "#2780e3"
+PRIMARY_DARK <- "#1a68be"
+RED <- "#dc3545"
+GREEN <- "#28a745"
+ORANGE <- "#ff8800"
+
 link_to_sample <- function(sample) {
-  return (sample)
-  #paste0('<a target=_blank href=samples/', sample, '.html>', sample,'</a>' )
+  paste0('<a target=_blank href="samples/', sample, '.html">', sample,'</a>' )
+}
+
+
+formatStyleTresholdValue <- function(datatable, column, threshold) {
+  formatStyle(
+    datatable,
+    column,
+    color = styleInterval(threshold, c(RED, ""))
+  )
+}
+
+formatStyleSample <- function(datatable) {
+    formatStyle(datatable, 'Sample_Link', fontWeight = 'bold')
 }
 
 variants <- read.delim(params$variants)
@@ -67,6 +85,8 @@ mapping <- mapping %>%
 statistics <- spread(statistics, key = Parameter, value = Value)
 statistics$MeanCoverage <- as.numeric(statistics$MeanDepth)
 statistics$MeanBaseQuality <- as.numeric(statistics$MeanBaseQuality)
+statistics$CoveredBases <- as.numeric(statistics$CoveredBases)
+statistics$MeanMapQuality <- as.numeric(statistics$MeanMapQuality)
 statistics <- merge(statistics, mapping, by.x="Sample", by.y="Filename")
 
 
@@ -79,14 +99,21 @@ contamination <- merge(contamination, mapping, by.x="Sample", by.y="Filename") %
 contaminated_samples = contamination %>%
   rename("Contamination_Status" = "Contamination.Status") %>%
   filter(Contamination_Status == "YES");
+#variants_count <- data.table(t(table(variants$ID)))
+#variants_count <- merge(variants_count, mapping, by.x="V2", by.y="Filename") %>%
+#  arrange(Sample_Label)
 
-variants_count <- data.table(t(table(variants$ID)))
-variants_count <- merge(variants_count, mapping, by.x="V2", by.y="Filename") %>%
+variants <- merge(variants, mapping, by.x="ID", by.y="Filename") %>%
   arrange(Sample_Label)
 
-variants <- merge(variants, mapping, by.x="ID", by.y="Filename") %>%
+variants_count <- variants %>% group_by(Sample_Label) %>% 
+  summarise(
+    N = n(),
+    Filtered = sum(Filter != "PASS")
+  ) %>%
   arrange(Sample_Label)
 
+
 variant_caller <- pipeline_params %>%
   filter(Parameter == "Variant Caller")
 
@@ -133,17 +160,17 @@ Row
 
 ```{r}
 
-colors <- c("#28a745", "#dc3545")
+colors <- c(GREEN, RED)
 names(colors) <- c("PASSED", "FAILED")
 
-colors_contamination <- c("#dddddd","#28a745", "#dc3545")
+colors_contamination <- c("", GREEN, RED)
 names(colors_contamination) <- c("-", "NO", "YES")
 
 statistics %>%
   mutate (
     Sample_Link = link_to_sample(Sample_Label),
     contamination = case_when(
-      qc == "FAILED" ~ "-",
+      qc == "FAILED" ~ "",
       Sample_Label %in% contaminated_samples$Sample_Label ~ "YES",
       TRUE ~ "NO"
     )
@@ -155,8 +182,13 @@ statistics %>%
       bPaginate = FALSE
     ),
     escape = FALSE,
+    rowname = FALSE,
     class = 'cell-border stripe'
-  ) %>% 
+  ) %>%
+  formatStyleSample() %>%
+  formatStyleTresholdValue('MeanDepth', MIN_MEAN_DEPTH) %>%
+  formatStyleTresholdValue('CoveragePercentage', MIN_COVERAGE_PERCENTAGE) %>%
+  formatStyleTresholdValue('MeanBaseQuality', MIN_MEAN_BASE_QUALITY) %>%
   formatStyle(
     'qc',
     backgroundColor = styleEqual(c("PASSED", "FAILED"), colors),
@@ -183,41 +215,62 @@ Row
 -----------------------------------------------------------------------
     
 
-### Mean Coverage per sample
+### Mean Coverage
 
 ```{r}
 
 ggplotly(
   ggplot(statistics) +
-    geom_col(aes(x=Sample_Label, y=MeanCoverage, fill=qc)) +
-    theme(axis.text.x=element_text(angle=+90)) + 
-    geom_hline(yintercept=MIN_MEAN_DEPTH, color="black", linetype="dashed") +
-    scale_fill_manual(values=colors) +
-    xlab("Samples") +
-    ylab("Mean Coverage") +
-    labs(fill = "")
+    geom_histogram(aes(x=MeanCoverage), fill=PRIMARY) +
+    geom_vline(xintercept=MIN_MEAN_DEPTH, color=RED, linetype="dashed") +
+    ylab("Samples") +
+    xlab("Mean Coverage") +
+    theme_bw()
+)
+```
+
+### Covered Bases
+
+```{r}
+
+ggplotly(
+  ggplot(statistics) +
+    geom_histogram(aes(x=CoveredBases), fill=PRIMARY) +
+    geom_vline(xintercept=MIN_COVERAGE_PERCENTAGE*16569, color=RED, linetype="dashed") +
+    ylab("Samples") +
+    xlab("Covered Bases (%)") +
+    theme_bw()
 )
 ```
 
 Row
 -----------------------------------------------------------------------
 
-### Mean Base Quality per sample
+### Mean Base Quality
 
 ```{r}
 ggplotly(
   ggplot(statistics) +
-    geom_col(aes(x=Sample_Label, y=MeanBaseQuality, fill=qc)) +
-    theme(axis.text.x=element_text(angle=+90)) + 
-    geom_hline(yintercept=MIN_MEAN_BASE_QUALITY, color="black", linetype="dashed") +
-    scale_fill_manual(values=colors) +
-    xlab("Samples") +
-    ylab("Mean Base Quality") +
-    labs(fill = "")
+    geom_histogram(aes(x=MeanBaseQuality), fill=PRIMARY) +
+    geom_vline(xintercept=MIN_MEAN_BASE_QUALITY, color=RED, linetype="dashed") +
+    ylab("Samples") +
+    xlab("Mean Base Quality") +
+    theme_bw()
 )
 ```
 
 
+### Mean Map Quality
+
+```{r}
+ggplotly(
+  ggplot(statistics) +
+    geom_histogram(aes(x=MeanMapQuality), fill=PRIMARY) +
+    ylab("Samples") +
+    xlab("Mean Mapping Quality") +
+    theme_bw()
+)
+```
 
 # Contamination
 
@@ -231,8 +284,10 @@ contaminated_samples %>%
       bPaginate = FALSE
     ),
     escape = FALSE,
+    rowname = FALSE,
     class = 'cell-border stripe'
-  )
+  ) %>%
+  formatStyleSample()
 ```
 
 ---
@@ -247,50 +302,17 @@ Row
 ```{r}
 variants_count %>%
   mutate (Sample_Link = link_to_sample(Sample_Label)) %>%
-  select("Sample_Link", "N") %>%
+  select("Sample_Link", "N", "Filtered") %>%
   datatable(
-    colnames=c("Sample", "Number of Variants"),
+    colnames=c("Sample", "Number of Variants", "Flagged Variants"),
     options = list(
       bPaginate = FALSE
     ),
     escape = FALSE,
+    rowname = FALSE,
     class = 'cell-border stripe'
-  )
-```
-
-Row
--------------------------------------
-
-### Common Variants and Hetereoplasmies
-
-
-```{r}
-variants <- variants %>%
-  mutate(Type = case_when(
-    Type == "0/1" ~ "2",
-    Type == "1/0" ~ "2",
-    Type == "INDEL" ~ "3",
-    TRUE ~ as.character(Type)
-  ))
-
-summary_data <- aggregate(  Sample_Label ~ Pos + Type , data = variants, FUN = length)
-summary_data <- summary_data %>% filter(Sample_Label >= 1)
-summary_data <- summary_data %>% mutate(
-  label = case_when(
-    Type == 1 ~ "Variant",
-    Type == 2 ~ "Heteroplasmy",
-    Type == 3 ~ "INDEL",
-    TRUE ~ "Unknown"
-  )
-)
-summary_data$AF<-summary_data$Sample_Label / max(length(unique(variants$Sample_Label)))
-ggplotly(
-  ggplot(summary_data, aes(x = Pos, y = AF, color=label)) +
-    geom_point() +
-    xlab("Position") +
-    ylab("Allele Frequency") +
-    labs(color = "Type")
-)
+  ) %>%
+  formatStyleSample()
 ```
 
 ---
@@ -314,7 +336,14 @@ haplogroups %>%
       bPaginate = FALSE
     ),
     escape = FALSE,
+    rowname = FALSE,
     class = 'cell-border stripe'
+  ) %>%
+  formatStyleSample() %>%
+  formatStyle(
+    "Quality",
+    backgroundColor = styleInterval(c(0.8,0.9), c(RED, ORANGE, GREEN)),
+    color ="white"
   )
 ```
 
@@ -326,12 +355,12 @@ Row
 ```{r}
 ggplotly(
   ggplot(haplogroups) +
-    geom_col(aes(y=Quality, x=Sample_Label), alpha=0.7) +
-    geom_hline(yintercept=0.90, color="green", linetype="dashed") +
-    geom_hline(yintercept=0.80, color="orange", linetype="dashed") +
-    geom_hline(yintercept=0.70, color="red", linetype="dashed") +
-    xlab("Samples") +
-    ylab("Haplogroup Quality") +
-    theme(axis.text.x=element_text(angle=+90))
+    geom_histogram(aes(x=Quality), fill=PRIMARY) +
+    geom_vline(xintercept=0.90, color=GREEN, linetype="dashed") +
+    geom_vline(xintercept=0.80, color="orange", linetype="dashed") +
+    geom_vline(xintercept=0.70, color=RED, linetype="dashed") +
+    ylab("Samples") +
+    xlab("Haplogroup Quality") +
+    theme_bw()
 )
 ```
diff --git a/reports/sample.Rmd b/reports/sample.Rmd
index 2b1cfcf..5cf1d1f 100644
--- a/reports/sample.Rmd
+++ b/reports/sample.Rmd
@@ -133,6 +133,10 @@ variants <- variants %>%
     Type == 2 ~ create_label('Heteroplasmy', 'default'),
     Type == 3 ~ create_label('InDel', 'info'),
     TRUE ~ "Unknown"
+  )) %>%
+  mutate(Filter_Label = case_when(
+    Filter == "PASS" ~ create_label('PASS', 'success'),
+    TRUE ~ create_label(Filter, 'warning')
   ))
 
 variant_caller <- pipeline_params %>%
@@ -182,19 +186,40 @@ statistics %>%
 #)
 ```
 
+### Variant Flags
+
+```{r}
+variants %>% count(Filter_Label) %>%
+  datatable(
+    colnames=c("Filter Flag", "Variants"),
+    options = list(
+      bPaginate = FALSE,
+      bFilter = FALSE,
+      bSort = FALSE,
+      bFooter = FALSE,
+      info = FALSE
+    ),
+    escape = FALSE,
+    rownames = FALSE,
+    class = 'cell-border stripe'
+  )
+  
+```
+
 ### Variants and Hetroplasmies
 
 Detected **`r variants %>% filter(Type == 1) %>% nrow()` variants**, **`r variants %>% filter(Type == 2) %>% nrow()` heteroplasmies** and **`r  variants %>% filter(Type == 3) %>% nrow()` InDels**.
 
+
 ```{r}
 variants %>% 
   mutate(
     Variant_Label = link_to_variant(Pos, Ref, Variant)
   ) %>% 
   arrange(Pos, Ref, Variant) %>%
-  select("Variant_Label", "VariantLevel", "Type_Label") %>%
+  select("Variant_Label", "VariantLevel", "Type_Label","Filter_Label") %>%
   datatable(
-    colnames=c("Variant", "Level", ""),
+    colnames=c("Variant", "Level", "Type","Flags"),
     options = list(
       bPaginate = FALSE,
       bFilter = FALSE,