diff --git a/DESCRIPTION b/DESCRIPTION
index 07de2668b474820f17a9a6a341c5ccd35aaac81e..f67bea7680a8ef7e976dad98373cf8c596a02897 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
Package: splatter
Type: Package
Title: Simple Simulation of Single-cell RNA Sequencing Data
-Version: 1.3.4.9000
-Date: 2018-04-19
+Version: 1.3.5
+Date: 2018-04-25
Author: Luke Zappia
Authors@R:
c(person("Luke", "Zappia", role = c("aut", "cre"),
diff --git a/NEWS.md b/NEWS.md
index 31dca6fdec3e435356e537daaee67d7146b62c92..7f7748bddcaa72974bc6044c4211b47615a59e67 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,8 @@
+## Version 1.3.4 (2018-04-25)
+
+* Replace dropout.present with dropout.type in SplatParams
+ * Allows users to set dropout by experiment, batch, group or cell
+
## Version 1.3.4 (2018-04-19)
* Add option to use a normal distribution for library sizes in Splat simulations
diff --git a/R/splat-estimate.R b/R/splat-estimate.R
index ed2b6e8bd4cc61663af104356cb648d02ed5aa1e..5af464671d321fa45e8ef299285995b155cc2b78 100644
--- a/R/splat-estimate.R
+++ b/R/splat-estimate.R
@@ -230,6 +230,8 @@ splatEstBCV <- function(counts, params) {
#' Logistic function parameters are estimated by fitting a logistic function
#' to the relationship between log2 mean gene expression and the proportion of
#' zeros in each gene. See \code{\link[stats]{nls}} for details of fitting.
+#' Note this is done on the experiment level, more granular (eg. group or cell)
+#' level dropout is not estimated.
#'
# #' The
# #' presence of dropout is determined by comparing the observed number of zeros
diff --git a/docs/articles/index.html b/docs/articles/index.html
index 578c4208edba5d314f24cf6b33ebeadfadd089e9..088ab52f0cea0b8d22450a42a0b6a9a80616136b 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -96,7 +96,7 @@
</header>
<div class="page-header">
- <h1>Articles <small>version 1.3.4</small></h1>
+ <h1>Articles <small>version 1.3.5</small></h1>
</div>
<div class="row">
diff --git a/docs/articles/splatter.html b/docs/articles/splatter.html
index 9d304865aa487624ff8167d50b3938da7d24b020..7602e9346bd996ab2c0f23b14a0c72a68e27efee 100644
--- a/docs/articles/splatter.html
+++ b/docs/articles/splatter.html
@@ -76,7 +76,7 @@
<h1>Introduction to Splatter</h1>
<h4 class="author">Luke Zappia</h4>
- <h4 class="date">2018-04-19</h4>
+ <h4 class="date">2018-04-25</h4>
</div>
@@ -174,7 +174,7 @@
<a class="sourceLine" id="cb34-3" data-line-number="3">params <-<span class="st"> </span><span class="kw"><a href="../reference/splatEstimate.html">splatEstimate</a></span>(sc_example_counts)</a></code></pre></div>
<pre><code>## NOTE: Library sizes have been found to be normally distributed instead of log-normal. You may want to check this is correct.</code></pre>
<div class="sourceCode" id="cb36"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb36-1" data-line-number="1"><span class="co"># Simulate data using estimated parameters</span></a>
-<a class="sourceLine" id="cb36-2" data-line-number="2">sim <-<span class="st"> </span><span class="kw"><a href="../reference/splatSimulate.html">splatSimulate</a></span>(params, <span class="dt">dropout.present =</span> <span class="ot">FALSE</span>)</a></code></pre></div>
+<a class="sourceLine" id="cb36-2" data-line-number="2">sim <-<span class="st"> </span><span class="kw"><a href="../reference/splatSimulate.html">splatSimulate</a></span>(params)</a></code></pre></div>
<pre><code>## Getting parameters...</code></pre>
<pre><code>## Creating simulation object...</code></pre>
<pre><code>## Simulating library sizes...</code></pre>
@@ -285,7 +285,7 @@
<strong>Dropout parameters</strong>
<ul>
<li>
-<code>dropout.present</code> - Logical. Whether to simulate dropout.</li>
+<code>dropout.type</code> - Type of dropout to simulate.</li>
<li>
<code>dropout.mid</code> - Midpoint parameter for the dropout logistic function.</li>
<li>
@@ -483,7 +483,7 @@
<h1 class="hasAnchor">
<a href="#simulating-counts" class="anchor"></a>Simulating counts</h1>
<p>Once we have a set of parameters we are happy with we can use <code>splatSimulate</code> to simulate counts. If we want to make small adjustments to the parameters we can provide them as additional arguments, alternatively if we don’t supply any parameters the defaults will be used:</p>
-<div class="sourceCode" id="cb67"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb67-1" data-line-number="1">sim <-<span class="st"> </span><span class="kw"><a href="../reference/splatSimulate.html">splatSimulate</a></span>(params, <span class="dt">nGenes =</span> <span class="dv">1000</span>, <span class="dt">dropout.present =</span> <span class="ot">FALSE</span>, <span class="dt">seed =</span> <span class="dv">0</span>)</a></code></pre></div>
+<div class="sourceCode" id="cb67"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb67-1" data-line-number="1">sim <-<span class="st"> </span><span class="kw"><a href="../reference/splatSimulate.html">splatSimulate</a></span>(params, <span class="dt">nGenes =</span> <span class="dv">1000</span>)</a></code></pre></div>
<pre><code>## Getting parameters...</code></pre>
<pre><code>## Creating simulation object...</code></pre>
<pre><code>## Simulating library sizes...</code></pre>
@@ -507,45 +507,45 @@
<div class="sourceCode" id="cb78"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb78-1" data-line-number="1"><span class="co"># Access the counts</span></a>
<a class="sourceLine" id="cb78-2" data-line-number="2"><span class="kw">counts</span>(sim)[<span class="dv">1</span><span class="op">:</span><span class="dv">5</span>, <span class="dv">1</span><span class="op">:</span><span class="dv">5</span>]</a></code></pre></div>
<pre><code>## Cell1 Cell2 Cell3 Cell4 Cell5
-## Gene1 16 0 0 1232 0
-## Gene2 77 0 293 7 0
-## Gene3 323 52 5 0 1
-## Gene4 0 0 7 3 0
-## Gene5 278 0 14 55 1</code></pre>
+## Gene1 0 4 6 0 0
+## Gene2 0 6 0 1 0
+## Gene3 0 0 0 0 0
+## Gene4 2 0 0 0 0
+## Gene5 48 515 97 176 11</code></pre>
<div class="sourceCode" id="cb80"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb80-1" data-line-number="1"><span class="co"># Information about genes</span></a>
<a class="sourceLine" id="cb80-2" data-line-number="2"><span class="kw">head</span>(<span class="kw">rowData</span>(sim))</a></code></pre></div>
<pre><code>## DataFrame with 6 rows and 4 columns
-## Gene BaseGeneMean OutlierFactor GeneMean
-## <factor> <numeric> <numeric> <numeric>
-## 1 Gene1 680.726908939431 1 680.726908939431
-## 2 Gene2 29.6384151850527 1 29.6384151850527
-## 3 Gene3 9.58778523489509 1 9.58778523489509
-## 4 Gene4 2.83976742238589 1 2.83976742238589
-## 5 Gene5 150.071547242578 1 150.071547242578
-## 6 Gene6 66.0478747990155 1 66.0478747990155</code></pre>
+## Gene BaseGeneMean OutlierFactor GeneMean
+## <factor> <numeric> <numeric> <numeric>
+## 1 Gene1 2.62549353556827 1 2.62549353556827
+## 2 Gene2 4.81434700182375 1 4.81434700182375
+## 3 Gene3 0.495916446978038 1 0.495916446978038
+## 4 Gene4 34.1648904749076 1 34.1648904749076
+## 5 Gene5 24.7045533636413 1 24.7045533636413
+## 6 Gene6 250.903326326503 1 250.903326326503</code></pre>
<div class="sourceCode" id="cb82"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb82-1" data-line-number="1"><span class="co"># Information about cells</span></a>
<a class="sourceLine" id="cb82-2" data-line-number="2"><span class="kw">head</span>(<span class="kw">colData</span>(sim))</a></code></pre></div>
<pre><code>## DataFrame with 6 rows and 3 columns
## Cell Batch ExpLibSize
## <factor> <character> <numeric>
-## Cell1 Cell1 Batch1 681471.700471143
-## Cell2 Cell2 Batch1 313386.003338354
-## Cell3 Cell3 Batch1 696954.252459665
-## Cell4 Cell4 Batch1 683666.296838061
-## Cell5 Cell5 Batch1 484986.516482731
-## Cell6 Cell6 Batch1 32266.4313600409</code></pre>
+## Cell1 Cell1 Batch1 954966.951755734
+## Cell2 Cell2 Batch1 405289.957543236
+## Cell3 Cell3 Batch1 584037.74996489
+## Cell4 Cell4 Batch1 602796.965710327
+## Cell5 Cell5 Batch1 87301.1571607906
+## Cell6 Cell6 Batch1 470868.325224977</code></pre>
<div class="sourceCode" id="cb84"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb84-1" data-line-number="1"><span class="co"># Gene by cell matrices</span></a>
<a class="sourceLine" id="cb84-2" data-line-number="2"><span class="kw">names</span>(<span class="kw">assays</span>(sim))</a></code></pre></div>
<pre><code>## [1] "BatchCellMeans" "BaseCellMeans" "BCV" "CellMeans"
## [5] "TrueCounts" "counts"</code></pre>
<div class="sourceCode" id="cb86"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb86-1" data-line-number="1"><span class="co"># Example of cell means matrix</span></a>
<a class="sourceLine" id="cb86-2" data-line-number="2"><span class="kw">assays</span>(sim)<span class="op">$</span>CellMeans[<span class="dv">1</span><span class="op">:</span><span class="dv">5</span>, <span class="dv">1</span><span class="op">:</span><span class="dv">5</span>]</a></code></pre></div>
-<pre><code>## Cell1 Cell2 Cell3 Cell4 Cell5
-## Gene1 1.996549e+01 5.070084e-03 0.2151287 1.246817e+03 2.348151e-03
-## Gene2 6.824467e+01 6.878904e-04 270.2654016 5.265928e+00 1.081630e+00
-## Gene3 3.299146e+02 5.260857e+01 2.6861953 1.121680e-03 2.510321e+00
-## Gene4 2.971991e-04 5.295532e-11 5.6812428 1.776702e+00 1.525443e-07
-## Gene5 3.066060e+02 2.441931e-11 18.0058655 4.726581e+01 6.353592e-01</code></pre>
+<pre><code>## Cell1 Cell2 Cell3 Cell4 Cell5
+## Gene1 5.858361e-03 2.084916e+00 1.181249e+01 5.295042e-04 3.916082e-01
+## Gene2 5.880603e-10 1.013736e+01 1.861441e-04 3.629131e-01 1.743725e-05
+## Gene3 1.673555e-09 8.432645e-04 9.257897e-06 2.886216e-01 4.932245e-21
+## Gene4 6.088198e-01 1.685011e-06 1.528356e-17 2.186295e-01 3.857391e-02
+## Gene5 4.210456e+01 5.108598e+02 9.006138e+01 1.578927e+02 1.056544e+01</code></pre>
<p>An additional (big) advantage of outputting a <code>SingleCellExperiment</code> is that we get immediate access to other analysis packages, such as the plotting functions in <code>scater</code>. For example we can make a PCA plot:</p>
<div class="sourceCode" id="cb88"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb88-1" data-line-number="1"><span class="co"># Use scater to calculate logcounts</span></a>
<a class="sourceLine" id="cb88-2" data-line-number="2">sim <-<span class="st"> </span><span class="kw"><a href="http://www.rdocumentation.org/packages/scater/topics/normalize">normalise</a></span>(sim)</a></code></pre></div>
diff --git a/docs/articles/splatter_files/figure-html/pca-1.png b/docs/articles/splatter_files/figure-html/pca-1.png
index fdd505da9563045b2f73faa71f18e54887026dfb..fcb82f525886e4647c2e86db4849d024b66fe403 100644
Binary files a/docs/articles/splatter_files/figure-html/pca-1.png and b/docs/articles/splatter_files/figure-html/pca-1.png differ
diff --git a/docs/news/index.html b/docs/news/index.html
index 4715b61bced570550a1ba48300f23528343bc898..b7ebc7ec88621fe2edcd08cbcbd6a8a4ed0a2ea9 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -104,6 +104,16 @@
<div class="contents">
<div class="section level2">
+<h2>Version 1.3.4 (2018-04-25)</h2>
+<ul>
+<li>Replace dropout.present with dropout.type in SplatParams
+<ul>
+<li>Allows users to set dropout by experiment, batch, group or cell</li>
+</ul>
+</li>
+</ul>
+</div>
+ <div class="section level2">
<h2>Version 1.3.4 (2018-04-19)</h2>
<ul>
<li>Add option to use a normal distribution for library sizes in Splat simulations</li>
@@ -121,6 +131,16 @@
<li>Add option to use a normal distribution for library sizes in Splat simulations</li>
</ul>
</div>
+<div class="section level3">
+<h3>Version 1.3.3.9000 (2018-04-12)</h3>
+<ul>
+<li>Replace dropout.present with dropout.type in SplatParams
+<ul>
+<li>Allows more control over dropout.mid and dropout.shape</li>
+</ul>
+</li>
+</ul>
+</div>
</div>
<div class="section level2">
<h2>Version 1.3.3 (2018-03-27)</h2>
@@ -478,6 +498,7 @@
<div id="tocnav">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
+ <li><a href="#NA">1.3.4</a></li>
<li><a href="#NA">1.3.4</a></li>
<li><a href="#NA">1.3.3</a></li>
<li><a href="#NA">1.3.2</a></li>
diff --git a/docs/reference/SplatParams.html b/docs/reference/SplatParams.html
index 26480caee4e0e0771240770bf88d7b390a241e14..1734151e69507c1be5cf17fcc20a064dffab01ec 100644
--- a/docs/reference/SplatParams.html
+++ b/docs/reference/SplatParams.html
@@ -171,8 +171,12 @@
chi-squared distribution.</p></dd>
</dl></p></dd>
<dt><em>Dropout parameters</em></dt><dd><p><dl class='dl-horizontal'>
- <dt><code>dropout.present</code></dt><dd><p>Logical. Whether to simulate
- dropout.</p></dd>
+ <dt><code>dropout.type</code></dt><dd><p>The type of dropout to simulate.
+ "none" indicates no dropout, "experiment" is global dropout using
+ the same parameters for every cell, "batch" uses the same
+ parameters for every cell in each batch, "group" uses the same
+ parameters for every cell in each groups and "cell" uses a
+ different set of parameters for each cell.</p></dd>
<dt><code>dropout.mid</code></dt><dd><p>Midpoint parameter for the dropout
logistic function.</p></dd>
<dt><code>dropout.shape</code></dt><dd><p>Shape parameter for the dropout
diff --git a/docs/reference/addGeneLengths.html b/docs/reference/addGeneLengths.html
index 56f4c47975253f2d313d6755e1785bbedd01e335..b43634746f849c4c71de9876f98d2261b0cbc780 100644
--- a/docs/reference/addGeneLengths.html
+++ b/docs/reference/addGeneLengths.html
@@ -154,14 +154,14 @@ vector.</p>
<pre class="examples"><div class='input'><span class='co'># Default generate method</span>
<span class='no'>sce</span> <span class='kw'><-</span> <span class='fu'><a href='simpleSimulate.html'>simpleSimulate</a></span>()</div><div class='output co'>#> <span class='message'>Simulating means...</span></div><div class='output co'>#> <span class='message'>Simulating counts...</span></div><div class='output co'>#> <span class='message'>Creating final dataset...</span></div><div class='input'><span class='no'>sce</span> <span class='kw'><-</span> <span class='fu'>addGeneLengths</span>(<span class='no'>sce</span>)
<span class='fu'>head</span>(<span class='fu'>rowData</span>(<span class='no'>sce</span>))</div><div class='output co'>#> DataFrame with 6 rows and 3 columns
-#> Gene GeneMean Length
-#> <factor> <numeric> <numeric>
-#> 1 Gene1 0.26662904681126 1135
-#> 2 Gene2 3.22843622430885 6836
-#> 3 Gene3 0.747825116595176 3205
-#> 4 Gene4 0.0237206245029356 1427
-#> 5 Gene5 0.0901336217761832 4777
-#> 6 Gene6 2.1010781020721 1065</div><div class='input'># Sample method (human coding genes)
+#> Gene GeneMean Length
+#> <factor> <numeric> <numeric>
+#> 1 Gene1 3.19721697566766 428
+#> 2 Gene2 0.316692135258865 2948
+#> 3 Gene3 2.90867080625693 1507
+#> 4 Gene4 7.5357203351493 6034
+#> 5 Gene5 5.92953185619191 1713
+#> 6 Gene6 3.78237895789214 2926</div><div class='input'># Sample method (human coding genes)
</div><span class='co'># NOT RUN {</span>
<span class='fu'>library</span>(<span class='no'>TxDb.Hsapiens.UCSC.hg19.knownGene</span>)
<span class='fu'>library</span>(<span class='no'>GenomicFeatures</span>)
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 3f5b17a89377cd5b5e8d556d740ad881e7c8cdd1..37647c51c2c57d024a4992825c4e0ac146c83a31 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -100,7 +100,7 @@
<div class="page-header">
<h1>
Reference
- <small>version 1.3.4</small>
+ <small>version 1.3.5</small>
</h1>
</div>
diff --git a/docs/reference/lunEstimate.html b/docs/reference/lunEstimate.html
index 09b6b464402fa329cf65f6b880f5fd6106068f87..797828822a980d4dcad7c8486bb48fd169391ec1 100644
--- a/docs/reference/lunEstimate.html
+++ b/docs/reference/lunEstimate.html
@@ -140,12 +140,8 @@ for more details on the parameters.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># Load example data</span>
-<span class='fu'>library</span>(<span class='no'>scater</span>)</div><div class='output co'>#> <span class='message'>Loading required package: ggplot2</span></div><div class='output co'>#> <span class='message'></span>
-#> <span class='message'>Attaching package: ‘scater’</span></div><div class='output co'>#> <span class='message'>The following object is masked from ‘package:S4Vectors’:</span>
-#> <span class='message'></span>
-#> <span class='message'> rename</span></div><div class='output co'>#> <span class='message'>The following object is masked from ‘package:stats’:</span>
-#> <span class='message'></span>
-#> <span class='message'> filter</span></div><div class='input'><span class='fu'>data</span>(<span class='st'>"sc_example_counts"</span>)
+<span class='fu'>library</span>(<span class='no'>scater</span>)
+<span class='fu'>data</span>(<span class='st'>"sc_example_counts"</span>)
<span class='no'>params</span> <span class='kw'><-</span> <span class='fu'>lunEstimate</span>(<span class='no'>sc_example_counts</span>)
<span class='no'>params</span></div><div class='output co'>#> A Params object of class LunParams
@@ -153,7 +149,7 @@ for more details on the parameters.</p>
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 2000 40 457996
+#> 2000 40 33804
#>
#> 9 additional parameters
#>
diff --git a/docs/reference/mfaEstimate.html b/docs/reference/mfaEstimate.html
index 7d344b65944267e3c811102c9e132206025a2530..df646e1540d457182a1f2e52462d3f39853b936e 100644
--- a/docs/reference/mfaEstimate.html
+++ b/docs/reference/mfaEstimate.html
@@ -150,7 +150,7 @@ details on the parameters.</p>
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 2000 40 457996
+#> 2000 40 33804
#>
#> 4 additional parameters
#>
diff --git a/docs/reference/phenoEstimate.html b/docs/reference/phenoEstimate.html
index 1a75c9adf0f619e52727207dcfb56ceedd110131..b19c0960da87d610ce9b234b593019f1696d6a38 100644
--- a/docs/reference/phenoEstimate.html
+++ b/docs/reference/phenoEstimate.html
@@ -151,7 +151,7 @@ See <code><a href='PhenoParams.html'>PhenoParams</a></code> for more details on
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 2000 40 457996
+#> 2000 40 33804
#>
#> 4 additional parameters
#>
diff --git a/docs/reference/setParam.html b/docs/reference/setParam.html
index 5824593598294e89dc832c5c5b3ae49b851d8289..7b675e5a1c4a0f200b12a690b81991ccc7aadf61 100644
--- a/docs/reference/setParam.html
+++ b/docs/reference/setParam.html
@@ -160,7 +160,7 @@
#>
#> Global:
#> (GENES) (Cells) [Seed]
-#> 100 100 457996
+#> 100 100 33804
#>
#> 3 additional parameters
#>
diff --git a/docs/reference/setParams.html b/docs/reference/setParams.html
index 7f2abf8eefd86b24f935a59fcd37295b627653c9..24447c4954327481e77dfdb45aa700c56d22d346 100644
--- a/docs/reference/setParams.html
+++ b/docs/reference/setParams.html
@@ -146,7 +146,7 @@ them manually), see examples.</p>
#>
#> Global:
#> (Genes) (Cells) [Seed]
-#> 10000 100 457996
+#> 10000 100 33804
#>
#> 3 additional parameters
#>
@@ -164,7 +164,7 @@ them manually), see examples.</p>
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 1000 50 457996
+#> 1000 50 33804
#>
#> 3 additional parameters
#>
@@ -182,7 +182,7 @@ them manually), see examples.</p>
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 1000 50 457996
+#> 1000 50 33804
#>
#> 3 additional parameters
#>
diff --git a/docs/reference/simpleEstimate.html b/docs/reference/simpleEstimate.html
index 07b9e52f5852b059a81d034b2d32b9ade6f6a269..548b300cb20ce4389f0e8882d7388b9adb581165 100644
--- a/docs/reference/simpleEstimate.html
+++ b/docs/reference/simpleEstimate.html
@@ -152,7 +152,7 @@ details on the parameters.</p>
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 2000 40 457996
+#> 2000 40 33804
#>
#> 3 additional parameters
#>
diff --git a/docs/reference/sparseDCEstimate.html b/docs/reference/sparseDCEstimate.html
index 675f8df47a5b2550183927d97274e67c309bb5a5..3ab9bb0b43468bb761df4c22b0c76d24e90f0c85 100644
--- a/docs/reference/sparseDCEstimate.html
+++ b/docs/reference/sparseDCEstimate.html
@@ -173,7 +173,7 @@ input data. The counts are preprocessed using
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 500 20 457996
+#> 500 20 33804
#>
#> 7 additional parameters
#>
diff --git a/docs/reference/splatEstDropout.html b/docs/reference/splatEstDropout.html
index f275512cc393a29b075fec8e6a16601143466dbf..f763342199c29592a1ed2e4f6db4860ac07bb705 100644
--- a/docs/reference/splatEstDropout.html
+++ b/docs/reference/splatEstDropout.html
@@ -129,7 +129,9 @@ when simulating dropout.</p>
<p>Logistic function parameters are estimated by fitting a logistic function
to the relationship between log2 mean gene expression and the proportion of
-zeros in each gene. See <code><a href='http://www.rdocumentation.org/packages/stats/topics/nls'>nls</a></code> for details of fitting.</p>
+zeros in each gene. See <code><a href='http://www.rdocumentation.org/packages/stats/topics/nls'>nls</a></code> for details of fitting.
+Note this is done on the experiment level, more granular (eg. group or cell)
+level dropout is not estimated.</p>
</div>
diff --git a/docs/reference/splatEstimate.html b/docs/reference/splatEstimate.html
index 94f00767aa76aee47c1b07c439688fe2b0784f7f..4699daf5afff0f0a90af25b00419c0b99c2ad381 100644
--- a/docs/reference/splatEstimate.html
+++ b/docs/reference/splatEstimate.html
@@ -151,7 +151,7 @@ containing count data to estimate parameters from.</p></td>
#>
#> Global:
#> (GENES) (CELLS) [Seed]
-#> 2000 40 457996
+#> 2000 40 33804
#>
#> 28 additional parameters
#>
@@ -184,8 +184,8 @@ containing count data to estimate parameters from.</p></td>
#> 3.21969047393022 14.7262017878812
#>
#> Dropout:
-#> [Present] (MIDPOINT) (SHAPE)
-#> FALSE 5.00420976858168 -0.652889139821156
+#> [Type] (MIDPOINT) (SHAPE)
+#> none 5.00420976858168 -0.652889139821156
#>
#> Paths:
#> [From] [Length] [Skew] [Non-linear] [Sigma Factor]
diff --git a/docs/reference/summariseDiff.html b/docs/reference/summariseDiff.html
index 490a07ad7eaed7f54ad88bb195987e71f646fd0b..a1d0f606ff5d9b1146e7e826c1d8250437c5450d 100644
--- a/docs/reference/summariseDiff.html
+++ b/docs/reference/summariseDiff.html
@@ -127,20 +127,20 @@ Error (RMSE) for the various properties and ranks them.</p>
<pre class="examples"><div class='input'><span class='no'>sim1</span> <span class='kw'><-</span> <span class='fu'><a href='splatSimulate.html'>splatSimulate</a></span>(<span class='kw'>nGenes</span> <span class='kw'>=</span> <span class='fl'>1000</span>, <span class='kw'>batchCells</span> <span class='kw'>=</span> <span class='fl'>20</span>)</div><div class='output co'>#> <span class='message'>Getting parameters...</span></div><div class='output co'>#> <span class='message'>Creating simulation object...</span></div><div class='output co'>#> <span class='message'>Simulating library sizes...</span></div><div class='output co'>#> <span class='message'>Simulating gene means...</span></div><div class='output co'>#> <span class='message'>Simulating BCV...</span></div><div class='output co'>#> <span class='message'>Simulating counts..</span></div><div class='output co'>#> <span class='message'>Simulating dropout (if needed)...</span></div><div class='output co'>#> <span class='message'>Done!</span></div><div class='input'><span class='no'>sim2</span> <span class='kw'><-</span> <span class='fu'><a href='simpleSimulate.html'>simpleSimulate</a></span>(<span class='kw'>nGenes</span> <span class='kw'>=</span> <span class='fl'>1000</span>, <span class='kw'>nCells</span> <span class='kw'>=</span> <span class='fl'>20</span>)</div><div class='output co'>#> <span class='message'>Simulating means...</span></div><div class='output co'>#> <span class='message'>Simulating counts...</span></div><div class='output co'>#> <span class='message'>Creating final dataset...</span></div><div class='input'><span class='no'>difference</span> <span class='kw'><-</span> <span class='fu'><a href='diffSCEs.html'>diffSCEs</a></span>(<span class='fu'>list</span>(<span class='kw'>Splat</span> <span class='kw'>=</span> <span class='no'>sim1</span>, <span class='kw'>Simple</span> <span class='kw'>=</span> <span class='no'>sim2</span>), <span class='kw'>ref</span> <span class='kw'>=</span> <span class='st'>"Simple"</span>)</div><div class='output co'>#> <span class='message'>Note that the names of some metrics have changed, see 'Renamed metrics' in ?calculateQCMetrics.</span>
#> <span class='message'>Old names are currently maintained for back-compatibility, but may be removed in future releases.</span></div><div class='output co'>#> <span class='message'>Note that the names of some metrics have changed, see 'Renamed metrics' in ?calculateQCMetrics.</span>
#> <span class='message'>Old names are currently maintained for back-compatibility, but may be removed in future releases.</span></div><div class='input'><span class='no'>summary</span> <span class='kw'><-</span> <span class='fu'>summariseDiff</span>(<span class='no'>difference</span>)
-<span class='fu'>head</span>(<span class='no'>summary</span>)</div><div class='output co'>#> Dataset Statistic MAD MADScaled MADRank MAE MAEScaled
-#> 1 Splat Mean 2.67384 NaN 1 2.710879 NaN
-#> 2 Splat Variance 11.83125 NaN 1 10.836162 NaN
-#> 3 Splat ZerosGene 35.00000 NaN 1 40.860000 NaN
-#> 4 Splat MeanVar 11.35193 NaN 1 12.464230 NaN
-#> 5 Splat MeanZeros 45.00000 NaN 1 43.990000 NaN
-#> 6 Splat LibSize 54007.50000 NaN 1 57638.350000 NaN
+<span class='fu'>head</span>(<span class='no'>summary</span>)</div><div class='output co'>#> Dataset Statistic MAD MADScaled MADRank MAE MAEScaled
+#> 1 Splat Mean 2.578921 NaN 1 2.526951 NaN
+#> 2 Splat Variance 11.923672 NaN 1 10.771444 NaN
+#> 3 Splat ZerosGene 35.000000 NaN 1 41.210000 NaN
+#> 4 Splat MeanVar 11.687919 NaN 1 12.429719 NaN
+#> 5 Splat MeanZeros 45.000000 NaN 1 42.440000 NaN
+#> 6 Splat LibSize 53750.500000 NaN 1 57352.550000 NaN
#> MAERank RMSE RMSEScaled RMSERank
-#> 1 1 3.287816 NaN 1
-#> 2 1 13.638593 NaN 1
-#> 3 1 45.098780 NaN 1
-#> 4 1 15.539611 NaN 1
-#> 5 1 53.837719 NaN 1
-#> 6 1 58755.898060 NaN 1</div></pre>
+#> 1 1 3.056807 NaN 1
+#> 2 1 13.346501 NaN 1
+#> 3 1 45.518677 NaN 1
+#> 4 1 15.389141 NaN 1
+#> 5 1 51.924946 NaN 1
+#> 6 1 58750.990661 NaN 1</div></pre>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
diff --git a/inst/NEWS.Rd b/inst/NEWS.Rd
index 4dad2117cdde8ed95c6b972db5a671b9af3788c6..4c7cd3bc2283ca639a23d166a8c4eeba3f6fb364 100644
--- a/inst/NEWS.Rd
+++ b/inst/NEWS.Rd
@@ -1,12 +1,14 @@
\name{NEWS}
\title{News for Package \pkg{splatter}}
-\section{Version 1.3.4, Bioconductor 3.7 Release (2017-04-19)}{
+\section{Version 1.3.5, Bioconductor 3.7 Release (2017-04-25)}{
\itemize{
\item{Move scater to Imports and add scater version}
\item{Remove lingering references to SCESets}
\item{Add option to use a normal distribution for library sizes in Splat
simulations}
+ \item{Allow Splat dropout parameters to be specified by experiment, batch,
+ group or cell}
\item{Add SparseDC simulation}
\item{Rename params in metadata slot of simulation to Params for
consistency}
diff --git a/man/splatEstDropout.Rd b/man/splatEstDropout.Rd
index a2cf09d8272cdb2f5b698e556017192dd9368106..478a782a34a427116879f0efcfe7fe66c1cfa37c 100644
--- a/man/splatEstDropout.Rd
+++ b/man/splatEstDropout.Rd
@@ -22,4 +22,6 @@ when simulating dropout.
Logistic function parameters are estimated by fitting a logistic function
to the relationship between log2 mean gene expression and the proportion of
zeros in each gene. See \code{\link[stats]{nls}} for details of fitting.
+Note this is done on the experiment level, more granular (eg. group or cell)
+level dropout is not estimated.
}