Merge pull request #44 from YosefLab/docs

Merge docs

Author: deto

.Rbuildignore

@@ -3,3 +3,4 @@
 ^\.travis\.yml$
 ^build_whitelist.sh$
 ^docs/.*$
+^.*.eslintrc.json

.travis.yml

@@ -1,6 +1,6 @@
 # R for travis: see documentation at https://docs.travis-ci.com/user/languages/r
 
-language: R
+language: r
 cache: packages
 
 r:

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: VISION
 Title: Functional interpretation of single cell RNA-seq latent manifolds
-Version: 0.99.6
+Version: 1.0.0
 Authors@R: c(person("Matt", "Jones", email = "mattjones315@gmail.com", role = c("aut", "cre")),
 			 person("David", "Detomaso", email = "david.detomaso@berkeley.edu", role = c("aut", "cre")),
 			 person("Tal", "Ashuach", email = "tal_ashuach@berkeley.edu", role = c("aut")),
@@ -17,6 +17,7 @@ Imports:
 	loe,
 	logging,
     parallel,
+    pbmcapply (>= 1.3.1),
 	Matrix,
 	matrixStats,
 	mclust,
@@ -32,16 +33,16 @@ LinkingTo: Rcpp
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true
+URL: https://yoseflab.github.io/VISION, https://github.com/yoseflab/VISION
 BugReports: https://github.com/YosefLab/VISION/issues
 RoxygenNote: 6.1.1
 Suggests:
 	Biobase,
 	BiocStyle,
 	knitr,
 	rmarkdown,
-	SummarizedExperiment,
     testthat,
-    ggplot2,
+    ggplot2
 biocViews:
 	GeneExpression,
 	RNASeq,

NAMESPACE

@@ -2,10 +2,25 @@
 
 export(Vision)
 export(applyMicroClustering)
+export(convertGeneIds)
 export(createGeneSignature)
+export(poolMatrixCols)
+export(poolMatrixRows)
+export(poolMetaData)
+export(read_10x)
+export(read_10x_h5)
 exportMethods(Vision)
 exportMethods(addProjection)
 exportMethods(analyze)
+exportMethods(getLatentSpace)
+exportMethods(getLatentTrajectory)
+exportMethods(getMetaAutocorrelation)
+exportMethods(getMetaDifferential)
+exportMethods(getProjections)
+exportMethods(getSelections)
+exportMethods(getSignatureAutocorrelation)
+exportMethods(getSignatureDifferential)
+exportMethods(getSignatureScores)
 exportMethods(saveAndViewResults)
 exportMethods(viewResults)
 import(Matrix)
@@ -15,6 +30,7 @@ import(loe)
 import(logging)
 import(methods)
 import(stats)
+importFrom(Matrix,readMM)
 importFrom(Matrix,rowMeans)
 importFrom(Matrix,rowSums)
 importFrom(Matrix,sparseMatrix)
@@ -48,6 +64,7 @@ importFrom(matrixStats,rowSds)
 importFrom(mclust,Mclust)
 importFrom(mclust,mclustBIC)
 importFrom(parallel,mclapply)
+importFrom(pbmcapply,pbmclapply)
 importFrom(rsvd,rsvd)
 importFrom(stats,chisq.test)
 importFrom(stats,kmeans)

NEWS

@@ -1,3 +1,8 @@
 # VISION 1.0.0
 
-Initial release of VISION
+* Added Layout Options to the output report
+* Selected cells can now be saved/loaded
+* Addition of "get*"-style accessor methods to the VISION object
+* Added an interface to Seurat objects
+* Added convenience methods for working with outputs from 10x Genomic's CellRanger
+* **Note**: Some changes were made to the Vision object structure and how results are stored.  If updating to 1.0.0, older Vision objects may need to be re-created and re-run before using `viewResults`

NEWS.md

@@ -6,7 +6,7 @@
 # on the different types of data.
 
 setClassUnion('numericORNULL', members=c('numeric', 'NULL'))
-setClassUnion('matrixORSparse', members=c("matrix", "dgCMatrix", "dgTMatrix"))
+setClassUnion('matrixORSparse', members=c("matrix", "dgeMatrix", "dgCMatrix", "dgTMatrix"))
 
 Cluster <- setClass("Cluster",
     slots = c(
@@ -19,10 +19,10 @@ Cluster <- setClass("Cluster",
 
 ProjectionData <- setClass("ProjectionData",
     slots = c(
-    sigProjMatrix = "matrix",
-    pMatrix = "matrix",
-    sigClusters = "list",
-    emp_pMatrix = "matrix"
+    Consistency = "matrix",
+    pValue = "matrix",
+    FDR = "matrix",
+    sigClusters = "list"
 ))
 
 PCAnnotatorData <- setClass("PCAnnotatorData",
@@ -83,13 +83,10 @@ Vision <- setClass("Vision",
         sig_norm_method = "character",
         sig_score_method = "character",
         exprData = "matrixORSparse",
-        initialExprData = "matrixORSparse",
         unnormalizedData = "matrixORSparse",
-        initialUnnormalizedData = "matrixORSparse",
         housekeepingData = "character",
         sigData = "list",
         metaData = "data.frame",
-        initialMetaData = "data.frame",
         perm_wPCA = "logical",
         pool = "logical",
         sigScores = "matrix",
@@ -104,10 +101,8 @@ Vision <- setClass("Vision",
         pools = "list",
         inputProjections = "list",
         name = "character",
-        cluster_variable = "character",
         latentSpace = "matrix",
         latentTrajectory = "Trajectory",
-        initialLatentSpace = "matrix",
         version = "numeric",
         selections = "list"),
     prototype = list(
@@ -116,13 +111,10 @@ Vision <- setClass("Vision",
         threshold = 0,
         sig_norm_method = "znorm_rows",
         exprData = matrix(NA, 1, 1),
-        initialExprData = matrix(NA, 1, 1),
         unnormalizedData = matrix(NA, 1, 1),
-        initialUnnormalizedData = matrix(NA, 1, 1),
         housekeepingData = character(),
         sigData = list(),
         metaData = data.frame(),
-        initialMetaData = data.frame(),
         perm_wPCA = FALSE,
         pool = FALSE,
         sigScores = matrix(NA, 1, 1),
@@ -137,10 +129,8 @@ Vision <- setClass("Vision",
         pools = list(),
         inputProjections = list(),
         name = "",
-        cluster_variable = "",
         latentSpace = matrix(NA, 1, 1),
         latentTrajectory = NULL,
-        initialLatentSpace = matrix(NA, 1, 1),
-        version = 1.0,
+        version = 1.1,
         selections = list()
 ))

R/AllClasses.R

@@ -35,3 +35,35 @@ setGeneric("getSelections", function(object, ...) {
 setGeneric("computeKNNWeights", function(object, ...) {
     standardGeneric("computeKNNWeights")
 })
+
+setGeneric("getProjections", function(object, ...) {
+    standardGeneric("getProjections")
+})
+
+setGeneric("getLatentSpace", function(object, ...) {
+    standardGeneric("getLatentSpace")
+})
+
+setGeneric("getLatentTrajectory", function(object, ...) {
+    standardGeneric("getLatentTrajectory")
+})
+
+setGeneric("getSignatureScores", function(object, ...) {
+    standardGeneric("getSignatureScores")
+})
+
+setGeneric("getSignatureAutocorrelation", function(object, ...) {
+    standardGeneric("getSignatureAutocorrelation")
+})
+
+setGeneric("getSignatureDifferential", function(object, ...) {
+    standardGeneric("getSignatureDifferential")
+})
+
+setGeneric("getMetaAutocorrelation", function(object, ...) {
+    standardGeneric("getMetaAutocorrelation")
+})
+
+setGeneric("getMetaDifferential", function(object, ...) {
+    standardGeneric("getMetaDifferential")
+})