version bump. update manuals.

mahmoudibrahim · Apr 13, 2020 · c9ab435 · c9ab435
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,24 +1,24 @@
-Package: genesorteR
-Type: Package
-Title: Feature Ranking in Clustered Single Cell Data
-Version: 0.4.2
-Author: Mahmoud M Ibrahim
-Maintainer: Mahmoud M Ibrahim <[email protected]>
-Description: The main purpose of this R extension is to select features in (possibly very large) single cell data including scRNA-Seq and scATAC-Seq.
-    The main idea is that the dropout rate of a gene is a good measure of its expression, and that empirical statistics calculated based on binarized expression matrices are sufficient to select marker genes in a way that is consistent with the expected definition of "marker gene" in experimental biology research.
-    It can provide a ranking of genes specificity in each cell cluster, as well as select large or small sets of marker genes by a permutation test or using entropy-based feature selection.
-    To assess cell clustering quality, some functions can also compute cell cluster quality metrics.
-License: GPL-3 + file LICENSE
-Encoding: UTF-8
-LazyData: true
-RoxygenNote: 6.1.1
-URL: http://github.com/mahmoudibrahim/genesorteR
-BugReports: http://github.com/mahmoudibrahim/genesorteR/issues
-Imports:
-    mclust,
-    parallel,
-    pheatmap,
-    methods
-Depends:
-	R (>= 2.10),
-    Matrix
+Package: genesorteR
+Type: Package
+Title: Feature Ranking in Clustered Single Cell Data
+Version: 0.4.3
+Author: Mahmoud M Ibrahim
+Maintainer: Mahmoud M Ibrahim <[email protected]>
+Description: The main purpose of this R extension is to select features in (possibly very large) single cell data including scRNA-Seq and scATAC-Seq.
+    The main idea is that the dropout rate of a gene is a good measure of its expression, and that empirical statistics calculated based on binarized expression matrices are sufficient to select marker genes in a way that is consistent with the expected definition of "marker gene" in experimental biology research.
+    It can provide a ranking of genes specificity in each cell cluster, as well as select large or small sets of marker genes by a permutation test or using entropy-based feature selection.
+    To assess cell clustering quality, some functions can also compute cell cluster quality metrics.
+License: GPL-3 + file LICENSE
+Encoding: UTF-8
+LazyData: true
+RoxygenNote: 7.1.0
+URL: http://github.com/mahmoudibrahim/genesorteR
+BugReports: http://github.com/mahmoudibrahim/genesorteR/issues
+Imports:
+    mclust,
+    parallel,
+    pheatmap,
+    methods
+Depends:
+	R (>= 2.10),
+    Matrix
diff --git a/genesorteR.pdf b/genesorteR.pdf
diff --git a/man/getMarkers.Rd b/man/getMarkers.Rd
diff --git a/man/getPValues.Rd b/man/getPValues.Rd
diff --git a/man/getTable.Rd b/man/getTable.Rd
diff --git a/man/kidneyTabulaMuris.Rd b/man/kidneyTabulaMuris.Rd
diff --git a/man/plotBinaryHeat.Rd b/man/plotBinaryHeat.Rd
diff --git a/man/plotCorrelationHeat.Rd b/man/plotCorrelationHeat.Rd
diff --git a/man/plotMarkerHeat.Rd b/man/plotMarkerHeat.Rd
diff --git a/man/plotMarkerScores.Rd b/man/plotMarkerScores.Rd
diff --git a/man/plotTopBinaryHeat.Rd b/man/plotTopBinaryHeat.Rd
diff --git a/man/plotTopMarkerHeat.Rd b/man/plotTopMarkerHeat.Rd
diff --git a/man/sim.Rd b/man/sim.Rd
diff --git a/man/sortGenes.Rd b/man/sortGenes.Rd
diff --git a/man/write.files.Rd b/man/write.files.Rd