diff --git a/r/NAMESPACE b/r/NAMESPACE
index 304a2878..55d4adef 100644
--- a/r/NAMESPACE
+++ b/r/NAMESPACE
@@ -7,6 +7,7 @@ S3method(svds,default)
 export("all_matrix_inputs<-")
 export("cellNames<-")
 export("chrNames<-")
+export(Pipeline)
 export(add_cols)
 export(add_rows)
 export(all_matrix_inputs)
@@ -40,8 +41,10 @@ export(convert_matrix_type)
 export(convert_to_fragments)
 export(discrete_palette)
 export(draw_trackplot_grid)
+export(estimate)
 export(expm1_slow)
 export(extend_ranges)
+export(fit)
 export(footprint)
 export(gene_region)
 export(gene_score_archr)
@@ -85,6 +88,7 @@ export(plot_tf_footprint)
 export(plot_tss_profile)
 export(plot_tss_scatter)
 export(prefix_cell_names)
+export(project)
 export(pseudobulk_matrix)
 export(qc_scATAC)
 export(range_distance_to_nearest)
@@ -136,8 +140,17 @@ export(write_matrix_anndata_hdf5)
 export(write_matrix_dir)
 export(write_matrix_hdf5)
 export(write_matrix_memory)
+exportClasses(Estimator)
+exportClasses(PipelineBase)
+exportClasses(PipelineStep)
+exportClasses(Transformer)
 exportMethods(as.data.frame)
 exportMethods(as.matrix)
+exportMethods(c)
+exportMethods(estimate)
+exportMethods(fit)
+exportMethods(project)
+exportMethods(show)
 exportMethods(t)
 importClassesFrom(Matrix,dgCMatrix)
 importFrom(Matrix,colMeans)
diff --git a/r/R/matrix_pipelines.R b/r/R/matrix_pipelines.R
new file mode 100644
index 00000000..ea43c7f5
--- /dev/null
+++ b/r/R/matrix_pipelines.R
@@ -0,0 +1,361 @@
+# Copyright 2024 BPCells contributors
+# 
+# Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
+# https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
+# <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
+# option. This file may not be copied, modified, or distributed
+# except according to those terms.
+
+
+#' Pipeline Base Class
+#' @slot fitted (logical) Whether the pipeline has been fitted
+#' @name PipelineBase
+#' @noRd
+#' @export
+setClass("PipelineBase",
+  contains = "VIRTUAL",
+  slots = list(
+    fitted = "logical"
+  ),
+  prototype = list(
+    fitted = FALSE
+  )
+)
+
+#' Fit a pipeline object to data
+#' @param object (PipelineBase) The pipeline object to fit.
+#' @param x (IterableMatrix) Input data to be fitted on.
+#' @param y Optional output data to be fitted on.  Required if the final step is a supervised Estimator, else ignored.
+#' @return The fitted pipeline object.
+#' @details The `fit()` method is used to fit a pipeline object to data and a potential label output.  Within single estimators, the `fit()` method only
+#' takes the input data to be fitted on. Within pipelines, the `fit()` method sequentially fits the transformers on each non-terminal step of the pipeline. More specifically,
+#' The input data is transformed by each transformer, and used to fit the next transformer in the pipeline.  If the final step is an estimator, the input IterableMatrix
+#' and label (if supervised) are used to fit the estimator.
+#'
+#' The fitted pipeline object is returned, allowing for projection of new data.
+#' @name fit(PipelineBase,IterableMatrix)
+#' @export
+setGeneric("fit", function(object, x, y = NULL, ...) standardGeneric("fit"))
+#' @export
+setMethod("fit", signature(object = "PipelineBase", x = "IterableMatrix"), function(object, x, y = NULL, ...) {
+  stop("fit() method not implemented for PipelineBase")
+})
+
+#' Project input data using a fitted pipeline or pipeline step.
+#' @param object (PipelineBase) A fitted pipeline object
+#' @param x (IterableMatrix) Input data to be transformed
+#' @return (IterableMatrix) of data transformed by a fitted pipeline or pipeline step.
+#' @details Projecting data using a pipeline or pipeline step requires the pipeline to be fitted to data first.  Therefore,
+#' the `fit()` method must be executed prior to projecting any data.
+#' @name project(PipelineBase,IterableMatrix)
+#' @export
+setGeneric("project", function(object, x, ...) standardGeneric("project"))
+#' @export
+setMethod("project", signature(object = "PipelineBase", x = "IterableMatrix"), function(object, x, ...) {
+  stop("project() method not implemented for PipelineBase")
+})
+
+#' Estimate predictions on the output data using a fitted pipeline
+#' @param object (PipelineBase) The fitted pipeline object. Either the final step is an Estimator, or the pipeline is a single Estimator.
+#' @param x (IterableMatrix) Input data to be estimated on
+#' @return Predicted output labels as an array.
+#' @details Estimation of input data using a pipeline or pipeline step requires the pipeline to be fitted to data first.  Therefore,
+#' the `fit()` method must be executed prior to projecting any data.
+#' @name estimate(PipelineBase,IterableMatrix)
+#' @export
+setGeneric("estimate", function(object, x, ...) standardGeneric("estimate"))
+#' @export
+setMethod("estimate", signature(object = "PipelineBase", x = "IterableMatrix"), function(object, x, ...) {
+  stop("estimate() method not implemented for PipelineBase")
+})
+
+#' Combine pipeline objects, to create a new pipeline object.
+#' @param x (PipelineBase) The pipeline object to combine to.
+#' @param ... (PipelineBase) The pipeline objects to combine from.
+#' @name c(PipelineBase)
+#' @export
+setMethod("c", signature(x = "PipelineBase"), function(x, ...) {
+  stop("c() method not implemented for PipelineBase")
+})
+
+#' Print how to recreate the pipeline object.
+#' @details Utilizes the `short_description()` method to print the steps of the pipeline object.
+#' If the object is a pipeline, it will print the steps of the pipeline, demonstrating how to recreate the pipeline with a function call.
+#' If the object is a pipeline step, it will print the step name.
+#' @param object (PipelineBase) The pipeline object to describe.
+setMethod("show", signature(object = "PipelineBase"), function(object) {
+  stop("show() method not implemented for PipelineBase")
+})
+
+#' S4 class for combining multiple pipeline steps into a single pipeline
+#' @slot steps (list) List of pipeline steps to execute in order
+#' @name Pipeline
+setClass(
+  "Pipeline",
+  contains = "PipelineBase",
+  slots = list(
+    steps = "list"
+  ),
+  prototype = list(
+    steps = list()
+  )
+)
+
+#' Return a new Pipeline object.
+#' @param steps A list of ordered steps of operations to be converted into a pipeline object.
+#' @return A new Pipeline object.
+#' @details Pipeline objects represent multiple pipeline steps that are to be executed on input data sequentially. 
+#' Creating a pipeline object can be done by passing a list of pipeline steps to the constructor.  
+#' Creation only expects that all steps make logical sense.  i.e., the final step can be either an Estimator or a Transformer, 
+#' but each intermediate step cannot be an Estimator.
+#' 
+#' If the steps are all previously fitted, then the overall pipeline is considered fit, and can be used to project/estimate on input data.
+#' Otherwise, the pipeline must be fitted before projecting/estimating on input data.
+#' @export
+Pipeline <- function(steps = list()) {
+  # Check if all steps are transformers, with the final step being either an estimator or a transformer
+  for (i in seq_along(steps)) {
+    step <- steps[[i]]
+    # allow to fit with estimators as well
+    if (i < length(steps)) {
+      assert_is(step, "Transformer")
+    } else {
+      assert_is(step, "PipelineStep")
+    }
+  }
+  return(new("Pipeline", steps = steps))
+}
+
+
+#' Check if all steps are transformers, with the final step being either an estimator or a transformer
+#' @param object (Pipeline) The pipeline object to check
+#' @keywords internal
+check_pipeline_validity <- function(object) {
+  steps <- object@steps
+  for (i in seq_along(steps)) {
+    step <- steps[[i]]
+    # allow to fit with estimators as well
+    if (i < length(steps)) {
+      assert_is(step, "Transformer")
+    } else {
+      assert_is(step, c("PipelineStep"))
+    }
+  }
+}
+
+#' Fit the pipeline object to data
+#' @param object (Pipeline) The pipeline object to fit.
+#' @param x (IterableMatrix) Input data to be fitted on.
+#' @param y Optional output data to be fitted on.  Required if the final step is an Estimator, else ignored.
+#' @return The fitted pipeline object.
+#' @noRd
+#' @export
+setMethod("fit", signature(object = "Pipeline", x = "IterableMatrix"), function(object, x, y = NULL, ...) {
+  check_pipeline_validity(object)
+  steps <- object@steps
+  # Fit every step in the pipeline
+  for (i in seq_along(steps)) {
+    step <- steps[[i]]
+    # allow to fit with estimators as well
+    if (i < length(steps) || is.null(y)) {
+      step <- fit(step, x, ...)
+      x <- project(step, x)
+      if (is(x, "dgCMatrix")) x <- as(x, "IterableMatrix")
+    } else {
+      step <- fit(step, x, y, ...)
+    }
+    steps[[i]] <- step
+  }
+  object@steps <- steps
+  object@fitted <- TRUE
+  return(object)
+})
+
+
+#' Project input data using a fitted pipeline
+#' @param object (Pipeline) The fitted pipeline object
+#' @param x (IterableMatrix) Input data to be used by the pipeline to project new data.
+#' @return Data projected by the pipeline
+#' @noRd
+#' @export
+setMethod("project", signature(object = "Pipeline", x = "IterableMatrix"), function(object, x, ...) {
+  if (!object@fitted) stop("Pipeline must be fitted before projecting")
+  check_pipeline_validity(object)
+  # check if final step is an estimator
+  if (is(object@steps[[length(object@steps)]], "Estimator")) stop("The final step must be a transformer instead of an estimator.  Please use the `estimate()` method instead.")
+  steps <- object@steps
+  for (step in steps) {
+    x <- project(step, x)
+    # Some actions convert matrices to a different type, 
+    # so we need to convert back to IterableMatrix for following steps
+    if (is(x, "dgCMatrix")) x <- as(x, "IterableMatrix")
+  }
+  return(x)
+})
+
+
+#' Estimate predictions on the output data using a fitted pipeline
+#' @param object (Pipeline) The fitted pipeline object
+#' @param x (IterableMatrix) Input data to be estimated on
+#' @noRd
+#' @export
+setMethod("estimate", signature(object = "Pipeline", x = "IterableMatrix"), function(object, x, ...) {
+  if (!object@fitted) stop("Pipeline must be fitted before estimating")
+  check_pipeline_validity(object)
+  if (!is(object@steps[[length(object@steps)]], "Estimator")) stop("The final step must be an estimator with a estimate method. Please use the `project()` method instead.")
+  steps <- object@steps
+  for (i in seq_along(steps)) {
+    step <- steps[[i]]
+    if (i < n_steps) {
+      x <- project(step, x)
+    } else if (is(step, "Estimator")) {
+        y_pred <- estimate(step, x)
+        return(y_pred)
+    } else {
+      stop("The final step must be an estimator with a estimate method")
+    }
+  }
+})
+
+setMethod("short_description", "Pipeline", function(x) {
+  character(0)
+})
+
+#' Show the pipeline steps, demonstrating how to recreate the pipeline with a function call.
+#' @param object (Pipeline) The pipeline object to show
+#' @noRd
+#' @export
+setMethod("show", signature(object = "Pipeline"), function(object) {
+  fitted <- ifelse(object@fitted, "Fitted", "Unfitted")
+  cat(fitted, "Pipeline with steps:\n")
+  cat("Pipeline(\n")
+  for (i in seq_along(object@steps)) {
+    step <- object@steps[[i]]
+    cat("  ", short_description(step))
+    if (i < length(object@steps)) {
+      cat(",")
+    }
+    cat("\n")
+  }
+  cat(")\n")
+})
+
+#' Add steps to a pipeline, where the first argument is the pipeline object and the rest are either pipeline steps, or full pipelines to add in order.
+#' Requires for every additional step to be a pipeline object.
+#' @param x (Pipeline) The PipelineBase object to add steps to.
+#' @param ... (PipelineBase) The steps to add to the pipeline.
+#' @noRd
+#' @export
+setMethod("c", signature(x = "Pipeline"), function(x, ...) {
+  pipelines <- list(...)
+  steps <- x@steps
+  for (pipe in pipelines) {
+    assert_is(pipe, "PipelineBase")
+    # If the step is a pipeline step, add the single step.  Else, the step is a full pipeline and we want to move all the steps over.
+    if (is(pipe, "PipelineStep")) {
+      steps <- c(steps, pipe)
+    } else {
+      steps <- c(steps, pipe@steps)
+    }
+  }
+<<<<<<< Updated upstream
+  
+=======
+>>>>>>> Stashed changes
+  # If all the steps are fitted, the pipeline overall is fitted.
+  # We trust the user to have fitted the pipelines with the same data
+  new_pipeline <- Pipeline(steps = steps)
+  check_pipeline_validity(new_pipeline)
+  fitted <- TRUE
+  for (step in steps) {
+    if (!step@fitted) {
+      fitted <- FALSE
+    }
+  }
+  new_pipeline@fitted <- fitted
+  return(new_pipeline)
+})
+
+#' PipelineBase representing a single step within a pipeline
+#' @slot step_name (character) Name of the step
+#' @slot fitted (logical) Whether the pipeline has been fitted
+#' @name PipelineStep
+#' @export
+setClass("PipelineStep",
+  contains = "PipelineBase",
+  slots = list(
+    step_name = "character"
+  ),
+  prototype = list(
+    step_name = character(0)
+  )
+)
+
+#' Create a Pipeline out of pipeline steps.
+#' @param x (PipelineStep) The initial pipeline step we want to add to the pipeline
+#' @param ... (PipelineBase) The additional pipeline steps to add to the pipeline.  These can be either PipelineStep or Pipeline objects.
+#' @return A new Pipeline object with the steps added.
+#' @noRd 
+#' @export
+setMethod("c", signature(x = "PipelineStep"), function(x, ...) {
+  pipelines <- list(...)
+  steps <- list(x)
+  for (pipe in pipelines) {
+    assert_is(pipe, "PipelineBase")
+    if(is(pipe, "PipelineStep")) {
+      steps <- c(steps, pipe)
+    } else {
+      steps <- c(steps, pipe@steps)
+    }
+  }
+  new_pipeline <- Pipeline(steps = steps)
+  check_pipeline_validity(new_pipeline)
+  fitted <- TRUE
+  for (step in steps) {
+    if (!step@fitted) fitted <- FALSE
+  }
+  new_pipeline@fitted <- fitted
+  return(new_pipeline)
+})
+
+
+setMethod("show", signature(object = "PipelineStep"), function(object) {
+  cat(short_description(object))
+  cat("\n")
+})
+
+
+#' PipelineStep representing an operation that transforms data, and holds fitted parameters
+#' @slot step_name (character) Name of the step
+#' @slot fitted (logical) Whether the pipeline has been fitted
+#' @details Transformers represent single operations (derived from the PipelineStep class) that project data from an IterableMatrix to another IterableMatrix/dgCMatrix.
+#' They can be fit to data within an IterableMatrix object, which will be used to hold the fitted parameters.
+#' Using the `project()`` method on a fitted transformer will apply the transformation to the data and return
+#' the projected data as an IterableMatrix object, or a dgCMatrix.
+#'
+#' These objects can be combined into a Pipeline object using the `c()` function, with other transformers, or estimators.
+#' Transformers can also be combined with full pipelines, to create a new pipeline object.
+#' Derived classes should implement the `fit()`, `project()`, and `short_description()` methods.
+#' @name Transformer
+#' @export
+setClass("Transformer",
+  contains = "PipelineStep"
+)
+
+
+#' PipelineStep representing an operation that estimates data, and holds fitted parameters.
+#' @slot step_name (character) Name of the step
+#' @slot fitted (logical) Whether the pipeline has been fitted
+#' @details Estimators represent single operations (derived from the PipelineStep class) that make predictions based on data given by an
+#' IterableMatrix.  Additionally, supervised estimators will require a target numeric, or character array to be provided during a `fit()` call.
+#' Unsupervised estimators, on the other hand, do not require a target array.  Following a `fit()` call, the estimator will hold the fitted parameters
+#' such that data can be labeled using the `estimate()` method.
+#'
+#' Estimators can be combined into a Pipeline object using the `c()` function, with other transformers.  Estimators are required to be the terminal step
+#' within a pipeline.  Estimators can also be combined with full pipelines, to create a new pipeline object.
+#' Derived classes should implement the `fit()`, `estimate()`, and `short_description()` methods.
+#' @name Estimator
+#' @export
+setClass("Estimator",
+  contains = "PipelineStep"
+)
\ No newline at end of file
diff --git a/r/man/Estimator.Rd b/r/man/Estimator.Rd
new file mode 100644
index 00000000..346fbc83
--- /dev/null
+++ b/r/man/Estimator.Rd
@@ -0,0 +1,27 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\docType{class}
+\name{Estimator}
+\alias{Estimator}
+\title{PipelineStep representing an operation that estimates data, and holds fitted parameters.}
+\description{
+PipelineStep representing an operation that estimates data, and holds fitted parameters.
+}
+\details{
+Estimators represent single operations (derived from the PipelineStep class) that make predictions based on data given by an
+IterableMatrix.  Additionally, supervised estimators will require a target numeric, or character array to be provided during a \code{fit()} call.
+Unsupervised estimators, on the other hand, do not require a target array.  Following a \code{fit()} call, the estimator will hold the fitted parameters
+such that data can be labeled using the \code{estimate()} method.
+
+Estimators can be combined into a Pipeline object using the \code{c()} function, with other transformers.  Estimators are required to be the terminal step
+within a pipeline.  Estimators can also be combined with full pipelines, to create a new pipeline object.
+Derived classes should implement the \code{fit()}, \code{estimate()}, and \code{short_description()} methods.
+}
+\section{Slots}{
+
+\describe{
+\item{\code{step_name}}{(character) Name of the step}
+
+\item{\code{fitted}}{(logical) Whether the pipeline has been fitted}
+}}
+
diff --git a/r/man/Pipeline.Rd b/r/man/Pipeline.Rd
new file mode 100644
index 00000000..efed722b
--- /dev/null
+++ b/r/man/Pipeline.Rd
@@ -0,0 +1,31 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\docType{class}
+\name{Pipeline}
+\alias{Pipeline}
+\title{S4 class for combining multiple pipeline steps into a single pipeline}
+\usage{
+Pipeline(steps = list())
+}
+\arguments{
+\item{steps}{A list of ordered steps to be executed in the pipeline.}
+}
+\value{
+A new Pipeline object.
+}
+\description{
+S4 class for combining multiple pipeline steps into a single pipeline
+
+Return a new Pipeline object.
+}
+\details{
+Creating a pipeline object can be done by passing a list of pipeline steps to the constructor.
+Creation only expects that all steps make logical sense.  i.e., the final step can be either an Estimator or a Transformer,
+but each intermediate step cannot be an Estimator.
+}
+\section{Slots}{
+
+\describe{
+\item{\code{steps}}{(list) List of pipeline steps to execute in order}
+}}
+
diff --git a/r/man/PipelineStep.Rd b/r/man/PipelineStep.Rd
new file mode 100644
index 00000000..a54db9ae
--- /dev/null
+++ b/r/man/PipelineStep.Rd
@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\docType{class}
+\name{PipelineStep}
+\alias{PipelineStep}
+\title{PipelineBase representing a single step within a pipeline}
+\description{
+PipelineBase representing a single step within a pipeline
+}
+\section{Slots}{
+
+\describe{
+\item{\code{step_name}}{(character) Name of the step}
+
+\item{\code{fitted}}{(logical) Whether the pipeline has been fitted}
+}}
+
diff --git a/r/man/Transformer.Rd b/r/man/Transformer.Rd
new file mode 100644
index 00000000..ce341fdf
--- /dev/null
+++ b/r/man/Transformer.Rd
@@ -0,0 +1,27 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\docType{class}
+\name{Transformer}
+\alias{Transformer}
+\title{PipelineStep representing an operation that transforms data, and holds fitted parameters}
+\description{
+PipelineStep representing an operation that transforms data, and holds fitted parameters
+}
+\details{
+Transformers represent single operations (derived from the PipelineStep class) that project data from an IterableMatrix to another IterableMatrix/dgCMatrix.
+They can be fit to data within an IterableMatrix object, which will be used to hold the fitted parameters.
+Using the `project()`` method on a fitted transformer will apply the transformation to the data and return
+the projected data as an IterableMatrix object, or a dgCMatrix.
+
+These objects can be combined into a Pipeline object using the \code{c()} function, with other transformers, or estimators.
+Transformers can also be combined with full pipelines, to create a new pipeline object.
+Derived classes should implement the \code{fit()}, \code{project()}, and \code{short_description()} methods.
+}
+\section{Slots}{
+
+\describe{
+\item{\code{step_name}}{(character) Name of the step}
+
+\item{\code{fitted}}{(logical) Whether the pipeline has been fitted}
+}}
+
diff --git a/r/man/c-open-paren-PipelineBase-close-paren.Rd b/r/man/c-open-paren-PipelineBase-close-paren.Rd
new file mode 100644
index 00000000..09d8b7a7
--- /dev/null
+++ b/r/man/c-open-paren-PipelineBase-close-paren.Rd
@@ -0,0 +1,16 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\name{c(PipelineBase)}
+\alias{c(PipelineBase)}
+\title{Combine pipeline objects, to create a new pipeline object.}
+\usage{
+\S4method{c}{PipelineBase}(x, ...)
+}
+\arguments{
+\item{x}{(PipelineBase) The pipeline object to combine to.}
+
+\item{...}{(PipelineBase) The pipeline objects to combine from.}
+}
+\description{
+Combine pipeline objects, to create a new pipeline object.
+}
diff --git a/r/man/call_macs_peaks.Rd b/r/man/call_macs_peaks.Rd
new file mode 100644
index 00000000..5ad425c5
--- /dev/null
+++ b/r/man/call_macs_peaks.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/atac_utils.R
+\name{call_macs_peaks}
+\alias{call_macs_peaks}
+\title{Call peaks using MACS2/3}
+\usage{
+call_macs_peaks(...)
+}
+\description{
+\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}
+
+This function has been renamed to \code{call_peaks_macs()}
+}
+\keyword{internal}
diff --git a/r/man/check_pipeline_validity.Rd b/r/man/check_pipeline_validity.Rd
new file mode 100644
index 00000000..4e314773
--- /dev/null
+++ b/r/man/check_pipeline_validity.Rd
@@ -0,0 +1,15 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\name{check_pipeline_validity}
+\alias{check_pipeline_validity}
+\title{Check if all steps are transformers, with the final step being either an estimator or a transformer}
+\usage{
+check_pipeline_validity(object)
+}
+\arguments{
+\item{object}{(Pipeline) The pipeline object to check}
+}
+\description{
+Check if all steps are transformers, with the final step being either an estimator or a transformer
+}
+\keyword{internal}
diff --git a/r/man/estimate-open-paren-PipelineBase-IterableMatrix-close-paren.Rd b/r/man/estimate-open-paren-PipelineBase-IterableMatrix-close-paren.Rd
new file mode 100644
index 00000000..755e3fba
--- /dev/null
+++ b/r/man/estimate-open-paren-PipelineBase-IterableMatrix-close-paren.Rd
@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\name{estimate(PipelineBase,IterableMatrix)}
+\alias{estimate(PipelineBase,IterableMatrix)}
+\title{Estimate predictions on the output data using a fitted pipeline}
+\usage{
+estimate(object, x, ...)
+}
+\arguments{
+\item{object}{(PipelineBase) The fitted pipeline object. Either the final step is an Estimator, or the pipeline is a single Estimator.}
+
+\item{x}{(IterableMatrix) Input data to be estimated on}
+}
+\value{
+Predicted output labels
+}
+\description{
+Estimate predictions on the output data using a fitted pipeline
+}
diff --git a/r/man/fit-open-paren-PipelineBase-IterableMatrix-close-paren.Rd b/r/man/fit-open-paren-PipelineBase-IterableMatrix-close-paren.Rd
new file mode 100644
index 00000000..c4faf066
--- /dev/null
+++ b/r/man/fit-open-paren-PipelineBase-IterableMatrix-close-paren.Rd
@@ -0,0 +1,29 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\name{fit(PipelineBase,IterableMatrix)}
+\alias{fit(PipelineBase,IterableMatrix)}
+\title{Fit a pipeline object to data}
+\usage{
+fit(object, x, y = NULL, ...)
+}
+\arguments{
+\item{object}{(PipelineBase) The pipeline object to fit.}
+
+\item{x}{(IterableMatrix) Input data to be fitted on.}
+
+\item{y}{Optional output data to be fitted on.  Required if the final step is a supervised Estimator, else ignored.}
+}
+\value{
+The fitted pipeline object.
+}
+\description{
+Fit a pipeline object to data
+}
+\details{
+The \code{fit()} method is used to fit a pipeline object to data and a potential label output.  Within single estimators, the \code{fit()} method only
+takes the input data to be fitted on. Within pipelines, the \code{fit()} method sequentially fits the transformers on each non-terminal step of the pipeline. More specifically,
+The input data is transformed by each transformer, and used to fit the next transformer in the pipeline.  If the final step is an estimator, the input IterableMatrix
+and label (if supervised) are used to fit the estimator.
+
+The fitted pipeline object is returned, allowing for projection of new data.
+}
diff --git a/r/man/project-open-paren-PipelineBase-IterableMatrix-close-paren.Rd b/r/man/project-open-paren-PipelineBase-IterableMatrix-close-paren.Rd
new file mode 100644
index 00000000..ffa6c5c4
--- /dev/null
+++ b/r/man/project-open-paren-PipelineBase-IterableMatrix-close-paren.Rd
@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/matrix_pipelines.R
+\name{project(PipelineBase,IterableMatrix)}
+\alias{project(PipelineBase,IterableMatrix)}
+\title{Project input data using a fitted pipeline}
+\usage{
+project(object, x, ...)
+}
+\arguments{
+\item{object}{(PipelineBase) A fitted pipeline object}
+
+\item{x}{(IterableMatrix) Input data to be transformed}
+}
+\value{
+Data projected by the pipeline
+}
+\description{
+Project input data using a fitted pipeline
+}
diff --git a/r/man/write_insertion_bed.Rd b/r/man/write_insertion_bed.Rd
index e4e4a664..ad190e13 100644
--- a/r/man/write_insertion_bed.Rd
+++ b/r/man/write_insertion_bed.Rd
@@ -8,7 +8,7 @@ write_insertion_bed(
   fragments,
   path,
   cell_groups = rlang::rep_along(cellNames(fragments), "all"),
-  insertion_mode = c("start_only", "both", "end_only"),
+  insertion_mode = c("both", "start_only", "end_only"),
   verbose = FALSE,
   threads = 1
 )
diff --git a/r/pkgdown/_pkgdown.yml b/r/pkgdown/_pkgdown.yml
index c08f55f0..038b1cdb 100644
--- a/r/pkgdown/_pkgdown.yml
+++ b/r/pkgdown/_pkgdown.yml
@@ -173,3 +173,22 @@ reference:
   - discrete_palette
   - collect_features
   - rotate_x_labels
+
+
+- title: "Matrix Projections and Predictions"
+
+- subtitle: "Pipeline S4 Classes"
+- desc: Base class for pipeline objects
+- contents:
+  - PipelineStep
+  - Pipeline
+  - Transformer
+  - Estimator
+
+
+- subtitle: "Pipeline Methods"
+- contents:
+  - fit(PipelineBase,IterableMatrix)
+  - estimate(PipelineBase,IterableMatrix)
+  - project(PipelineBase,IterableMatrix)
+  - c(PipelineBase)