diff --git a/R/adat-helpers.R b/R/adat-helpers.R
index bed00ca..998028c 100644
--- a/R/adat-helpers.R
+++ b/R/adat-helpers.R
@@ -8,7 +8,7 @@
 #' [checkSomaScanVersion()] determines if the version of
 #'   is a recognized version of SomaScan.\cr
 #' \cr
-#' Table of SomaScan Assay versions:
+#' Table of SomaScan assay versions:
 #' \tabular{lll}{
 #'   **Version**  \tab **Commercial Name** \tab **Size** \cr
 #'   `V4`         \tab 5k                  \tab 5284     \cr
diff --git a/R/lift-adat.R b/R/lift-adat.R
index d729b81..362a239 100644
--- a/R/lift-adat.R
+++ b/R/lift-adat.R
@@ -5,7 +5,7 @@
 #' between assay versions; from changing reagents, liquid handling equipment,
 #' well volumes, and content expansion.
 #'
-#' Table of SomaScan Assay versions:
+#' Table of SomaScan assay versions:
 #'
 #' \tabular{lll}{
 #'   **Version**  \tab **Commercial Name** \tab **Size** \cr
@@ -36,34 +36,22 @@
 #' @details
 #' Matched samples across assay versions are used to calculate bridging
 #' scalars. For each analyte, this scalar is computed as the ratio of
-#' population _medians_ (\eqn{n > 1000}) between assay versions. For example,
-#' the linear scalar for the \eqn{i^{th}} analyte translating from `11k` -> `7k`
-#' is defined as:
-#'
-#' \deqn{R_i = \frac{\hat\mu_{7k}}{\hat\mu_{11k}}}
+#' population _medians_ across assay versions.
+#' Please see the lifting vignette
+#' `vignette("lifting-and-bridging", package = "SomaDataIO")`
+#' for more details.
 #'
 #' @section Lin's CCC:
-#'   Calculating analyte-specific bridging scalars involves a careful evaluation
-#'   of the correlation of post-lifting RFU values in the reference population
-#'   used to calculate the linear scalars. The Lin's Concordance Correlation
-#'   Coefficient (CCC) is calculated between matched samples from the original
-#'   SomaScan signal space and the identical lifted samples that have been
-#'   scaled back to the original signal space. This CCC value is an estimate
-#'   of how well an analyte can be bridged across specific SomaScan versions.
-#'   Factors affecting an analyte's lifting CCC are: reagents with high
-#'   intra-assay CV (Coefficient of Variation) and reagents signaling
-#'   near background or saturation levels.
+#'   The Lin's Concordance Correlation Coefficient (CCC) is calculated
+#'   by computing the correlation between post-lift RFU values and the
+#'   RFU values generated on the original SomaScan version.
+#'   This CCC estimate is a measure of how well an analyte can be bridged
+#'   across SomaScan versions.
+#'   See `vignette("lifting-and-bridging", package = "SomaDataIO")`.
 #'   As with the lifting scalars, if you have an annotations file
 #'   you may view the analyte-specific CCC values via [read_annotations()].
 #'   Alternatively, [getSomaScanLiftCCC()] retrieves these values
 #'   from an internal object for both `"serum"` and `"plasma"`.
-#'   Lin's CCC (\eqn{p_c}) is defined by:
-#'
-#'   \deqn{p_c = \frac{2\rho\hat\sigma_x\hat\sigma_y}{(\hat\mu_x - \hat\mu_y)^2 + \hat\sigma^2_x + \hat\sigma^2_y}}
-#'
-#'   where \eqn{\rho}, \eqn{\mu}, and \eqn{\sigma} are the Pearson correlation
-#'   coefficient, and estimated median and standard deviation estimates from
-#'   assay version groups \eqn{x} and \eqn{y} respectively.
 #'
 #' @section Extra Columns:
 #' * Newer versions of SomaScan typically have additional content, i.e.
diff --git a/_pkgdown.yml b/_pkgdown.yml
index d82b4aa..c7a1541 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -79,7 +79,7 @@ navbar:
         href: articles/stat-binary-classification.html
       - text: Linear Regression
         href: articles/stat-linear-regression.html
-    
+
     FAQs:
       text: Coming Soon
       menu:
@@ -106,6 +106,11 @@ articles:
     contents:
     - cli-merge-tool
 
+  - title: Lifting and Bridging
+    navbar: ~
+    contents:
+    - lifting-and-bridging
+
   - title: Statistical Workflow Examples
     contents:
     - starts_with("articles/stat-")
@@ -139,12 +144,15 @@ reference:
 
   - title: Transform Between SomaScan Versions
     desc: >
-      Functionality required to convert between SomaScan versions,
-      e.g. v4.1 -> v4.0, sometimes referred to as "lifting".
+      Functionality required to bridge between SomaScan versions,
+      e.g. 11k -> 7k, sometimes referred to as "lifting".
     contents:
-    - read_annotations
     - lift_adat
+    - read_annotations
     - transform
+    - getSomaScanLiftCCC
+    - getSomaScanVersion
+    - getSignalSpace
 
   - title: Expression Data
     desc: >
diff --git a/man/adat-helpers.Rd b/man/adat-helpers.Rd
index 787c0d8..9c560e7 100644
--- a/man/adat-helpers.Rd
+++ b/man/adat-helpers.Rd
@@ -48,7 +48,7 @@ These are elements of the \code{HEADER} attributes of the object.\cr\cr
 \code{\link[=checkSomaScanVersion]{checkSomaScanVersion()}} determines if the version of
 is a recognized version of SomaScan.\cr
 \cr
-Table of SomaScan Assay versions:
+Table of SomaScan assay versions:
 \tabular{lll}{
 \strong{Version}  \tab \strong{Commercial Name} \tab \strong{Size} \cr
 \code{V4}         \tab 5k                  \tab 5284     \cr
diff --git a/man/lift_adat.Rd b/man/lift_adat.Rd
index 7008369..5131dd6 100644
--- a/man/lift_adat.Rd
+++ b/man/lift_adat.Rd
@@ -34,7 +34,7 @@ The SomaScan platform continually improves its technical processes
 between assay versions; from changing reagents, liquid handling equipment,
 well volumes, and content expansion.
 
-Table of SomaScan Assay versions:
+Table of SomaScan assay versions:
 
 \tabular{lll}{
 \strong{Version}  \tab \strong{Commercial Name} \tab \strong{Size} \cr
@@ -65,35 +65,23 @@ See below for all options for the \code{bridge} argument.
 \details{
 Matched samples across assay versions are used to calculate bridging
 scalars. For each analyte, this scalar is computed as the ratio of
-population \emph{medians} (\eqn{n > 1000}) between assay versions. For example,
-the linear scalar for the \eqn{i^{th}} analyte translating from \verb{11k} -> \verb{7k}
-is defined as:
-
-\deqn{R_i = \frac{\hat\mu_{7k}}{\hat\mu_{11k}}}
+population \emph{medians} across assay versions.
+Please see the lifting vignette
+\code{vignette("lifting-and-bridging", package = "SomaDataIO")}
+for more details.
 }
 \section{Lin's CCC}{
 
-Calculating analyte-specific bridging scalars involves a careful evaluation
-of the correlation of post-lifting RFU values in the reference population
-used to calculate the linear scalars. The Lin's Concordance Correlation
-Coefficient (CCC) is calculated between matched samples from the original
-SomaScan signal space and the identical lifted samples that have been
-scaled back to the original signal space. This CCC value is an estimate
-of how well an analyte can be bridged across specific SomaScan versions.
-Factors affecting an analyte's lifting CCC are: reagents with high
-intra-assay CV (Coefficient of Variation) and reagents signaling
-near background or saturation levels.
+The Lin's Concordance Correlation Coefficient (CCC) is calculated
+by computing the correlation between post-lift RFU values and the
+RFU values generated on the original SomaScan version.
+This CCC estimate is a measure of how well an analyte can be bridged
+across SomaScan versions.
+See \code{vignette("lifting-and-bridging", package = "SomaDataIO")}.
 As with the lifting scalars, if you have an annotations file
 you may view the analyte-specific CCC values via \code{\link[=read_annotations]{read_annotations()}}.
 Alternatively, \code{\link[=getSomaScanLiftCCC]{getSomaScanLiftCCC()}} retrieves these values
 from an internal object for both \code{"serum"} and \code{"plasma"}.
-Lin's CCC (\eqn{p_c}) is defined by:
-
-\deqn{p_c = \frac{2\rho\hat\sigma_x\hat\sigma_y}{(\hat\mu_x - \hat\mu_y)^2 + \hat\sigma^2_x + \hat\sigma^2_y}}
-
-where \eqn{\rho}, \eqn{\mu}, and \eqn{\sigma} are the Pearson correlation
-coefficient, and estimated median and standard deviation estimates from
-assay version groups \eqn{x} and \eqn{y} respectively.
 }
 
 \section{Extra Columns}{
diff --git a/vignettes/lifting-and-bridging.Rmd b/vignettes/lifting-and-bridging.Rmd
new file mode 100644
index 0000000..d1b6b11
--- /dev/null
+++ b/vignettes/lifting-and-bridging.Rmd
@@ -0,0 +1,302 @@
+---
+title: "Lifting and Bridging SomaScan"
+author: "Stu Field, SomaLogic Operating Co., Inc."
+description: >
+  A primer on lifting and bridging 'SomaScan' data.
+output:
+  rmarkdown::html_vignette:
+    fig_caption: yes
+vignette: >
+  %\VignetteIndexEntry{Lifting and Bridging SomaScan}
+  %\VignetteEncoding{UTF-8}
+  %\VignetteEngine{knitr::rmarkdown}
+editor_options: 
+  chunk_output_type: console
+---
+
+```{r setup, include = FALSE}
+library(SomaDataIO)
+library(ggplot2)
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+
+
+# Overview
+
+`SomaDataIO` contains functionality to bridge
+(aka "lift") between various SomaScan versions by linear transformations
+of RFU data.
+Lifting between various versions is essentially a calibration of the
+analyte/features in RFU space.
+
+
+## Why lift?
+
+The SomaScan platform continually improves its technical processes
+between assay versions; from changing reagents, liquid handling equipment,
+well volumes, and content expansion.
+
+However, for a given analyte, these technical upgrades can result
+in minute measurement signal differences,
+requiring a calibration (aka "lifting" or "bridging") to bring RFUs into a
+comparable signal space.
+This is accomplished by applying an analyte-specific scalar,
+a linear transformation, to each analyte RFU measurement (column).
+
+### Current SomaScan Versions
+
+| **Version**   | **Commercial Name** | **Size**      |
+|:------------- |:------------------- |:------------- |
+|  `V4`         | 5k                  | 5284          |
+|  `v4.1`       | 7k                  | 7596          |
+|  `v5.0`       | 11k                 | 11083         |
+
+
+### Lifting Requirements
+
+There are 4 main requirements in order to reliably bridge
+across SomaScan signal space:
+
+1. the object attributes, where signal information is stored, must be intact.
+1. the sample matrix must be either serum or plasma. No other matrices
+   are currently supported.
+1. the RFU data must have been normalized by Adaptive Normalization via
+   Maximum-Likelihood (ANML). This is the standard normalization for
+   most SomaScan deliveries.
+1. the current SomaScan version and signal space must be one of those
+   above (see table), i.e. one of `5k`, `7k`, or `11k`. Older versions
+   of SomaScan are not supported.
+
+---------------
+
+## Lifting Scalars
+
+Matched samples (n > 1000) from a healthy, normal reference population
+were run across assay versions and used to calculate bridging scalars. 
+This experiment was run separately for both serum and plasma and all
+SomaScan runs were first normalized as per the standard normalization
+procedure, and flagged samples were removed prior to further analysis.
+
+For each analyte, the "lifting" or "bridging" scalar is computed as the
+ratio of population _medians_ between assay versions. For example,
+the linear scalar for the $i^{th}$ analyte translating from `11k -> 7k`
+is defined as:
+
+$$
+R_i = \frac{\hat\mu_{7k}}{\hat\mu_{11k}}
+$$
+
+Signals generated in `11k` space can be multiplied by this scale factor
+to translate into `7k` space.
+
+
+## Lin's CCC:
+
+The Lin's Concordance Correlation Coefficient (CCC) is calculated
+by computing the correlation between post-lift RFU values and the
+RFU values generated on the original SomaScan version. Measurements
+generated from the matched samples used to calculate the lifting scalars
+were also used to calculate the post-hoc CCC estimates for the SomaScan
+bridge.
+Lin's CCC ($p_c$) is defined by:
+
+$$
+p_c = \frac{2\rho\hat\sigma_x\hat\sigma_y}{(\hat\mu_x - \hat\mu_y)^2 + \hat\sigma^2_x + \hat\sigma^2_y}
+$$
+
+where $\rho$, $\mu$, and $\sigma$ are the Pearson correlation
+coefficient, and estimated median and standard deviation estimates from
+assay version groups _x_ and _y_ respectively.
+
+
+### Interpretation of CCC
+
+This CCC value can be viewed as an estimate of the confidence in the
+bridging transformation across SomaScan versions.
+
+Factors affecting an analyte's lifting CCC are: reagents with high
+intra-assay CV (Coefficient of Variation) and reagents signaling
+near background or saturation levels.
+
+
+
+### Accessing CCC
+
+The `getSomaScanLiftCCC()` function retrieves these values
+from an internal object for either `"serum"` and `"plasma"`.
+
+```{r ccc}
+plasma <- getSomaScanLiftCCC("p")
+plasma
+
+serum <- getSomaScanLiftCCC("s")
+serum
+```
+
+```{r cdf, fig.width = 6, fig.height = 5}
+cdf_df <- data.frame(
+  ccc    = c(plasma$plasma_11k_to_7k_ccc, serum$serum_11k_to_7k_ccc),
+  matrix = rep(c("plasma", "serum"), each = nrow(plasma))
+)
+cdf_df <- cdf_df[!is.na(cdf_df$ccc), ]   # rm NAs; non-comparable analytes
+ggplot(cdf_df, aes(x = ccc, colour = matrix)) +
+  stat_ecdf(linewidth = 0.75) +
+  scale_colour_manual(name = "", values = c("#00A499", "#24135F")) +
+  labs(title = "CDF of CCC Values",
+       x = "Lin's CCC (11k -> 7k)", y = "P(X < x)") +
+  coord_cartesian()
+```
+
+As shown in distribution above, for the `11k -> 7k` lift, post-bridging
+CCC values above 0.75 (high quality) are approximately 88% and 84% of
+the SomaScan menu for plasma and serum respectively.
+
+
+## Column Setdiff
+
+There are two scenarios to consider:
+
+* Newer versions of SomaScan typically have additional content, i.e.
+  new reagents added to the multi-plex assay that bind to additional proteins.
+  When lifting _to_ a previous SomaScan version, new reagents that do _not_
+  exist in the "earlier" assay version assay are scaled by 1.0, and thus
+  maintained, unmodified in the returned object. Users may need to drop
+  these columns in order to combine these data with a previous study
+  from an earlier SomaScan version, e.g. with `collapseAdats()`.
+* In the inverse scenario, lifting "forward" _from_ a previous, lower-plex
+  version, there will be extra reference values that are unnecessary
+  to perform the lift, and a warning is triggered. The resulting data
+  consists of RFU data in the "new" signal space, but with fewer analytes
+  than would otherwise be expected (e.g. `11k` space with only 5284
+  analytes; see example below).
+
+
+------------
+
+
+## Example: `5k` -> `11k`
+### Steps:
+
+1. Determine that attributes are intact:
+   ```r
+   is_intact_attr(adat)
+   ```
+1. Determine the matrix type of the data (serum or plasma)
+   ```r
+   attr(adat, "Header.Meta")$HEADER$StudyMatrix
+   ```
+1. Determine whether the SomaScan version is supported
+   ```r
+   checkSomaScanVersion(getSomaScanVersion(adat))
+   ```
+1. Ensure the current `soma_adat` is in the SomaScan version space you think
+   ```r
+   getSignalSpace(adat)
+   ```
+1. Apply the scale factors using `lift_adat()`
+   ```r
+   lift_adat(adat, bridge = "<direction>")
+   ```
+
+### Step 1
+```{r attr}
+# determine intact attributes
+is_intact_attr(example_data)
+```
+
+### Step 2
+```{r matx}
+# determine study matrix
+attr(example_data, "Header.Meta")$HEADER$StudyMatrix |> as.character()
+```
+
+Confirm that the matrix of the SomaScan run was `"EDTA Plasma"`.
+
+### Step 3
+```{r version}
+# determine if current space can be lifted
+is.null(checkSomaScanVersion(getSomaScanVersion(example_data)))
+```
+
+### Step 4
+```{r space}
+# determine current SomaScan space
+getSignalSpace(example_data)
+```
+
+The `example_data` object is in `r getSignalSpace(example_data)` space,
+so for this vignette assume we wish to lift to `11k` signal space.
+Invoke `lift_adat()` to perform the lift/bridge/transformation:
+
+### Step 5
+```{r lift}
+lift_11k <- lift_adat(example_data, bridge = "5k_to_11k")
+
+is_lifted(lift_11k)
+
+is.soma_adat(lift_11k)
+
+getSignalSpace(lift_11k)
+
+getSomaScanVersion(lift_11k)
+```
+
+
+-------------
+
+
+## Visualize Linear Transformation
+
+It is always a good idea to plot the before/after to ensure it actually did
+what you think (in this case a linear shift or bias).
+In this example let's randomly select an analyte:
+
+```{r seq}
+seq <- withr::with_seed(101, sample(getAnalytes(lift_11k), 1L))
+seq
+
+tbl <- getAnalyteInfo(lift_11k)
+filter(tbl, AptName == seq) |>
+  unlist() |>
+  tibble::enframe()
+```
+
+If you have downloaded and are familiar with our plotting package
+[SomaPlotr](https://github.com/SomaLogic/SomaPlotr), it can be useful to
+plot concordance between 2 numeric vectors.
+See `SomaPlotr::plotConcord()`.
+
+Below we visualize the linear shift that was performed for `r seq`.
+
+```{r plot, echo = FALSE, fig.width = 6, fig.height = 5}
+target_tbl <- getTargetNames(tbl)
+plot_df <- data.frame(
+  orig  = rep(example_data[[seq]], 2L),
+  lift  = c(example_data[[seq]] / 0.75, example_data[[seq]]),
+  group = rep(c("pre-lift", "post-lift"), each = nrow(lift_11k))
+)
+lims <- range(plot_df[, -3L])
+plot_df |>
+  ggplot(aes(x = orig, y = lift, colour = group)) +
+  geom_point(alpha = 0.5, size = 3) +
+  scale_x_log10() +
+  scale_y_log10() +
+  scale_colour_manual(name = "", values = c("#00A499", "#24135F")) +
+  expand_limits(x = lims, y = lims) +
+  labs(x = "5k", y = "11k",
+       title = sprintf("Lifting Concordance: %s", target_tbl[[seq]])) +
+  geom_abline(slope = 1, intercept = 0, color = "black")
+```
+
+The figure above highlights the linear shift (down) that was applied to the `5k`
+RFU signal space to transform it into `11k` signal space.
+The low-signaling samples ($n = 6$) at ~100 RFU are control (`Buffer`)
+samples containing no protein.
+
+```{r buffers}
+table(lift_11k$SampleType)
+```
+