diff --git a/NAMESPACE b/NAMESPACE
index 84f0b44..7a6fa5e 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -14,6 +14,14 @@ S3method(qp_mark_outliers,data.frame)
 S3method(qp_mark_outliers,list)
 S3method(qp_remove_empty,data.frame)
 S3method(qp_remove_empty,list)
+S3method(qp_samples_all,data.frame)
+S3method(qp_samples_all,list)
+S3method(qp_samples_summary,data.frame)
+S3method(qp_samples_summary,list)
+S3method(qp_standards_all,data.frame)
+S3method(qp_standards_all,list)
+S3method(qp_standards_summary,data.frame)
+S3method(qp_standards_summary,list)
 S3method(qp_summarize,data.frame)
 S3method(qp_summarize,list)
 S3method(qp_tidy,character)
@@ -31,6 +39,7 @@ export(qp_mark_outliers)
 export(qp_plot_plate)
 export(qp_plot_standards)
 export(qp_remove_empty)
+export(qp_report)
 export(qp_summarize)
 export(qp_tidy)
 importFrom(rlang,.data)
diff --git a/R/color.R b/R/color.R
new file mode 100644
index 0000000..d583901
--- /dev/null
+++ b/R/color.R
@@ -0,0 +1,18 @@
+qp_pal <- grDevices::colorRampPalette(
+  c("darkseagreen1", "#A763A0", "#3D1452"),
+  bias = 0.9
+)(100)
+
+# Notes:
+# Abs vs apparent color
+# 0.1 - gray - between green and purple
+# 0.31 - around mediumorchid3
+# Let's call 0.5 the max since you shouldn't go too far above anyway
+
+abs_to_col <- function(abs, pal) {
+  scaled <- abs * 200
+  idx <- ifelse(scaled < 1, 1, scaled)
+  idx <- ifelse(idx > 100, 100, idx)
+  idx <- round(idx)
+  pal[idx]
+}
diff --git a/R/qp_dilute.R b/R/qp_dilute.R
index 2874fe3..747a07b 100644
--- a/R/qp_dilute.R
+++ b/R/qp_dilute.R
@@ -1,8 +1,8 @@
 #' Calculate dilutions from predicted concentrations
 #'
 #' @param x A `data.frame` or `list` containing a `data.frame` named `qp` with
-#'   a column named `.pred_conc` or `.mean_pred_conc`. If both, will favor
-#'   `.mean_pred_conc`.
+#'   a column named `.pred_conc` or `.pred_conc_mean`. If both, will favor
+#'   `.pred_conc_mean`.
 #' @param target_conc Numeric vector. Target concentration in (mg/mL) protein.
 #'   If length == 1, recycled.
 #' @param target_vol Target volume in uL. If length == 1, recycled.
@@ -21,7 +21,7 @@ qp_dilute <- function(x, ...) {
 #' @export
 qp_dilute.data.frame <- function(x, target_conc = NULL, target_vol = 15,
                                  remove_standards = FALSE, ...) {
-  check_has_cols(x, c(".pred_conc", ".mean_pred_conc"), type = "or")
+  check_has_cols(x, c(".pred_conc", ".pred_conc_mean"), type = "or")
 
   if (remove_standards || is.null(target_conc)) {
     check_has_cols(x, "sample_type")
@@ -36,7 +36,7 @@ qp_dilute.data.frame <- function(x, target_conc = NULL, target_vol = 15,
   }
 
   conc_col_name <- ifelse(
-    has_cols(x, ".mean_pred_conc"), ".mean_pred_conc", ".pred_conc"
+    has_cols(x, ".pred_conc_mean"), ".pred_conc_mean", ".pred_conc"
   )
 
   if (is.null(target_conc)) {
@@ -54,7 +54,8 @@ qp_dilute.data.frame <- function(x, target_conc = NULL, target_vol = 15,
 
   x |>
     dplyr::bind_cols(dils) |>
-    tidyr::unnest_wider("value")
+    tidyr::unnest_wider("value") |>
+    dplyr::mutate(.target_conc = target_conc, .target_vol = target_vol)
 }
 
 #' @rdname qp_dilute
diff --git a/R/qp_plot_plate.R b/R/qp_plot_plate.R
index 7498f17..b897db0 100644
--- a/R/qp_plot_plate.R
+++ b/R/qp_plot_plate.R
@@ -13,13 +13,16 @@ qp_plot_plate <- function(x, size = 15) {
   ggplot2::ggplot(x, ggplot2::aes(
     x = .data$.col,
     y = .data$.row,
-    color = .data$.abs
+    color = abs_to_col(.data$.abs, qp_pal)
   )) +
     ggplot2::geom_point(size = size) +
     ggplot2::geom_text(
-      ggplot2::aes(label = round(.data$.abs, 2)),
-      color = "black"
+      ggplot2::aes(
+        label = round(.data$.abs, 2),
+        color = ifelse(.data$.abs < 0.35, "black", "white")
+      ),
+      size = size / 3
     ) +
     ggplot2::scale_y_reverse() +
-    ggplot2::scale_color_gradient(low = "darkseagreen1", high = "mediumpurple3")
+    ggplot2::scale_color_identity()
 }
diff --git a/R/qp_report.R b/R/qp_report.R
index 0db50a7..68d2807 100644
--- a/R/qp_report.R
+++ b/R/qp_report.R
@@ -1,3 +1,261 @@
-qp_report <- function(qp) {
-  ""
+#' Create a report for a protein quantificaiton experiment
+#'
+#' @param qp Likely the output from `qp` AND `qp_dilute`.
+#' @param output_file Character. The path of the file to export,
+#'   including `.html`
+#' @param other Generally used for Shiny application. Assumes a
+#'   named list of key-values that will be used to document report
+#'   parameters.
+#'
+#' @export
+#' @examples
+#' \dontrun{
+#' absorbances |>
+#'   qp() |>
+#'   qp_dilute() |>
+#'   qp_report(
+#'     "~/my_report.html",
+#'     other = list(key = "value") # Essentially metadata
+#'   )
+#' }
+qp_report <- function(qp, output_file, other = list()) {
+  rmarkdown::render(
+    system.file(
+      "rmarkdown/templates/quantify-protein-report/skeleton/skeleton.Rmd",
+      package = "qp"
+    ),
+    output_file = output_file,
+    params = list(qp = qp, other = other)
+  )
+}
+
+# Standards ----
+## All ----
+qp_standards_all <- function(x) {
+  UseMethod("qp_standards_all")
+}
+
+#' @export
+qp_standards_all.data.frame <- function(x) {
+  x <- add_coords_col(x)
+  table_data <- add_well_circles_plot_col(
+    x,
+    "standard",
+    c(".sample_name", ".abs", ".is_outlier", ".pred_conc", ".coord", ".conc"),
+    c(".sample_name", ".pred_conc", ".conc")
+  )
+  table_data |>
+    make_gt(35, 1, c(".abs", ".pred_conc", ".conc")) |>
+    gt::cols_label(
+      .sample_name = "Sample", .conc = "[Actual]",
+      .pred_conc = "[Predicted]", .abs = "Absorbance", gg = ""
+    )
+}
+
+#' @export
+qp_standards_all.list <- function(x) {
+  x$qp <- qp_standards_all.data.frame(x$qp)
+  x
+}
+
+## Summary ----
+qp_standards_summary <- function(x) {
+  UseMethod("qp_standards_summary")
+}
+
+#' @export
+qp_standards_summary.data.frame <- function(x) {
+  x <- add_coords_col(x)
+  table_data <- add_well_circles_plot_col(
+    x,
+    "standard",
+    c(".sample_name", ".pred_conc_mean", ".is_outlier", ".abs", ".coord"),
+    c(".sample_name", ".pred_conc_mean"),
+    summary = TRUE
+  )
+  table_data |>
+    make_gt(50, 2, ".pred_conc_mean") |>
+    gt::cols_label(
+      .sample_name = "Sample", .pred_conc_mean = "Concentration", gg = ""
+    )
+}
+
+#' @export
+qp_standards_summary.list <- function(x) {
+  x$qp <- qp_standards_summary.data.frame(x$qp)
+  x
+}
+
+
+# Samples -----
+## All ----
+qp_samples_all <- function(x) {
+  UseMethod("qp_samples_all")
+}
+
+#' @export
+qp_samples_all.data.frame <- function(x) {
+  x <- add_coords_col(x)
+  table_data <- add_well_circles_plot_col(
+    x,
+    "unknown",
+    c(".sample_name", ".abs", ".is_outlier", ".pred_conc", ".coord"),
+    group_vars = c(".sample_name", ".pred_conc")
+  )
+  table_data |>
+    make_gt(35, 1, c(".abs", ".pred_conc")) |>
+    gt::cols_label(
+      .sample_name = "Sample", .pred_conc = "[Predicted]",
+      .abs = "Absorbance", gg = ""
+    )
+}
+
+#' @export
+qp_samples_all.list <- function(x) {
+  x$qp <- qp_samples_all.data.frame(x$qp)
+  x
+}
+
+## Summary ----
+qp_samples_summary <- function(x) {
+  UseMethod("qp_samples_summary")
+}
+
+#' @export
+qp_samples_summary.data.frame <- function(x) {
+  x <- add_coords_col(x)
+  table_data <- add_well_circles_plot_col(
+    x,
+    "unknown",
+    c(".sample_name", ".pred_conc_mean", ".is_outlier", ".abs", ".coord"),
+    c(".sample_name", ".pred_conc_mean"),
+    summary = TRUE
+  )
+  table_data |>
+    make_gt(50, 2, ".pred_conc_mean") |>
+    gt::cols_label(
+      .sample_name = "Sample", .pred_conc_mean = "Concentration", gg = ""
+    )
+}
+
+#' @export
+qp_samples_summary.list <- function(x) {
+  x$qp <- qp_samples_summary.data.frame(x$qp)
+  x
+}
+
+make_well_circles_plot <- function(df) {
+  x <- seq_along(df$.abs)
+  y <- 1
+  if (nrow(df) == 1) {
+    size <- 120
+  } else {
+    size <- 200 / nrow(df)
+  }
+
+  well <- data.frame(x = x, y = y, color = abs_to_col(df$.abs, qp_pal))
+
+  text <- data.frame(
+    x = x, y = y, color = ifelse(df$.abs > 0.3, "white", "black"),
+    label = df$.coord
+  )
+
+  cross <- data.frame(
+    x = x, y = y, color = ifelse(df$.is_outlier, "red", "#FFFFFF00")
+  )
+
+  ggplot2::ggplot(
+    well, ggplot2::aes(.data$x, .data$y, color = .data$color)
+  ) +
+    ggplot2::geom_point(size = size, shape = 16) +
+    ggplot2::geom_text(
+      data = text, ggplot2::aes(label = .data$label), size = size / 2.5
+    ) +
+    ggplot2::geom_point(data = cross, shape = 4, size = size, stroke = 4) +
+    ggplot2::theme_void() +
+    ggplot2::coord_cartesian(clip = "off") +
+    ggplot2::scale_color_identity() +
+    ggplot2::theme(plot.margin = ggplot2::margin(0, 1.5, 0, 1.5, unit = "cm"))
+}
+
+add_well_circles_plot_col <- function(x,
+                                      sample_type,
+                                      select_vars,
+                                      group_vars,
+                                      summary = FALSE) {
+  x <- dplyr::filter(x, .data$sample_type == .env$sample_type)
+
+  x <- x |>
+    dplyr::select(dplyr::all_of(select_vars)) |>
+    dplyr::group_by(dplyr::across(dplyr::all_of(group_vars))) |>
+    tidyr::nest() |>
+    dplyr::mutate(gg = purrr::map(.data$data, make_well_circles_plot))
+
+  if (summary) {
+    x <- dplyr::select(x, -"data")
+  } else {
+    x <- x |>
+      tidyr::unnest(.data$data) |>
+      dplyr::select(-c(".is_outlier", ".coord"))
+  }
+
+  dplyr::ungroup(x)
+}
+
+add_coords_col <- function(x) {
+  x$.coord <- paste0(LETTERS[x$.row], x$.col)
+  x
+}
+
+make_gt <- function(x, well_img_height, well_img_aspect_ratio, cols_to_round) {
+  x |>
+    gt::gt() |>
+    gt::text_transform(
+      location = gt::cells_body(
+        columns = .data$gg
+      ),
+      fn = function(z) {
+        gt::ggplot_image(
+          x$gg,
+          height = gt::px(well_img_height),
+          aspect_ratio = well_img_aspect_ratio
+        )
+      }
+    ) |>
+    gt::fmt_number(
+      dplyr::all_of(cols_to_round),
+      n_sigfig = 2
+    )
+}
+
+dil_summary <- function(qp) {
+  check_has_cols(qp, c(
+    ".sample_name", ".pred_conc_mean", ".target_conc",
+    ".target_vol", "sample_type"
+  ))
+
+  qp |>
+    dplyr::summarize(
+      .by = c(
+        ".sample_name", ".pred_conc_mean", ".target_conc",
+        ".target_vol", "sample_type"
+      )
+    ) |>
+    qp_dilute() |>
+    dplyr::filter(.data$sample_type == "unknown") |>
+    dplyr::select(
+      Name = ".sample_name",
+      ".pred_conc_mean", ".target_conc",
+      `Final Vol` = ".target_vol",
+      `Sample to Add (uL)` = "sample_to_add",
+      `Diluent to Add (uL)` = "add_to"
+    ) |>
+    dplyr::mutate(
+      .target_conc = round(.data$.target_conc, 2),
+      .pred_conc_mean = round(.data$.pred_conc_mean, 2)
+    ) |>
+    dplyr::rename(
+      "[Target]" = .data$.target_conc,
+      "[Sample]" = .data$.pred_conc_mean
+    )
 }
diff --git a/R/qp_summarize.R b/R/qp_summarize.R
index aa66af9..d7dc62e 100644
--- a/R/qp_summarize.R
+++ b/R/qp_summarize.R
@@ -21,7 +21,7 @@ qp_summarize.data.frame <- function(x) {
   }
   x |>
     dplyr::summarize(
-      .mean_pred_conc = mean(.data$.pred_conc_mean, na.rm = TRUE),
+      .pred_conc_mean = mean(.data$.pred_conc_mean, na.rm = TRUE),
       .by = c(".sample_name", "sample_type")
     ) |>
     dplyr::arrange(.data$sample_type)
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 099eebf..d4aec09 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -30,6 +30,7 @@ reference:
     - qp_summarize
     - qp_plot_plate
     - qp_plot_standards
+    - qp_report
   - title: "Data"
     contents:
     - absorbances
diff --git a/inst/rmarkdown/templates/quantify-protein-report/skeleton/skeleton.Rmd b/inst/rmarkdown/templates/quantify-protein-report/skeleton/skeleton.Rmd
new file mode 100644
index 0000000..97bd2da
--- /dev/null
+++ b/inst/rmarkdown/templates/quantify-protein-report/skeleton/skeleton.Rmd
@@ -0,0 +1,152 @@
+---
+title: "Protein Quantification Report"
+output:
+  html_document:
+    css: "style.css"
+params:
+  qp : NA
+  other : list()
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = FALSE)
+library(qp)
+library(ggplot2)
+library(dplyr)
+library(gt)
+library(knitr)
+```
+
+
+# Plots
+```{r}
+plate_plot <- qp_plot_plate(params$qp$qp) +
+  theme_void() +
+  coord_cartesian(clip = "off") +
+  theme(
+    plot.margin = margin(1, 0.5, 1, 0.5, unit = "cm"),
+    panel.background = element_rect(fill = "transparent", color = NA),
+    plot.background = element_rect(fill = "#FFFFFF33", color = NA)
+  )
+
+ggsave(
+  "plate_plot.png",
+  plate_plot,
+  device = "png",
+  width = 17, height = max(params$qp$qp$.col), units = "cm",
+  bg = "transparent"
+)
+```
+
+```{r}
+standards_plot <- qp_plot_standards(params$qp) +
+  theme_minimal() +
+  theme(
+    panel.background = element_rect(fill = "transparent", color = NA),
+    plot.background = element_rect(fill = "#FFFFFF33", color = NA)
+  )
+
+ggsave(
+  "standards_plot.png",
+  standards_plot,
+  device = "png",
+  width = 12, height = 9, units = "cm",
+  bg = "transparent"
+)
+```
+
+![test](plate_plot.png){height=300px} ![test](standards_plot.png){height=300px}
+
+# Tables
+
+
+```{r message=FALSE}
+
+params$qp$qp |>
+  dil_summary() |>
+  gt() |>
+  tab_options(
+    table.background.color = "#FFFFFF33",
+    table.border.top.color = "white",
+    table.border.bottom.color = "white"
+  )
+
+```
+
+
+## Summaries
+:::: {style="display: flex; justify-content: space-between;"}
+
+::: {}
+
+```{r}
+mk_tbl <- function(qp_tbl_out, name) {
+  qp_tbl_out$qp |>
+    tab_options(
+      table.background.color = "#FFFFFF33",
+      table.border.top.color = "white",
+      table.border.bottom.color = "white"
+    ) |>
+    tab_header(name)
+}
+
+mk_tbl(qp_samples_summary(params$qp), "Samples Summary")
+```
+
+:::
+
+
+::: {}
+
+```{r}
+mk_tbl(qp_standards_summary(params$qp), "Standards Summary")
+```
+
+:::
+
+
+::::
+
+## All
+:::: {style="display: flex; justify-content: space-between;"}
+
+:::{}
+
+```{r}
+mk_tbl(qp_samples_all(params$qp), "Samples")
+```
+
+:::
+
+:::{}
+
+```{r}
+mk_tbl(qp_standards_all(params$qp), "Standards")
+```
+
+:::
+
+
+::::
+
+
+```{r}
+#load_all()
+library(rmarkdown)
+f <- system.file("rmarkdown/templates/quantify-protein-report/skeleton/skeleton.Rmd", package = "qp")
+out_file <- "~/Desktop/test.html"
+# render(f, output_file = out_file, params = list(qp = qp(absorbances) |> qp_dilute(), other = list(foo = "bar", fruit = "banana")))
+```
+
+# Report Parameters
+
+```{r}
+if (length(params$other) > 0) {
+  params$other |>
+    as.data.frame() |>
+    t() |>
+    as_tibble(rownames = "Parameter") |>
+    rename("Value" = "V1") |>
+    kable()
+}
+```
diff --git a/inst/rmarkdown/templates/quantify-protein-report/skeleton/style.css b/inst/rmarkdown/templates/quantify-protein-report/skeleton/style.css
new file mode 100644
index 0000000..9df1e97
--- /dev/null
+++ b/inst/rmarkdown/templates/quantify-protein-report/skeleton/style.css
@@ -0,0 +1,31 @@
+body {
+    background: linear-gradient(45deg, #8965CD, #C1FFC1);
+    background-attachment: fixed;
+    color: white;
+    font-family: Arial;
+    font-weight: bold;
+    text-align: center;
+}
+
+h1 {
+    font-size: 40px;
+    text-align: center;
+}
+
+h2 {
+    font-size: 30px;
+    text-align: left;
+}
+
+h1, h2 {
+    font-weight: bold;
+}
+
+
+h1.title {
+    font-size: 60px;
+}
+
+body .main-container {
+    min-width: 30%;
+}
diff --git a/inst/rmarkdown/templates/quantify-protein-report/template.yaml b/inst/rmarkdown/templates/quantify-protein-report/template.yaml
new file mode 100644
index 0000000..3efdf84
--- /dev/null
+++ b/inst/rmarkdown/templates/quantify-protein-report/template.yaml
@@ -0,0 +1,4 @@
+name: Quantify Protein Report
+description: >
+  Report output from qp
+create_dir: FALSE
diff --git a/man/qp_dilute.Rd b/man/qp_dilute.Rd
index cd27af2..116516b 100644
--- a/man/qp_dilute.Rd
+++ b/man/qp_dilute.Rd
@@ -26,8 +26,8 @@ qp_dilute(x, ...)
 }
 \arguments{
 \item{x}{A \code{data.frame} or \code{list} containing a \code{data.frame} named \code{qp} with
-a column named \code{.pred_conc} or \code{.mean_pred_conc}. If both, will favor
-\code{.mean_pred_conc}.}
+a column named \code{.pred_conc} or \code{.pred_conc_mean}. If both, will favor
+\code{.pred_conc_mean}.}
 
 \item{...}{Unused}
 
diff --git a/man/qp_report.Rd b/man/qp_report.Rd
new file mode 100644
index 0000000..0880937
--- /dev/null
+++ b/man/qp_report.Rd
@@ -0,0 +1,32 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/qp_report.R
+\name{qp_report}
+\alias{qp_report}
+\title{Create a report for a protein quantificaiton experiment}
+\usage{
+qp_report(qp, output_file, other = list())
+}
+\arguments{
+\item{qp}{Likely the output from \code{qp} AND \code{qp_dilute}.}
+
+\item{output_file}{Character. The path of the file to export,
+including \code{.html}}
+
+\item{other}{Generally used for Shiny application. Assumes a
+named list of key-values that will be used to document report
+parameters.}
+}
+\description{
+Create a report for a protein quantificaiton experiment
+}
+\examples{
+\dontrun{
+absorbances |>
+  qp() |>
+  qp_dilute() |>
+  qp_report(
+    "~/my_report.html",
+    other = list(key = "value") # Essentially metadata
+  )
+}
+}
diff --git a/tests/testthat/test-qp_dilute.R b/tests/testthat/test-qp_dilute.R
index e8c7269..5ecc627 100644
--- a/tests/testthat/test-qp_dilute.R
+++ b/tests/testthat/test-qp_dilute.R
@@ -13,7 +13,7 @@ test_that("length_is_recyclable works", {
 test_that("dilution prefers .mean_pred_conc", {
   data <- data.frame(
     .pred_conc = c(1, 2),
-    .mean_pred_conc = c(5, 10)
+    .pred_conc_mean = c(5, 10)
   )
   out <- qp_dilute(data, target_conc = 5, target_vol = 2)
   expect_equal(out$sample_to_add, c(2, 1))
diff --git a/tests/testthat/test-qp_summarize.R b/tests/testthat/test-qp_summarize.R
index 8dc6397..6066dbc 100644
--- a/tests/testthat/test-qp_summarize.R
+++ b/tests/testthat/test-qp_summarize.R
@@ -13,7 +13,7 @@ test_that("qp_summarize summary is correct", {
   out <- data.frame(
     .sample_name = c(paste0("Standard ", 1:3), 1:3),
     sample_type = rep(c("standard", "unknown"), each = 3),
-    .mean_pred_conc = c(2, 8, 14, 5, 11, 17)
+    .pred_conc_mean = c(2, 8, 14, 5, 11, 17)
   )
   expect_equal(qp_summarize.data.frame(df), out)
 })