diff --git a/man/calcDivIndexes.Rd b/man/calcDivIndexes.Rd
index dae2ffa..b959be7 100644
--- a/man/calcDivIndexes.Rd
+++ b/man/calcDivIndexes.Rd
@@ -4,10 +4,12 @@
 \alias{calcDivIndexes}
 \title{Calculate diversity indices for barcode samples}
 \usage{
-calcDivIndexes(dat)
+calcDivIndexes(counts, group = NULL)
 }
 \arguments{
-\item{dat}{dataframe of raw or normalised counts with samples as columns and observations/barcodes as rows}
+\item{counts}{dataframe of raw or normalised counts with samples as columns and observations/barcodes as rows}
+
+\item{group}{vector of sample group metadata, assumes the same sample order as counts}
 }
 \value{
 Returns a data-frame containing the calculated diversity indices per sample
@@ -23,5 +25,5 @@ calcDivIndexes
 Calculates common diversity indices per sample in a dataframe of counts
 }
 \examples{
-indexes <- calcDivIndexes(dat = test.counts)
+indexes <- calcDivIndexes(counts = test.dge$counts)
 }
diff --git a/man/compareAbundance.Rd b/man/compareAbundance.Rd
index 47449f5..9dd129a 100644
--- a/man/compareAbundance.Rd
+++ b/man/compareAbundance.Rd
@@ -4,29 +4,49 @@
 \alias{compareAbundance}
 \title{Barcode abundance comparison}
 \usage{
-compareAbundance(counts, condition, condition_names)
+compareAbundance(
+  dge.obj,
+  meta,
+  condition1,
+  condition2,
+  pval.cutoff = 0.05,
+  logFC.cutoff = 2,
+  filename = NULL
+)
 }
 \arguments{
-\item{counts}{dataframe containing raw counts of barcodes}
+\item{dge.obj}{DGElist list object with counts and samples dataframe}
 
-\item{condition}{sample condition of interest}
+\item{meta}{Name of metadata field of interest for the comparison}
 
-\item{condition_names}{names of possible conditions in experiment}
+\item{condition1}{Name of reference condition in meta}
+
+\item{condition2}{Name of second condition in meta}
+
+\item{pval.cutoff}{Pvalue threshold for the volcano plot}
+
+\item{logFC.cutoff}{logFC threshold for the volcano plot}
+
+\item{filename}{Filename for the results of the likelihood ratio test}
 }
 \value{
-Returns a text file
+Returns a volcano plot and a csv file with differentially abundant 
+barcode results
 }
 \description{
-Takes a dataframe of barcode counts,
-computes the mean abundance of each barcode for two specific conditions,
-then do a line plot for both conditions
+Takes a DGElist list object with counts and samples dataframe.
+Finds differentially abundant barcodes between two experimental conditions,
+using the likelihood ratio test (LRT) based on the fitted generalized linear 
+model (GLM) to compare two nested models, typically a reduced model and a 
+full model, to determine if the additional terms in the full model 
+significantly improve the model fit.  Additionally, it computes the p-values
+associated with the test statistic for each barcode.
+It save the results in a csv file and returns a volcano plot.
 }
 \details{
 compareAbundance
-
-Compare barcode abundance between 2 conditions using EdgeR
 }
 \examples{
 data(test.dge)
-compareAbundance(test.dge, test.dge$samples$group, c("T0","10_High_dose"))
+compareAbundance(test.dge,"Treatment", "Vehicle","Low_dose",0.01,2)       
 }
diff --git a/man/figures/README-example-1.png b/man/figures/README-example-1.png
new file mode 100644
index 0000000..9c7e2fc
Binary files /dev/null and b/man/figures/README-example-1.png differ
diff --git a/man/figures/README-example-2.png b/man/figures/README-example-2.png
new file mode 100644
index 0000000..cf980c0
Binary files /dev/null and b/man/figures/README-example-2.png differ
diff --git a/man/figures/README-example-3.png b/man/figures/README-example-3.png
new file mode 100644
index 0000000..77a735f
Binary files /dev/null and b/man/figures/README-example-3.png differ
diff --git a/man/figures/README-example-4.png b/man/figures/README-example-4.png
new file mode 100644
index 0000000..c7e3e79
Binary files /dev/null and b/man/figures/README-example-4.png differ
diff --git a/man/normaliseCounts.Rd b/man/normaliseCounts.Rd
index cdc1b7b..34e2223 100644
--- a/man/normaliseCounts.Rd
+++ b/man/normaliseCounts.Rd
@@ -4,12 +4,12 @@
 \alias{normaliseCounts}
 \title{Normalise barcode counts}
 \usage{
-normaliseCounts(dge, method = "cpm", threshold = 0)
+normaliseCounts(dge, method = "CPM", threshold = 0)
 }
 \arguments{
 \item{dge}{DGEList object containing raw barcode counts to be normalised}
 
-\item{method}{method of normalisation}
+\item{method}{method of normalization. One of cpm, tmm, tmmwsp, upperquartile or rle. see edgeR::calcNormFactors()}
 
 \item{threshold}{Threshold to apply to counts before normalisation}
 }
@@ -21,6 +21,6 @@ Normalise barcode counts within a DGEList object
 }
 \examples{
 data(test.dge)
-normaliseCounts(test.dge, method = "cpm", threshold = 0)
+normaliseCounts(test.dge, method = "CPM", threshold = 0)
 
 }
diff --git a/man/plotBarcodeBoxplot.Rd b/man/plotBarcodeBoxplot.Rd
index 92edb7f..948cfc1 100644
--- a/man/plotBarcodeBoxplot.Rd
+++ b/man/plotBarcodeBoxplot.Rd
@@ -4,14 +4,30 @@
 \alias{plotBarcodeBoxplot}
 \title{Boxplot of selected barcodes}
 \usage{
-plotBarcodeBoxplot(dge.obj, barcodes, condition = NULL)
+plotBarcodeBoxplot(
+  dge.obj,
+  barcodes = NULL,
+  group = NULL,
+  conditions = NULL,
+  trans = NULL,
+  point = FALSE,
+  violin = FALSE
+)
 }
 \arguments{
 \item{dge.obj}{DGE object containing counts and sample information}
 
-\item{barcodes}{vector of barcodes to be plotted}
+\item{barcodes}{a vector of barcodes to be plotted}
 
-\item{condition}{specific metadata condition to be plotted}
+\item{group}{metadata field to facet data on}
+
+\item{conditions}{specific levels of group to be plotted. If NULL all levels are plotted}
+
+\item{trans}{From ggplot2. For continuous scales, the name of a transformation object or the object itself.}
+
+\item{point}{From ggplot2. Include plot points?}
+
+\item{violin}{From ggplot2. Include violin plot?}
 }
 \value{
 Returns a boxplot
@@ -28,7 +44,6 @@ Boxplot of selected barcodes
 }
 \examples{
 data(test.dge)
-barcodes <- sample(rownames(test.dge), 10)
-plotBarcodeBoxplot(test.dge, barcodes)
-plotBarcodeBoxplot(test.dge, barcodes, condition = c("T0", "T0b"))
+plotBarcodeBoxplot(test.dge, barcodes = "BC_190202", group = "Treatment", 
+conditions = c("Vehicle", "Low_dose", "High_dose"))
 }
diff --git a/man/plotBarcodeBubble.Rd b/man/plotBarcodeBubble.Rd
index 3f7e97a..fc46e75 100644
--- a/man/plotBarcodeBubble.Rd
+++ b/man/plotBarcodeBubble.Rd
@@ -27,7 +27,6 @@ Returns a bubbleplot of barcodes represented by proportion of total pool
 Generate proportional bubbleplots from raw count object with barcodes labelled above a specified threshold
 }
 \examples{
-data(test.counts)
-plotBarcodeBubble(test.counts, labels = TRUE, proportion.cutoff = 10)
-plotBarcodeBubble(test.counts, labels = FALSE, proportion.cutoff = 10)
+plotBarcodeBubble(test.dge$counts, labels = TRUE, proportion.cutoff = 10)
+plotBarcodeBubble(test.dge$counts, labels = FALSE, proportion.cutoff = 10)
 }
diff --git a/man/plotBarcodeCounts.Rd b/man/plotBarcodeCounts.Rd
index b36ee51..77942fb 100644
--- a/man/plotBarcodeCounts.Rd
+++ b/man/plotBarcodeCounts.Rd
@@ -20,8 +20,7 @@ Returns a plot of the read counts per barcode (row) in a data frame
 Simple plot of total read counts per barcode in library
 }
 \examples{
-data(test.counts)
-plotBarcodeCounts(test.counts)
-plotBarcodeCounts(test.counts, order = TRUE)
-plotBarcodeCounts(test.counts, order = TRUE, log10 = TRUE)
+plotBarcodeCounts(test.dge$counts)
+plotBarcodeCounts(test.dge$counts, order = TRUE)
+plotBarcodeCounts(test.dge$counts, order = TRUE, log10 = TRUE)
 }
diff --git a/man/plotBarcodeCumSum.Rd b/man/plotBarcodeCumSum.Rd
index 0659733..d6eff96 100644
--- a/man/plotBarcodeCumSum.Rd
+++ b/man/plotBarcodeCumSum.Rd
@@ -27,6 +27,5 @@ plotBarcodeCumSum
 Plot the cumulative sum of barcode cpm counts for a list of samples against and ordered by sample1.
 }
 \examples{
-data(test.counts)
-plotBarcodeCumSum(counts = test.counts, sample1 = 'T0-1', samples = c('T0-1','S9-1', 'S8-1'))
+plotBarcodeCumSum(counts = test.dge$counts, sample1 = 'T0-1', samples = c('T0-1','S9-1', 'S8-1'))
 }
diff --git a/man/plotBarcodeDistance.Rd b/man/plotBarcodeDistance.Rd
index def8151..cf29a26 100644
--- a/man/plotBarcodeDistance.Rd
+++ b/man/plotBarcodeDistance.Rd
@@ -30,6 +30,5 @@ Returns a heatmap of sample distances using desired clustering
 Plot sample distances between barcode sets / samples
 }
 \examples{
-test.mat <- matrix(rnorm(10*10,mean=0,sd=2), 10, 10)
-plotBarcodeDistance(test.mat)
+plotBarcodeDistance(test.dge$counts)
 }
diff --git a/man/plotBarcodeHeatmap.Rd b/man/plotBarcodeHeatmap.Rd
index febcf92..c65824b 100644
--- a/man/plotBarcodeHeatmap.Rd
+++ b/man/plotBarcodeHeatmap.Rd
@@ -4,16 +4,36 @@
 \alias{plotBarcodeHeatmap}
 \title{Plot barcode heatmap}
 \usage{
-plotBarcodeHeatmap(counts, N, name = "CPM", show_bc = FALSE)
+plotBarcodeHeatmap(
+  counts,
+  N,
+  name = "CPM",
+  show_bc = FALSE,
+  samples = NULL,
+  group = NULL,
+  col_annot = NULL,
+  discrete = F,
+  discrete_threshold = 1
+)
 }
 \arguments{
 \item{counts}{Dataframe containing cpm counts}
 
-\item{N}{String of sample 1 name (used to ranked barcode abundance)}
+\item{N}{Number of top barcodes per sample}
 
 \item{name}{String of the heatmap scale name}
 
 \item{show_bc}{Boolean to show barcode names on the heatmap}
+
+\item{samples}{Dataframe containing sample metadata sheet}
+
+\item{group}{metadata fields to annotate samples}
+
+\item{col_annot}{list of vectors assigning colours to each level of metadata}
+
+\item{discrete}{Boolean to show presence/absence of barcodes instead of abundance}
+
+\item{discrete_threshold}{Threshold for presence of barcode in samples}
 }
 \value{
 Returns a heatmap
@@ -29,6 +49,5 @@ plotBarcodeHeatmap
 Plot a heatmap of the N most abundant barcodes per sample
 }
 \examples{
-data(test.counts)
-plotBarcodeHeatmap(test.counts, 10,'Counts',FALSE)
+plotBarcodeHeatmap(counts = cpm(test.dge$counts),N = 5,show_bc = TRUE,samples = test.dge$samples)
 }
diff --git a/man/plotBarcodeHistogram.Rd b/man/plotBarcodeHistogram.Rd
index 9d38020..f3e75e1 100644
--- a/man/plotBarcodeHistogram.Rd
+++ b/man/plotBarcodeHistogram.Rd
@@ -27,6 +27,5 @@ Returns a barcode histogram plot of barcodes represented by proportion of total
 Generate stacked barcode plots showing proportion from raw count object.
 }
 \examples{
-data(test.counts)
-plotBarcodeHistogram(test.counts, sample = "T0-1", top = 10, name = "Barcode Histogram")
+plotBarcodeHistogram(test.dge$counts, sample = "T0-1", top = 10, name = "Barcode Histogram")
 }
diff --git a/man/plotBarcodePCA.Rd b/man/plotBarcodePCA.Rd
index c50fbbf..20c299e 100644
--- a/man/plotBarcodePCA.Rd
+++ b/man/plotBarcodePCA.Rd
@@ -40,6 +40,5 @@ plotBarcodePCA
 Plot the first two principal components of the barcode dataset
 }
 \examples{
-data(test.dge)
-plotBarcodePCA(test.dge, intgroup = "group", ntop = 500, returnData = FALSE, batch = NULL)
+plotBarcodePCA(test.dge, intgroup = "Treatment", ntop = 500, returnData = FALSE, batch = NULL)
 }
diff --git a/man/plotBarcodeTimeseries.Rd b/man/plotBarcodeTimeseries.Rd
index 2bb185e..069fe6e 100644
--- a/man/plotBarcodeTimeseries.Rd
+++ b/man/plotBarcodeTimeseries.Rd
@@ -23,5 +23,5 @@ Generate proportional timeseries plot from raw / normalised barcode count object
 }
 \examples{
 data(test.counts)
-plotBarcodeTimeseries(test.counts[,1:4], name = "Proportional Timeseries Plot", seed = 5, top = 10)
+plotBarcodeTimeseries(test.dge$counts[,1:4], name = "Proportional Timeseries Plot", seed = 5)
 }
diff --git a/man/plotCellsInClusters.Rd b/man/plotCellsInClusters.Rd
new file mode 100644
index 0000000..15b2a5f
--- /dev/null
+++ b/man/plotCellsInClusters.Rd
@@ -0,0 +1,40 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotCellsinClusters.R
+\name{plotCellsInClusters}
+\alias{plotCellsInClusters}
+\title{Plot cells per ident class}
+\usage{
+plotCellsInClusters(
+  sc.obj,
+  group = NULL,
+  factor = NULL,
+  idents = NULL,
+  plot.pct = T,
+  plot = T
+)
+}
+\arguments{
+\item{sc.obj}{single cell object in Seurat or SingleCellExperiment format containing idents and group metadata}
+
+\item{group}{a column of metadata}
+
+\item{factor}{a level of group to plot per level of idents}
+
+\item{idents}{a column of metadata defining the cluster identities of each cell. default = "seurat_clusters"}
+
+\item{plot.pct}{Logical. Plot percentages (TRUE) or raw numbers (FALSE). default = TRUE}
+
+\item{plot}{Logical. Plot or return raw data. default = TRUE}
+}
+\value{
+Returns a histogram or underlying plot data
+}
+\description{
+Takes a single cell object, a grouping variable, a factor within the group to test, 
+and an ident class (i.e. clusters). Plots percentage or raw number of cells within factor
+present per level of ident (i.e. per cluster)
+}
+\details{
+Plot number or percentage of a group per level of ident in a single
+cell object
+}
diff --git a/man/plotCellsPerGroup.Rd b/man/plotCellsPerGroup.Rd
new file mode 100644
index 0000000..b6032d8
--- /dev/null
+++ b/man/plotCellsPerGroup.Rd
@@ -0,0 +1,45 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotCellsPerGroup.R
+\name{plotCellsPerGroup}
+\alias{plotCellsPerGroup}
+\title{Plot of cells per barcode}
+\usage{
+plotCellsPerGroup(
+  sc.obj = NULL,
+  group = NULL,
+  order = TRUE,
+  trans = NULL,
+  threshold = 100,
+  plot = TRUE,
+  label = TRUE
+)
+}
+\arguments{
+\item{sc.obj}{single cell object in Seurat or SingleCellExperiment format containing group metadata}
+
+\item{group}{a column of metadata in sc.obj}
+
+\item{order}{Logical. Rank order levels of group by cell number}
+
+\item{trans}{From ggplot2. For continuous scales, the name of a transformation object or the object itself.}
+
+\item{threshold}{threshold number of cells above which labels for group levels will appear}
+
+\item{plot}{Logical. Plot results or return data.}
+
+\item{label}{Logical. Label group levels above cell number threshold. if ggrepel is installed will use geom_text_repel
+instead of geom_text}
+}
+\value{
+Returns a plot of cell number by barcode test results or underlying plot data
+}
+\description{
+Takes a single cell object, a grouping variable, a factor within the group to test, 
+and an ident class (i.e. clusters). Per level of ident performs hypergeometric testing
+for enrichment of group factor
+}
+\details{
+plotCellsPerGroup
+
+Plots number of cells for each detected barcode in a single cell dataset
+}
diff --git a/man/plotClusterEnrichment.Rd b/man/plotClusterEnrichment.Rd
new file mode 100644
index 0000000..4865f13
--- /dev/null
+++ b/man/plotClusterEnrichment.Rd
@@ -0,0 +1,45 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotClusterEnrichment.R
+\name{plotClusterEnrichment}
+\alias{plotClusterEnrichment}
+\title{Hypergeometric test for cluster enrichment}
+\usage{
+plotClusterEnrichment(
+  sc.obj = NULL,
+  group = NULL,
+  factor = NULL,
+  idents = "seurat_clusters",
+  threshold = 0.01,
+  order = TRUE,
+  plot = TRUE
+)
+}
+\arguments{
+\item{sc.obj}{single cell object in Seurat or SingleCellExperiment format containing idents and group metadata}
+
+\item{group}{a column of metadata}
+
+\item{factor}{a level of group to test for enrichment per level of ident}
+
+\item{idents}{a column of metadata defining the cluster identities of each cell. default = "seurat_clusters"}
+
+\item{threshold}{P-value threshold for phyper test. default = 0.01}
+
+\item{order}{Logical. Order levels of idents in plot by -log10 P-value}
+
+\item{plot}{Logical. Plot hypergeometric test results or return plot data.}
+}
+\value{
+Returns a histogram of hypergeometric test results or underlying plot data
+}
+\description{
+Takes a single cell object, a grouping variable, a factor within the group to test, 
+and an ident class (i.e. clusters). Per level of ident performs hypergeometric testing
+for enrichment of group factor
+}
+\details{
+plotClusterEnrichment
+
+Hypergeometric test for enrichment of specific classes of cells in 
+single cell RNA-seq clusters
+}
diff --git a/man/plotDetectedBarcodes.Rd b/man/plotDetectedBarcodes.Rd
index 9380086..2d95541 100644
--- a/man/plotDetectedBarcodes.Rd
+++ b/man/plotDetectedBarcodes.Rd
@@ -33,7 +33,6 @@ Returns a histogram plot of the number of detected barcodes per sample.
 Plot the total number of barcodes detected in a sample
 }
 \examples{
-data(test.dge)
 plotDetectedBarcodes(test.dge, percentile = .95)
 plotDetectedBarcodes(test.dge, plot = FALSE)
 }
diff --git a/man/plotDivIndexes.Rd b/man/plotDivIndexes.Rd
new file mode 100644
index 0000000..fd8a2a0
--- /dev/null
+++ b/man/plotDivIndexes.Rd
@@ -0,0 +1,39 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotDivIndexes.R
+\name{plotDivIndexes}
+\alias{plotDivIndexes}
+\title{Plot diversity indices across barcode samples}
+\usage{
+plotDivIndexes(
+  counts,
+  div = NULL,
+  metric = "shannon",
+  type = "bar",
+  group = NULL
+)
+}
+\arguments{
+\item{counts}{dataframe of raw or normalised counts with samples as columns and observations/barcodes as rows}
+
+\item{div}{dataframe of diversity metrics as columns and samples as rows}
+
+\item{metric}{diversity metric to plot. one of "shannon", "simpson", "invsimpson" or "gini"}
+
+\item{type}{plot as bar graph or point}
+
+\item{group}{a character vector of containing grouping information. Must be equal the number of columns of counts. Can pass a metadata column from DGEList object.}
+}
+\value{
+Returns a plot of calculated diversity index per sample
+}
+\description{
+Plots a dataframe of diversity indices per sample
+}
+\details{
+plotDivIndexes
+
+Plots common diversity indices per sample
+}
+\examples{
+plotDivIndexes(counts = test.dge$counts)
+}
diff --git a/man/plotMetrics.Rd b/man/plotMetrics.Rd
new file mode 100644
index 0000000..f0eeb07
--- /dev/null
+++ b/man/plotMetrics.Rd
@@ -0,0 +1,40 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plotMetrics.R
+\name{plotMetrics}
+\alias{plotMetrics}
+\title{Violin plot of selected metric per group variable}
+\usage{
+plotMetrics(
+  sc.obj = NULL,
+  group = NULL,
+  trans = NULL,
+  factor = NULL,
+  threshold = 100,
+  plot = TRUE
+)
+}
+\arguments{
+\item{sc.obj}{single cell object in Seurat or SingleCellExperiment format containing group metadata}
+
+\item{group}{a column of metadata in sc.obj containing grouping information}
+
+\item{trans}{From ggplot2. For continuous scales, the name of a transformation object or the object itself.}
+
+\item{factor}{a metadata field to plot per level of group}
+
+\item{threshold}{threshold number of cells per level of group to plot}
+
+\item{plot}{Logical. Plot results or return data.}
+}
+\value{
+Returns a plot of cell number by barcode test results or underlying plot data
+}
+\description{
+Takes a single cell object, a grouping variable and a metadata variable.
+Plots distribution of factor per level of group with total number of cells above threshold
+}
+\details{
+plotMetrics
+
+Plots metric distribution for selected groups in a single cell dataset
+}
diff --git a/man/plotOrderedBubble.Rd b/man/plotOrderedBubble.Rd
index 263ecef..ea45848 100644
--- a/man/plotOrderedBubble.Rd
+++ b/man/plotOrderedBubble.Rd
@@ -9,8 +9,14 @@ plotOrderedBubble(
   labels = T,
   name = "Proportional Bubble Plot",
   orderSample = NULL,
+  samples = NULL,
+  group = NULL,
+  displaySamples = NULL,
+  displayBarcodes = NULL,
   proportion.cutoff = 10,
-  colorDominant = FALSE
+  colorDominant = FALSE,
+  filterLow = FALSE,
+  filter.cutoff = 0.001
 )
 }
 \arguments{
@@ -22,9 +28,21 @@ plotOrderedBubble(
 
 \item{orderSample}{name of sample to order by}
 
+\item{samples}{Dataframe containing sample metadata sheet}
+
+\item{group}{metadata field to annotate samples on bubble plot}
+
+\item{displaySamples}{vector of samples to display - keep the order of vector}
+
+\item{displayBarcodes}{vector of barcodes to display}
+
 \item{proportion.cutoff}{barcodes represented at a percentage within any sample above this threshold will be labelled}
 
 \item{colorDominant}{only color clones with frequency above proportion.cutoff. Others colored grey}
+
+\item{filterLow}{Boolean to filter low barcodes in orderSample}
+
+\item{filter.cutoff}{barcodes below this threshold in orderSample will be filtered in all samples}
 }
 \value{
 Returns a bubbleplot of barcodes represented by proportion of total pool
@@ -33,6 +51,5 @@ Returns a bubbleplot of barcodes represented by proportion of total pool
 Generate ordered proportional bubbleplots from raw count object with barcodes labelled above a specified threshold
 }
 \examples{
-data(test.counts)
-plotOrderedBubble(test.counts, orderSample = "T0-1")
+plotOrderedBubble(test.dge$counts, orderSample = "T0-1")
 }
diff --git a/man/plotReadCounts.Rd b/man/plotReadCounts.Rd
index 25e20e6..c98fd3f 100644
--- a/man/plotReadCounts.Rd
+++ b/man/plotReadCounts.Rd
@@ -30,7 +30,6 @@ Returns a plot of the read counts per column (sample) in a data frame
 Simple plot of total read counts per sample
 }
 \examples{
-data(test.counts)
-plotReadCounts(test.dge$counts, group = test.dge$samples$Group)
+plotReadCounts(test.dge$counts, group = test.dge$samples$Treatment)
 
 }
diff --git a/man/processBarcodeLibrary.Rd b/man/processBarcodeLibrary.Rd
index 61bf4a5..d23ca95 100644
--- a/man/processBarcodeLibrary.Rd
+++ b/man/processBarcodeLibrary.Rd
@@ -29,7 +29,3 @@ returns data frame containing barcode and read count in reference
 \description{
 process barcode reference file from raw sequencing datasets
 }
-\examples{
-load(system.file("extdata", "test_raw_lib.rda", package = "bartools"))
-processBarcodeLibrary(file = test.raw.lib, samplename = "Barcode", outdir = tempdir())
-}
diff --git a/man/proportionalBubbleplot.Rd b/man/proportionalBubbleplot.Rd
new file mode 100644
index 0000000..33a91e5
--- /dev/null
+++ b/man/proportionalBubbleplot.Rd
@@ -0,0 +1,31 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/proportionalBubbleplot.R
+\name{proportionalBubbleplot}
+\alias{proportionalBubbleplot}
+\title{proportionalBubbleplot}
+\usage{
+proportionalBubbleplot(
+  counts.obj,
+  labels = TRUE,
+  proportion.cutoff = 10,
+  name = "Proportional Bubble Plot"
+)
+}
+\arguments{
+\item{counts.obj}{dataframe containing raw counts of barcodes. assumes barcodes as rownames.}
+
+\item{labels}{Boolean. print barcode labels?}
+
+\item{proportion.cutoff}{barcodes represented at a percentage within any sample above this threshold will be labelled}
+
+\item{name}{desired plot title}
+}
+\value{
+Returns a bubbleplot of barcodes represented by proportion of total pool
+}
+\description{
+Generate proportional bubbleplots from raw count object with barcodes labelled above a specified threshold
+}
+\examples{
+proportionalBubbleplot(test.dge$counts, name = "Proportional Bubble Plot", proportion.cutoff = 10)
+}
diff --git a/man/test.sce.Rd b/man/test.sce.Rd
new file mode 100644
index 0000000..d416a0c
--- /dev/null
+++ b/man/test.sce.Rd
@@ -0,0 +1,17 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.R
+\docType{data}
+\name{test.sce}
+\alias{test.sce}
+\title{Test barcode SCE object}
+\format{
+A SCE object with 100 rows and 100 variables:
+}
+\usage{
+test.sce
+}
+\description{
+A SingleCellExperiment object containing single cell RNA-seq data for 100 cells
+and 100 features
+}
+\keyword{datasets}
diff --git a/man/thresholdCounts.Rd b/man/thresholdCounts.Rd
index e0b2c21..736aaf9 100644
--- a/man/thresholdCounts.Rd
+++ b/man/thresholdCounts.Rd
@@ -4,22 +4,35 @@
 \alias{thresholdCounts}
 \title{Threshold counts}
 \usage{
-thresholdCounts(df, threshold = 20, plot = FALSE)
+thresholdCounts(
+  dge,
+  threshold = 10,
+  type = "absolute",
+  min.samps = 1,
+  plot = FALSE,
+  group = NULL
+)
 }
 \arguments{
-\item{df}{Dataframe to be thresholded.}
+\item{dge}{DGEList object to be thresholded.}
 
-\item{threshold}{The threshold to use. Rows with count below this will be removed.}
+\item{threshold}{The threshold to use. If type = "relative", must a float between 0 & 1. Default = 10}
 
-\item{plot}{Logical. Draw plots of dataset?}
+\item{type}{Threshold type to use. Must be one of "absolute" or "relative". Default = "absolute".}
+
+\item{min.samps}{Minimum number of samples a barcode must meet threshold to remain in dataset. Default = 1.}
+
+\item{plot}{Logical. Draw plots of dataset? Default = F}
+
+\item{group}{DGEList metadata field to color samples by}
 }
 \value{
-Returns a thresholded data-frame
+Returns a filtered DGEList object.
 }
 \description{
-Threshold dataframe to a given level and return number of barcodes meeting threshold in each
-sample.
+Filter barcodes meeting a given absolute (total read count) or relative (proportion based) abundance level
+Optionally plot number of barcodes detected using this threshold in each sample.
 }
 \examples{
-thresholdCounts(test.counts, threshold = 20, plot = FALSE)
+thresholdCounts(test.dge, type = "absolute", threshold = 10, plot = FALSE)
 }