... | ... |
@@ -1,10 +1,10 @@ |
1 | 1 |
Package: RGMQL |
2 | 2 |
Type: Package |
3 | 3 |
Title: GenoMetric Query Language for R/Bioconductor |
4 |
-Version: 0.99.31 |
|
4 |
+Version: 0.99.32 |
|
5 | 5 |
Author: Simone Pallotta, Marco Masseroli |
6 | 6 |
Maintainer: Simone Pallotta <simonepallotta@hotmail.com> |
7 |
-Description: This RGMQL package brings the GenoMetric Query Language (GMQL) |
|
7 |
+Description: This package brings the GenoMetric Query Language (GMQL) |
|
8 | 8 |
functionalities into the R environment. GMQL is a high-level, declarative |
9 | 9 |
language to query and compare multiple and heterogeneous genomic datasets |
10 | 10 |
for biomedical knowledge discovery. It allows expressing easily queries and |
... | ... |
@@ -63,12 +63,47 @@ Imports: |
63 | 63 |
methods, |
64 | 64 |
S4Vectors, |
65 | 65 |
dplyr, |
66 |
- stats |
|
66 |
+ stats, |
|
67 |
+ BiocGenerics |
|
67 | 68 |
Depends: |
68 | 69 |
R(>= 3.4.2) |
69 | 70 |
VignetteBuilder: knitr |
70 |
-Suggests: |
|
71 |
+Suggests: |
|
71 | 72 |
BiocStyle, |
72 | 73 |
knitr, |
73 | 74 |
rmarkdown |
74 |
-biocViews: Software,Infrastructure,DataImport,Network,SingleCell |
|
75 |
+biocViews: |
|
76 |
+ Software, |
|
77 |
+ Infrastructure, |
|
78 |
+ DataImport, |
|
79 |
+ Network, |
|
80 |
+ SingleCell |
|
81 |
+Collate: |
|
82 |
+ 'GMQLDataset-class.R' |
|
83 |
+ 'Cover.R' |
|
84 |
+ 'Difference.R' |
|
85 |
+ 'Extend.R' |
|
86 |
+ 'GMQL4TFarm.R' |
|
87 |
+ 'GMQLtoGRanges.R' |
|
88 |
+ 'GRangesToGMQL.R' |
|
89 |
+ 'Join.R' |
|
90 |
+ 'Map.R' |
|
91 |
+ 'Materialize.R' |
|
92 |
+ 'Merge.R' |
|
93 |
+ 'Order.R' |
|
94 |
+ 'Project.R' |
|
95 |
+ 'Read.R' |
|
96 |
+ 'Select.R' |
|
97 |
+ 'Union.R' |
|
98 |
+ 'Utils.R' |
|
99 |
+ 'aggregate-class.R' |
|
100 |
+ 'authOp.R' |
|
101 |
+ 'browseOp.R' |
|
102 |
+ 'condition-class.R' |
|
103 |
+ 'cover_param-class.R' |
|
104 |
+ 'datasetOp.R' |
|
105 |
+ 'distal-class.R' |
|
106 |
+ 'onLoad.R' |
|
107 |
+ 'operator-class.R' |
|
108 |
+ 'ordering-class.R' |
|
109 |
+ 'queryOp.R' |
... | ... |
@@ -30,7 +30,6 @@ export(SUM) |
30 | 30 |
export(UP) |
31 | 31 |
export(compile_query) |
32 | 32 |
export(compile_query_fromfile) |
33 |
-export(cover) |
|
34 | 33 |
export(delete_dataset) |
35 | 34 |
export(download_as_GRangesList) |
36 | 35 |
export(download_dataset) |
... | ... |
@@ -41,7 +40,6 @@ export(import_gmql) |
41 | 40 |
export(init_gmql) |
42 | 41 |
export(login_gmql) |
43 | 42 |
export(logout_gmql) |
44 |
-export(map) |
|
45 | 43 |
export(materialize) |
46 | 44 |
export(read) |
47 | 45 |
export(read_dataset) |
... | ... |
@@ -64,10 +62,11 @@ export(trace_job) |
64 | 62 |
export(upload_dataset) |
65 | 63 |
exportMethods(aggregate) |
66 | 64 |
exportMethods(cover) |
65 |
+exportMethods(extend) |
|
67 | 66 |
exportMethods(filter) |
68 | 67 |
exportMethods(join) |
68 |
+exportMethods(map) |
|
69 | 69 |
exportMethods(materialize) |
70 |
-exportMethods(mutate) |
|
71 | 70 |
exportMethods(setdiff) |
72 | 71 |
exportMethods(sort) |
73 | 72 |
exportMethods(subset) |
... | ... |
@@ -77,6 +76,7 @@ import(httr) |
77 | 76 |
import(xml2) |
78 | 77 |
importClassesFrom(GenomicRanges,GRangesList) |
79 | 78 |
importClassesFrom(S4Vectors,DataTable) |
79 |
+importFrom(BiocGenerics,subset) |
|
80 | 80 |
importFrom(GenomicRanges,makeGRangesFromDataFrame) |
81 | 81 |
importFrom(S4Vectors,metadata) |
82 | 82 |
importFrom(data.table,fread) |
... | ... |
@@ -21,14 +21,15 @@ |
21 | 21 |
#' yielding to one sample in the result for each group. |
22 | 22 |
#' Input samples that do not satisfy the \emph{groupby} condition |
23 | 23 |
#' are disregarded. |
24 |
-#' |
|
24 |
+#' |
|
25 |
+#' @include GMQLDataset-class.R |
|
25 | 26 |
#' @importFrom methods is |
26 | 27 |
#' @importFrom rJava J |
27 | 28 |
#' @importFrom rJava .jnull |
28 | 29 |
#' @importFrom rJava .jarray |
29 | 30 |
#' |
30 | 31 |
#' @param data GMQLDataset class object |
31 |
-#' @param minAcc minimum number of overlapping regions to be considered |
|
32 |
+#' @param min_acc minimum number of overlapping regions to be considered |
|
32 | 33 |
#' during execution |
33 | 34 |
#' Is a integer number, declared also as string. |
34 | 35 |
#' minAcc accept also: |
... | ... |
@@ -38,7 +39,7 @@ |
38 | 39 |
#' \item{and expression built using PARAMETER object: (ALL() + N) / K or |
39 | 40 |
#' ALL() / K } |
40 | 41 |
#' } |
41 |
-#' @param maxAcc maximum number of overlapping regions to be considered |
|
42 |
+#' @param max_acc maximum number of overlapping regions to be considered |
|
42 | 43 |
#' during execution |
43 | 44 |
#' Is a integer number, declared also as string. |
44 | 45 |
#' maxAcc accept also: |
... | ... |
@@ -99,7 +100,8 @@ |
99 | 100 |
#' the AccIndex region attribute.} |
100 | 101 |
#' \item{cover: default value.} |
101 | 102 |
#' } |
102 |
-#' |
|
103 |
+#' @param ... Additional arguments for use in specific methods. |
|
104 |
+#' |
|
103 | 105 |
#' @return GMQLDataset class object. It contains the value to use as input |
104 | 106 |
#' for the subsequent GMQL function |
105 | 107 |
#' |
... | ... |
@@ -113,7 +115,7 @@ |
113 | 115 |
#' init_gmql() |
114 | 116 |
#' test_path <- system.file("example","DATASET",package = "RGMQL") |
115 | 117 |
#' exp = read_dataset(test_path) |
116 |
-#' res = cover(exp, 2, ANY()) |
|
118 |
+#' res = cover(exp, 2, "ANY") |
|
117 | 119 |
#' |
118 | 120 |
#' \dontrun{ |
119 | 121 |
#' ## This GMQL statement computes the result grouping the input exp samples |
... | ... |
@@ -129,44 +131,25 @@ |
129 | 131 |
#' res = cover(exp, 2, 3, c("cell"), list(min_pValue = MIN("pvalue"))) |
130 | 132 |
#' } |
131 | 133 |
#' |
132 |
-#' |
|
133 |
-#' @rdname GMQLDataset-class |
|
134 |
-#' @aliases cover, GMQLDataset--method |
|
135 |
-#' |
|
136 |
-#' @export |
|
137 |
-#' |
|
138 |
-setGeneric("cover", function(data, minAcc, maxAcc, ...) |
|
139 |
-{ |
|
140 |
- minAcc <- .trasform_cover(deparse(substitute(minAcc))) |
|
141 |
- maxAcc <- .trasform_cover(deparse(substitute(maxAcc))) |
|
142 |
- |
|
143 |
- min <- .check_cover_param(minAcc,TRUE) |
|
144 |
- max <- .check_cover_param(maxAcc,FALSE) |
|
145 |
- |
|
146 |
- gmql_cover(data,min,max,NULL,NULL,"COVER") |
|
147 |
-}) |
|
148 |
- |
|
149 |
-#' @rdname GMQLDataset-class |
|
150 |
-#' @aliases cover, GMQLDataset--method |
|
134 |
+#' @aliases cover, cover-method |
|
151 | 135 |
#' @export |
152 | 136 |
setMethod("cover", "GMQLDataset", |
153 |
- function(data, minAcc, maxAcc, groupBy = NULL, aggregates = NULL, |
|
137 |
+ function(data, min_acc, max_acc, groupBy = NULL, aggregates = NULL, |
|
154 | 138 |
variation = "cover") |
155 | 139 |
{ |
156 |
- minAcc <- .trasform_cover(deparse(substitute(minAcc))) |
|
157 |
- maxAcc <- .trasform_cover(deparse(substitute(maxAcc))) |
|
158 |
- |
|
159 |
- min <- .check_cover_param(minAcc,TRUE) |
|
160 |
- max <- .check_cover_param(maxAcc,FALSE) |
|
140 |
+ val <- data@value |
|
141 |
+ q_max <- .check_cover_param(max_acc,FALSE) |
|
142 |
+ q_min <- .check_cover_param(min_acc,FALSE) |
|
161 | 143 |
flag = toupper(variation) |
162 |
- |
|
163 |
- gmql_cover(data@value, min, max, groupBy, aggregates, |
|
164 |
- flag) |
|
144 |
+ gmql_cover(val, q_min, q_max, groupBy, aggregates, flag) |
|
165 | 145 |
}) |
166 | 146 |
|
167 |
-gmql_cover <- function(data, minAcc, maxAcc, groupBy = NULL, |
|
147 |
+ |
|
148 |
+ |
|
149 |
+gmql_cover <- function(data, min_acc, max_acc, groupBy = NULL, |
|
168 | 150 |
aggregates = NULL, flag) |
169 | 151 |
{ |
152 |
+ |
|
170 | 153 |
if(!is.null(groupBy)) |
171 | 154 |
join_condition_matrix <- .jarray(.join_condition(groupBy), |
172 | 155 |
dispatch = TRUE) |
... | ... |
@@ -181,14 +164,14 @@ gmql_cover <- function(data, minAcc, maxAcc, groupBy = NULL, |
181 | 164 |
|
182 | 165 |
WrappeR <- J("it/polimi/genomics/r/Wrapper") |
183 | 166 |
response <- switch(flag, |
184 |
- "COVER" = WrappeR$cover(minAcc, maxAcc, join_condition_matrix, |
|
167 |
+ "COVER" = WrappeR$cover(min_acc, max_acc, join_condition_matrix, |
|
185 | 168 |
metadata_matrix, data), |
186 |
- "FLAT" = WrappeR$flat(minAcc, maxAcc, join_condition_matrix, |
|
169 |
+ "FLAT" = WrappeR$flat(min_acc, max_acc, join_condition_matrix, |
|
187 | 170 |
metadata_matrix, data), |
188 |
- "SUMMIT" = WrappeR$summit(minAcc,maxAcc, join_condition_matrix, |
|
171 |
+ "SUMMIT" = WrappeR$summit(min_acc,max_acc, join_condition_matrix, |
|
189 | 172 |
metadata_matrix, data), |
190 |
- "HISTOGRAM" = WrappeR$histogram(minAcc, maxAcc, |
|
191 |
- join_condition_matrix, metadata_matrix, data)) |
|
173 |
+ "HISTOGRAM" = WrappeR$histogram(min_acc, max_acc, |
|
174 |
+ join_condition_matrix, metadata_matrix, data)) |
|
192 | 175 |
if(is.null(response)) |
193 | 176 |
stop("no admissible variation: cover, flat, summit, histogram") |
194 | 177 |
|
... | ... |
@@ -200,7 +183,7 @@ gmql_cover <- function(data, minAcc, maxAcc, groupBy = NULL, |
200 | 183 |
GMQLDataset(data) |
201 | 184 |
} |
202 | 185 |
|
203 |
-.check_cover_param <- function(param,is_min) |
|
186 |
+.check_cover_param <- function(param, is_min) |
|
204 | 187 |
{ |
205 | 188 |
if(length(param)>1) |
206 | 189 |
stop("length > 1") |
... | ... |
@@ -214,12 +197,19 @@ gmql_cover <- function(data, minAcc, maxAcc, groupBy = NULL, |
214 | 197 |
} |
215 | 198 |
else if(is.character(param)) |
216 | 199 |
{ |
217 |
- if(is_min && identical(param,"ANY")) |
|
218 |
- stop("min cannot assume ANY as value") |
|
200 |
+ if(is.na(as.numeric(param))) |
|
201 |
+ { |
|
202 |
+ if(is_min && identical(param,"ANY")) |
|
203 |
+ stop("min cannot assume ANY as value") |
|
204 |
+ |
|
205 |
+ if(!identical(param,"ANY") && !identical(param,"ALL")) |
|
206 |
+ stop("invalid input data") |
|
207 |
+ } |
|
219 | 208 |
return(param) |
220 | 209 |
} |
221 | 210 |
else |
222 | 211 |
stop("invalid input data") |
212 |
+ |
|
223 | 213 |
} |
224 | 214 |
|
225 | 215 |
.trasform_cover <- function(predicate=NULL) |
... | ... |
@@ -15,10 +15,10 @@ |
15 | 15 |
#' @importFrom rJava .jnull |
16 | 16 |
#' @importFrom rJava .jarray |
17 | 17 |
#' |
18 |
-#' @param x returned object from any GMQL function |
|
19 |
-#' @param y returned object from any GMQL function |
|
20 |
-#' @param joinBy list of CONDITION objects where every object contains |
|
21 |
-#' the name of metadata to be used in semijoin, or simple string concatenation |
|
18 |
+#' @param x GMQLDataset class object |
|
19 |
+#' @param y GMQLDataset class object |
|
20 |
+#' @param joinBy vector of CONDITION objects where every object contains |
|
21 |
+#' the name of metadata to be used in semijoin, or string concatenation |
|
22 | 22 |
#' of name of metadata, e.g. c("cell_type", "attribute_tag", "size") |
23 | 23 |
#' without declaring condition. |
24 | 24 |
#' The CONDITION's available are: |
... | ... |
@@ -30,9 +30,9 @@ |
30 | 30 |
#' as value will match; no further prefixes are allowed. } |
31 | 31 |
#' } |
32 | 32 |
#' Every condition accepts only one string value. (e.g. FULL("cell_type") ) |
33 |
-#' In case of single concatenation with no CONDITION or list with some value |
|
34 |
-#' without conditon, the metadata are considered having default |
|
35 |
-#' evaluation: the two attributes match if both end with value. |
|
33 |
+#' In case of single concatenation with no CONDITION the metadata are |
|
34 |
+#' considered having default evaluation: |
|
35 |
+#' the two attributes match if both end with value. |
|
36 | 36 |
#' |
37 | 37 |
#' @param is_exact single logical value: TRUE means that the region difference |
38 | 38 |
#' is executed only on regions in left_input_data with exactly the same |
... | ... |
@@ -41,7 +41,7 @@ |
41 | 41 |
#' left_input_data that overlap with at least one region in right_input_data |
42 | 42 |
#' (even just one base). |
43 | 43 |
#' |
44 |
-#' @return DataSet class object. It contains the value to use as input |
|
44 |
+#' @return GMQLDataset class object. It contains the value to use as input |
|
45 | 45 |
#' for the subsequent GMQL function |
46 | 46 |
#' |
47 | 47 |
#' |
... | ... |
@@ -69,23 +69,21 @@ |
69 | 69 |
#' test_path2 <- system.file("example", "DATASET_GDM", package = "RGMQL") |
70 | 70 |
#' exp1 = read_dataset(test_path) |
71 | 71 |
#' exp2 = read_dataset(test_path2) |
72 |
-#' out = setdiff(exp1, exp2, c("antibody_target")) |
|
72 |
+#' out = setdiff(exp1, exp2, joinBy = c("antibody_target")) |
|
73 | 73 |
#' |
74 | 74 |
#' } |
75 |
-#' |
|
76 |
-#' @rdname setdiff-methods |
|
77 |
-#' @aliases setdiff, setdiff-methods |
|
75 |
+#' |
|
76 |
+#' @aliases setdiff, setdiff-method |
|
78 | 77 |
#' @export |
79 | 78 |
setMethod("setdiff", c("GMQLDataset","GMQLDataset"), |
80 |
- function(x, y, joinBy = NULL, is_exact = FALSE) |
|
79 |
+ function(x, y, is_exact = FALSE, joinBy = NULL) |
|
81 | 80 |
{ |
82 | 81 |
val_x = x@value |
83 | 82 |
val_y = y@value |
84 |
- gmql_difference(val_x, val_y, joinBy, is_exact) |
|
83 |
+ gmql_difference(val_x, val_y, is_exact, joinBy) |
|
85 | 84 |
}) |
86 | 85 |
|
87 |
-gmql_difference <- function(left_data, right_data, joinBy = NULL, |
|
88 |
- is_exact = FALSE) |
|
86 |
+gmql_difference <- function(left_data, right_data, is_exact, joinBy) |
|
89 | 87 |
{ |
90 | 88 |
if(!is.null(joinBy)) |
91 | 89 |
join_condition_matrix <- .jarray(.join_condition(joinBy), |
... | ... |
@@ -104,3 +102,4 @@ gmql_difference <- function(left_data, right_data, joinBy = NULL, |
104 | 102 |
GMQLDataset(data) |
105 | 103 |
} |
106 | 104 |
|
105 |
+ |
... | ... |
@@ -1,3 +1,11 @@ |
1 |
+#' @name extend |
|
2 |
+#' @rdname extend-GMQLDataset-method |
|
3 |
+#' @aliases extend, GMQLDataset-method |
|
4 |
+#' @exportMethod extend |
|
5 |
+setGeneric("extend", function(.data, ...) |
|
6 |
+ standardGeneric("extend")) |
|
7 |
+ |
|
8 |
+ |
|
1 | 9 |
#' GMQL Operation: EXTEND |
2 | 10 |
#' |
3 | 11 |
#' It generates new metadata attributes as result of aggregate functions |
... | ... |
@@ -10,7 +18,9 @@ |
10 | 18 |
#' @importFrom rJava .jarray |
11 | 19 |
#' |
12 | 20 |
#' @param .data GMQLDataset class object |
13 |
-#' @param metadata list of element in the form \emph{key} = \emph{aggregate}. |
|
21 |
+#' @param ... Additional arguments for use in specific methods. |
|
22 |
+#' |
|
23 |
+#' In this case a series of element in the form \emph{key} = \emph{aggregate}. |
|
14 | 24 |
#' The \emph{aggregate} is an object of class AGGREGATES |
15 | 25 |
#' The aggregate functions available are: \code{\link{SUM}}, |
16 | 26 |
#' \code{\link{COUNT}}, \code{\link{MIN}}, \code{\link{MAX}}, |
... | ... |
@@ -27,7 +37,7 @@ |
27 | 37 |
#' } |
28 | 38 |
#' "mixed style" is not allowed |
29 | 39 |
#' |
30 |
-#' @return DataSet class object. It contains the value to use as input |
|
40 |
+#' @return GMQLDataset class object. It contains the value to use as input |
|
31 | 41 |
#' for the subsequent GMQL function |
32 | 42 |
#' |
33 | 43 |
#' @examples |
... | ... |
@@ -37,7 +47,7 @@ |
37 | 47 |
#' init_gmql() |
38 | 48 |
#' test_path <- system.file("example", "DATASET", package = "RGMQL") |
39 | 49 |
#' r <- read_dataset(test_path) |
40 |
-#' e <- mutate(input_data = r, list(RegionCount = COUNT())) |
|
50 |
+#' e <- extend(r, RegionCount = COUNT()) |
|
41 | 51 |
#' |
42 | 52 |
#' \dontrun{ |
43 | 53 |
#' |
... | ... |
@@ -50,27 +60,25 @@ |
50 | 60 |
#' init_gmql() |
51 | 61 |
#' test_path <- system.file("example", "DATASET", package = "RGMQL") |
52 | 62 |
#' exp = read_dataset(test_path) |
53 |
-#' res = mutate(input_data = exp, list(RegionCount = COUNT(), |
|
54 |
-#' MinP = MIN("pvalue"))) |
|
63 |
+#' res = extend(exp, RegionCount = COUNT(), MinP = MIN("pvalue"))) |
|
55 | 64 |
#' |
56 | 65 |
#' } |
57 |
-#' |
|
58 |
-#' @name mutate |
|
59 |
-#' @rdname mutate-methods |
|
60 |
-#' @aliases mutate, mutate-methods |
|
66 |
+ |
|
67 |
+#' @aliases extend-method |
|
61 | 68 |
#' @export |
62 |
-setMethod("mutate", "GMQLDataset", |
|
63 |
- function(.data, metadata = NULL) |
|
69 |
+setMethod("extend", "GMQLDataset", |
|
70 |
+ function(.data, ...) |
|
64 | 71 |
{ |
65 | 72 |
val_x = .data@value |
66 |
- gmql_extend(val_x, metadata) |
|
73 |
+ meta <- list(...) |
|
74 |
+ gmql_extend(val_x, meta) |
|
67 | 75 |
}) |
68 | 76 |
|
69 | 77 |
|
70 |
-gmql_extend <-function(input_data, metadata = NULL) |
|
78 |
+gmql_extend <-function(input_data, meta) |
|
71 | 79 |
{ |
72 |
- if(!is.null(metadata)) |
|
73 |
- metadata_matrix <- .jarray(.aggregates(metadata,"META_AGGREGATES"), |
|
80 |
+ if(!is.null(meta) && !length(meta)==0) |
|
81 |
+ metadata_matrix <- .jarray(.aggregates(meta,"META_AGGREGATES"), |
|
74 | 82 |
dispatch = TRUE) |
75 | 83 |
else |
76 | 84 |
metadata_matrix <- .jnull("java/lang/String") |
77 | 85 |
similarity index 62% |
78 | 86 |
rename from R/Dataset-class.R |
79 | 87 |
rename to R/GMQLDataset-class.R |
... | ... |
@@ -7,6 +7,8 @@ |
7 | 7 |
#' @name GMQLDataset-class |
8 | 8 |
#' @rdname GMQLDataset-class |
9 | 9 |
#' |
10 |
+#' @return instance of GMQL dataset |
|
11 |
+ |
|
10 | 12 |
setClass("GMQLDataset", |
11 | 13 |
contains = c("DataTable"), |
12 | 14 |
representation(value = "character")) |
... | ... |
@@ -30,15 +32,6 @@ setMethod("show", "GMQLDataset", |
30 | 32 |
}) |
31 | 33 |
|
32 | 34 |
|
33 |
-#' Method mutate |
|
34 |
-#' |
|
35 |
-#' Wrapper to GMQL extend function |
|
36 |
-#' |
|
37 |
-#' @name mutate |
|
38 |
-#' @rdname mutate-methods |
|
39 |
-#' |
|
40 |
-setGeneric("mutate", function(.data, metadata = NULL) |
|
41 |
- standardGeneric("mutate")) |
|
42 | 35 |
|
43 | 36 |
# insted of GMQL order |
44 | 37 |
# setGeneric("sort", function(data, metadata_ordering = NULL, |
... | ... |
@@ -51,8 +44,9 @@ setGeneric("mutate", function(.data, metadata = NULL) |
51 | 44 |
#' Wrapper to GMQL merge function |
52 | 45 |
#' |
53 | 46 |
#' @name aggregate |
54 |
-#' @rdname aggregate-methods |
|
55 |
-#' |
|
47 |
+#' @rdname aggregate-GMQLDataset-method |
|
48 |
+#' @aliases aggregate |
|
49 |
+#' |
|
56 | 50 |
setGeneric("aggregate", function(data, groupBy = NULL) |
57 | 51 |
standardGeneric("aggregate")) |
58 | 52 |
|
... | ... |
@@ -62,9 +56,42 @@ setGeneric("aggregate", function(data, groupBy = NULL) |
62 | 56 |
#' Wrapper to GMQL join function |
63 | 57 |
#' |
64 | 58 |
#' @name join |
65 |
-#' @rdname join-methods |
|
59 |
+#' @rdname join-GMQLDataset-method |
|
66 | 60 |
#' @aliases join |
67 | 61 |
#' |
68 |
-setGeneric("join", function(x, y, by = NULL, ...) standardGeneric("join")) |
|
62 |
+setGeneric("join", function(x, y, by = NULL,...) standardGeneric("join")) |
|
63 |
+ |
|
64 |
+ |
|
65 |
+#' Method filter |
|
66 |
+#' |
|
67 |
+#' Wrapper to GMQL select function |
|
68 |
+#' |
|
69 |
+#' @name filter |
|
70 |
+#' @rdname filter-GMQLDataset-method |
|
71 |
+#' @aliases filter |
|
72 |
+#' |
|
73 |
+setGeneric("filter", function(.data,...) standardGeneric("filter")) |
|
74 |
+ |
|
75 |
+#' Method cover |
|
76 |
+#' |
|
77 |
+#' Wrapper to GMQL cover function |
|
78 |
+#' |
|
79 |
+#' @name cover |
|
80 |
+#' @rdname cover-GMQLDataset-method |
|
81 |
+#' @aliases cover |
|
82 |
+#' |
|
83 |
+setGeneric("cover", function(data, ...) standardGeneric("cover")) |
|
84 |
+ |
|
85 |
+#' Method map |
|
86 |
+#' |
|
87 |
+#' Wrapper to GMQL map function |
|
88 |
+#' |
|
89 |
+#' @name map |
|
90 |
+#' @rdname map-GMQLDataset-method |
|
91 |
+#' @aliases map |
|
92 |
+#' |
|
93 |
+setGeneric("map", function(x, y, ...) standardGeneric("map")) |
|
94 |
+ |
|
95 |
+ |
|
69 | 96 |
|
70 | 97 |
|
... | ... |
@@ -22,7 +22,7 @@ |
22 | 22 |
#' For details of DISTAL objects see: |
23 | 23 |
#' \code{\link{DLE}}, \code{\link{DGE}}, \code{\link{DL}}, \code{\link{DG}}, |
24 | 24 |
#' \code{\link{MD}}, \code{\link{UP}}, \code{\link{DOWN}} |
25 |
-#' |
|
25 |
+#' @param ... Additional arguments for use in specific methods. |
|
26 | 26 |
#' @param by list of CONDITION objects where every object contains |
27 | 27 |
#' the name of metadata to be used in semijoin, or simple string concatenation |
28 | 28 |
#' of name of metadata, e.g. c("cell_type", "attribute_tag", "size") |
... | ... |
@@ -84,9 +84,7 @@ |
84 | 84 |
#' region_output="RIGHT") |
85 | 85 |
#' |
86 | 86 |
|
87 |
-#' @name join |
|
88 |
-#' @rdname join-methods |
|
89 |
-#' @aliases join, join-methods |
|
87 |
+#' @aliases join-method |
|
90 | 88 |
#' @export |
91 | 89 |
setMethod("join", "GMQLDataset", |
92 | 90 |
function(x, y, by = NULL, genometric_predicate = NULL, |
... | ... |
@@ -94,7 +92,7 @@ setMethod("join", "GMQLDataset", |
94 | 92 |
{ |
95 | 93 |
r_data <- x@value |
96 | 94 |
l_data <- y@value |
97 |
- gmql_join(x, y, genometric_predicate, by, |
|
95 |
+ gmql_join(r_data, l_data, genometric_predicate, by, |
|
98 | 96 |
region_output="contig") |
99 | 97 |
}) |
100 | 98 |
|
... | ... |
@@ -19,9 +19,12 @@ |
19 | 19 |
#' present with equal values in both M1 and M2 |
20 | 20 |
#' |
21 | 21 |
#' |
22 |
-#' @param left_input_data returned object from any GMQL function |
|
23 |
-#' @param right_input_data returned object from any GMQL function |
|
24 |
-#' @param aggregates list of element in the form \emph{key} = \emph{aggregate}. |
|
22 |
+#' @param x GMQLDataset class object |
|
23 |
+#' @param y GMQLDataset class object |
|
24 |
+#' |
|
25 |
+#' @param ... Additional arguments for use in specific methods. |
|
26 |
+#' |
|
27 |
+#' In this case a series of element in the form \emph{key} = \emph{aggregate}. |
|
25 | 28 |
#' The \emph{aggregate} is an object of class AGGREGATES |
26 | 29 |
#' The aggregate functions available are: \code{\link{SUM}}, |
27 | 30 |
#' \code{\link{COUNT}}, \code{\link{MIN}}, \code{\link{MAX}}, |
... | ... |
@@ -54,7 +57,7 @@ |
54 | 57 |
#' without conditon, the metadata are considered having default |
55 | 58 |
#' evaluation: the two attributes match if both end with value. |
56 | 59 |
#' |
57 |
-#' @return DataSet class object. It contains the value to use as input |
|
60 |
+#' @return GMQLDataset class object. It contains the value to use as input |
|
58 | 61 |
#' for the subsequent GMQL function |
59 | 62 |
#' |
60 | 63 |
#' |
... | ... |
@@ -74,16 +77,23 @@ |
74 | 77 |
#' test_path2 <- system.file("example", "DATASET_GDM", package = "RGMQL") |
75 | 78 |
#' exp = read_dataset(test_path) |
76 | 79 |
#' ref = read_dataset(test_path2) |
77 |
-#' out = map(ref,exp, list(minScore = MIN("score")), |
|
78 |
-#' joinBy = c("cell_tissue")) |
|
79 |
-#' |
|
80 |
+#' out = map(ref,exp, minScore = MIN("score"), joinBy = c("cell_tissue")) |
|
80 | 81 |
#' |
82 |
+#' @aliases map-method |
|
81 | 83 |
#' @export |
82 |
-#' |
|
83 |
-map <- function(left_input_data, right_input_data, aggregates = NULL, |
|
84 |
- joinBy = NULL) |
|
84 |
+setMethod("map", "GMQLDataset", |
|
85 |
+ function(x, y, ..., joinBy = NULL) |
|
86 |
+ { |
|
87 |
+ r_data <- x@value |
|
88 |
+ l_data <- y@value |
|
89 |
+ aggregates = list(...) |
|
90 |
+ gmql_map(r_data, l_data, aggregates, joinBy) |
|
91 |
+ }) |
|
92 |
+ |
|
93 |
+ |
|
94 |
+gmql_map <- function(l_data, r_data, aggregates, joinBy) |
|
85 | 95 |
{ |
86 |
- if(!is.null(aggregates)) |
|
96 |
+ if(!is.null(aggregates) && !length(aggregates) == 0) |
|
87 | 97 |
metadata_matrix <- .jarray(.aggregates(aggregates,"AGGREGATES"), |
88 | 98 |
dispatch = TRUE) |
89 | 99 |
else |
... | ... |
@@ -96,8 +106,8 @@ map <- function(left_input_data, right_input_data, aggregates = NULL, |
96 | 106 |
join_condition_matrix <- .jnull("java/lang/String") |
97 | 107 |
|
98 | 108 |
WrappeR <- J("it/polimi/genomics/r/Wrapper") |
99 |
- response<-WrappeR$map(join_condition_matrix, metadata_matrix, |
|
100 |
- left_input_data@value, right_input_data@value) |
|
109 |
+ response<-WrappeR$map(join_condition_matrix, metadata_matrix, l_data, |
|
110 |
+ r_data) |
|
101 | 111 |
error <- strtoi(response[1]) |
102 | 112 |
data <- response[2] |
103 | 113 |
if(error!=0) |
... | ... |
@@ -12,9 +12,9 @@ |
12 | 12 |
#' init_gmql() |
13 | 13 |
#' test_path <- system.file("example","DATASET",package = "RGMQL") |
14 | 14 |
#' r = read_dataset(test_path) |
15 |
-#' s = filter(input_data = r) |
|
16 |
-#' m = aggregate(groupBy = c("antibody_targer","cell_karyotype"),input_data = s) |
|
17 |
-#' materialize(input_data = m, dir_out = test_path) |
|
15 |
+#' s = filter(r) |
|
16 |
+#' m = aggregate(s, groupBy = c("antibody_targer","cell_karyotype")) |
|
17 |
+#' materialize(m, dir_out = test_path) |
|
18 | 18 |
#' |
19 | 19 |
#' \dontrun{ |
20 | 20 |
#' execute() |
... | ... |
@@ -65,9 +65,7 @@ execute <- function() |
65 | 65 |
} |
66 | 66 |
} |
67 | 67 |
|
68 |
-#' @name materialize |
|
69 |
-#' @rdname materialize-methods |
|
70 |
-#' @aliases materialize |
|
68 |
+#' @rdname materialize-GMQLDataset-method |
|
71 | 69 |
#' @export |
72 | 70 |
setGeneric("materialize", function(data, ...) standardGeneric("materialize")) |
73 | 71 |
|
... | ... |
@@ -86,7 +84,7 @@ setGeneric("materialize", function(data, ...) standardGeneric("materialize")) |
86 | 84 |
#' @param data GMQLDataset class object |
87 | 85 |
#' @param dir_out destination folder path. |
88 | 86 |
#' by default is current working directory of the R process |
89 |
-#' |
|
87 |
+#' @param ... Additional arguments for use in specific methods. |
|
90 | 88 |
#' @return None |
91 | 89 |
#' |
92 | 90 |
#' @examples |
... | ... |
@@ -94,13 +92,11 @@ setGeneric("materialize", function(data, ...) standardGeneric("materialize")) |
94 | 92 |
#' init_gmql() |
95 | 93 |
#' test_path <- system.file("example","DATASET",package = "RGMQL") |
96 | 94 |
#' r = read_dataset(test_path) |
97 |
-#' s = filter(input_data = r) |
|
95 |
+#' s = filter(r) |
|
98 | 96 |
#' m = aggregate(s, groupBy = c("antibody_targer","cell_karyotype")) |
99 |
-#' materialize(input_data = m, dir_out = test_path) |
|
97 |
+#' materialize(m, dir_out = test_path) |
|
100 | 98 |
#' |
101 |
-#' @name materialize |
|
102 |
-#' @rdname materialize-methods |
|
103 |
-#' @aliases materialize, materialize-methods |
|
99 |
+#' @aliases materialize-method |
|
104 | 100 |
#' @export |
105 | 101 |
setMethod("materialize", "GMQLDataset", |
106 | 102 |
function(data, dir_out = getwd()) |
... | ... |
@@ -149,7 +145,7 @@ gmql_materialize <- function(data, dir_out) |
149 | 145 |
#' test_path <- system.file("example", "DATASET", package = "RGMQL") |
150 | 146 |
#' r = read_dataset(test_path) |
151 | 147 |
#' m = aggregate(r, groupBy = c("antibody_target", "cell_karyotype")) |
152 |
-#' g <- take(input_data = m, rows = 45) |
|
148 |
+#' g <- take(m, rows = 45) |
|
153 | 149 |
#' |
154 | 150 |
#' @export |
155 | 151 |
#' |
... | ... |
@@ -46,18 +46,16 @@ |
46 | 46 |
#' init_gmql() |
47 | 47 |
#' test_path <- system.file("example","DATASET",package = "RGMQL") |
48 | 48 |
#' exp = read_dataset(test_path) |
49 |
-#' merged = aggregate(input_data = exp, groupBy = c("antibody_target")) |
|
49 |
+#' merged = aggregate(exp, groupBy = c("antibody_target")) |
|
50 | 50 |
#' |
51 |
-#' @name aggregate |
|
52 |
-#' @rdname aggregate-methods |
|
53 |
-#' @aliases aggregate, aggregate-methods |
|
51 |
+#' @aliases aggregate-method |
|
54 | 52 |
#' @export |
55 | 53 |
#' |
56 | 54 |
setMethod("aggregate", "GMQLDataset", |
57 | 55 |
function(data, groupBy = NULL) |
58 | 56 |
{ |
59 | 57 |
val = data@value |
60 |
- gmql_merge(val, metadata) |
|
58 |
+ gmql_merge(val, groupBy) |
|
61 | 59 |
}) |
62 | 60 |
|
63 | 61 |
gmql_merge <- function(data, groupBy = NULL) |
... | ... |
@@ -81,9 +81,8 @@ |
81 | 81 |
#' num_fetch = 2) |
82 | 82 |
#' |
83 | 83 |
#' } |
84 |
-#' @name sort |
|
85 |
-#' @rdname sort-methods |
|
86 |
-#' @aliases sort, sort-methods |
|
84 |
+#' |
|
85 |
+#' @aliases sort-method |
|
87 | 86 |
#' @export |
88 | 87 |
setMethod("sort", "GMQLDataset", |
89 | 88 |
function(x, decreasing = FALSE, metadata_ordering = NULL, |
... | ... |
@@ -14,6 +14,7 @@ |
14 | 14 |
#' @importFrom rJava J |
15 | 15 |
#' @importFrom rJava .jnull |
16 | 16 |
#' @importFrom rJava .jarray |
17 |
+#' @importFrom BiocGenerics subset |
|
17 | 18 |
#' |
18 | 19 |
#' @param x GMQLDataset class object |
19 | 20 |
#' @param metadata vector of string made up by metadata attribute |
... | ... |
@@ -84,11 +85,8 @@ |
84 | 85 |
#' |
85 | 86 |
#' } |
86 | 87 |
#' |
87 |
-#' @export |
|
88 | 88 |
#' |
89 |
-#' @name subset |
|
90 |
-#' @rdname subset-methods |
|
91 |
-#' @aliases subset, subset-methods |
|
89 |
+#' @aliases subset |
|
92 | 90 |
#' @export |
93 | 91 |
setMethod("subset", "GMQLDataset", |
94 | 92 |
function(x, metadata = NULL, metadata_update=NULL, |
... | ... |
@@ -96,9 +94,27 @@ setMethod("subset", "GMQLDataset", |
96 | 94 |
regions_update = NULL, all_but_reg=FALSE) |
97 | 95 |
{ |
98 | 96 |
data = x@value |
99 |
- gmql_project(data, metadata, metadata_update, |
|
97 |
+ r_update <- substitute(regions_update) |
|
98 |
+ if(!is.null(r_update)) |
|
99 |
+ { |
|
100 |
+ reg_update <- .trasform_update(deparse(r_update)) |
|
101 |
+ reg_update <- paste(reg_update,collapse = "") |
|
102 |
+ } |
|
103 |
+ else |
|
104 |
+ reg_update <- .jnull("java/lang/String") |
|
105 |
+ |
|
106 |
+ m_update <- substitute(metadata_update) |
|
107 |
+ if(!is.null(m_update)) |
|
108 |
+ { |
|
109 |
+ meta_update <- .trasform_update(deparse(m_update)) |
|
110 |
+ meta_update <- paste(meta_update,collapse = "") |
|
111 |
+ } |
|
112 |
+ else |
|
113 |
+ meta_update <- .jnull("java/lang/String") |
|
114 |
+ |
|
115 |
+ gmql_project(data, metadata, meta_update, |
|
100 | 116 |
all_but_meta, regions, |
101 |
- regions_update, all_but_reg) |
|
117 |
+ reg_update, all_but_reg) |
|
102 | 118 |
}) |
103 | 119 |
|
104 | 120 |
gmql_project <-function(input_data, metadata = NULL, metadata_update=NULL, |
... | ... |
@@ -137,24 +153,7 @@ gmql_project <-function(input_data, metadata = NULL, metadata_update=NULL, |
137 | 153 |
else |
138 | 154 |
regions <- .jnull("java/lang/String") |
139 | 155 |
|
140 |
- reg_update <- substitute(regions_update) |
|
141 |
- if(!is.null(reg_update)) |
|
142 |
- { |
|
143 |
- regions_update <- .trasform_update(deparse(reg_update)) |
|
144 |
- regions_update <- paste(regions_update,collapse = "") |
|
145 |
- } |
|
146 |
- else |
|
147 |
- regions_update <- .jnull("java/lang/String") |
|
148 |
- |
|
149 |
- meta_update <- substitute(metadata_update) |
|
150 |
- if(!is.null(meta_update)) |
|
151 |
- { |
|
152 |
- metadata_update <- .trasform_update(deparse(meta_update)) |
|
153 |
- metadata_update <- paste(metadata_update,collapse = "") |
|
154 |
- } |
|
155 |
- else |
|
156 |
- metadata_update <- .jnull("java/lang/String") |
|
157 |
- |
|
156 |
+ |
|
158 | 157 |
if(length(all_but_meta)>1) |
159 | 158 |
warning("all_but_meta: no multiple values") |
160 | 159 |
|
... | ... |
@@ -167,7 +166,7 @@ gmql_project <-function(input_data, metadata = NULL, metadata_update=NULL, |
167 | 166 |
WrappeR <- J("it/polimi/genomics/r/Wrapper") |
168 | 167 |
response <- WrappeR$project(metadata,metadata_update,all_but_meta, |
169 | 168 |
regions,regions_update, |
170 |
- all_but_reg,input_data$value) |
|
169 |
+ all_but_reg,input_data) |
|
171 | 170 |
error <- strtoi(response[1]) |
172 | 171 |
data <- response[2] |
173 | 172 |
if(error!=0) |
... | ... |
@@ -15,14 +15,14 @@ |
15 | 15 |
#' @importFrom rJava .jarray |
16 | 16 |
#' @importFrom methods isClass |
17 | 17 |
#' |
18 |
-#' @param x GMQLDataset class object |
|
18 |
+#' @param .data GMQLDataset class object |
|
19 | 19 |
#' @param m_predicate logical predicate made up by R logical operation |
20 | 20 |
#' on metadata attribute. |
21 | 21 |
#' Only !, |, ||, &, && are admitted. |
22 | 22 |
#' @param r_predicate logical predicate made up by R logical operation |
23 | 23 |
#' on chema region values. |
24 | 24 |
#' Only !, |, ||, &, && are admitted. |
25 |
-#' @param semi_join list of CONDITION objects where every object contains |
|
25 |
+#' @param semi_join vector of CONDITION objects where every object contains |
|
26 | 26 |
#' the name of metadata to be used in semijoin, or simple string concatenation |
27 | 27 |
#' of name of metadata, e.g. c("cell_type", "attribute_tag", "size") |
28 | 28 |
#' without declaring condition. |
... | ... |
@@ -35,16 +35,17 @@ |
35 | 35 |
#' as value will match; no further prefixes are allowed. } |
36 | 36 |
#' } |
37 | 37 |
#' Every condition accepts only one string value. (e.g. FULL("cell_type") ) |
38 |
-#' In case of single concatenation with no CONDITION or list with some value |
|
39 |
-#' without conditon, the metadata are considered having default |
|
40 |
-#' evaluation: the two attributes match if both end with value. |
|
38 |
+#' In case of single concatenation with no CONDITION the metadata are |
|
39 |
+#' considered having default evaluation: |
|
40 |
+#' the two attributes match if both end with value. |
|
41 | 41 |
#' |
42 |
-#' @param semi_join_negation logical value: T => semijoin is perfomed |
|
42 |
+#' @param not_in logical value: T => semijoin is perfomed |
|
43 | 43 |
#' considering semi_join NOT IN semi_join_dataset, F => semijoin is performed |
44 | 44 |
#' considering semi_join IN semi_join_dataset |
45 | 45 |
#' |
46 | 46 |
#' @param semi_join_dataset GMQLDataset class object |
47 |
-#' |
|
47 |
+#' @param ... Additional arguments for use in specific methods. |
|
48 |
+#' |
|
48 | 49 |
#' @return GMQLDataset class object. It contains the value to use as input |
49 | 50 |
#' for the subsequent GMQL function |
50 | 51 |
#' |
... | ... |
@@ -56,7 +57,7 @@ |
56 | 57 |
#' init_gmql() |
57 | 58 |
#' test_path <- system.file("example", "DATASET", package = "RGMQL") |
58 | 59 |
#' input <- read_dataset(test_path) |
59 |
-#' s <- subset(input, Patient_age < 70) |
|
60 |
+#' s <- filter(input, Patient_age < 70) |
|
60 | 61 |
#' |
61 | 62 |
#' |
62 | 63 |
#' \dontrun{ |
... | ... |
@@ -84,25 +85,14 @@ |
84 | 85 |
#' |
85 | 86 |
#' } |
86 | 87 |
#' |
87 |
-#' @name filter |
|
88 |
-#' @rdname GMQLDataset-class |
|
89 |
-#' @aliases filter, filter-methods |
|
90 |
-#' |
|
91 |
-setGeneric("filter", function(data, m_predicate = NULL, r_predicate = NULL, |
|
92 |
- semi_join = NULL, semi_join_negation = FALSE, |
|
93 |
- semi_join_dataset = NULL) |
|
94 |
- standardGeneric("filter")) |
|
95 |
- |
|
96 |
-#' @name filter |
|
97 |
-#' @rdname filter-methods |
|
98 |
-#' @aliases filter, filter-methods |
|
88 |
+#' @aliases filter, filter-method |
|
99 | 89 |
#' @export |
100 | 90 |
setMethod("filter", "GMQLDataset", |
101 |
- function(data, m_predicate = NULL, r_predicate = NULL, |
|
102 |
- semi_join = NULL, semi_join_negation = FALSE, |
|
91 |
+ function(.data, m_predicate = NULL, r_predicate = NULL, |
|
92 |
+ semi_join = NULL, not_in = FALSE, |
|
103 | 93 |
semi_join_dataset = NULL) |
104 | 94 |
{ |
105 |
- val <- data@value |
|
95 |
+ val <- .data@value |
|
106 | 96 |
meta_pred <- substitute(m_predicate) |
107 | 97 |
if(!is.null(meta_pred)) |
108 | 98 |
{ |
... | ... |
@@ -122,12 +112,11 @@ setMethod("filter", "GMQLDataset", |
122 | 112 |
region_predicate <- .jnull("java/lang/String") |
123 | 113 |
|
124 | 114 |
gmql_select(val, predicate, region_predicate, |
125 |
- semi_join, semi_join_negation, semi_join_dataset) |
|
115 |
+ semi_join, not_in, semi_join_dataset) |
|
126 | 116 |
}) |
127 | 117 |
|
128 |
-gmql_select <- function(input_data, predicate = NULL, region_predicate = NULL, |
|
129 |
- semi_join = NULL, semi_join_negation = FALSE, |
|
130 |
- semi_join_dataset = NULL) |
|
118 |
+gmql_select <- function(input_data, predicate, region_predicate, semi_join, |
|
119 |
+ semi_join_negation, semi_join_dataset) |
|
131 | 120 |
{ |
132 | 121 |
if(is.null(semi_join) && is.null(semi_join_dataset)) |
133 | 122 |
{ |
... | ... |
@@ -42,9 +42,9 @@ |
42 | 42 |
#' |
43 | 43 |
#' res <- union(data1, data2) |
44 | 44 |
#' |
45 |
-#' @rdname union-method |
|
46 |
-#' @aliases union, union-method |
|
47 |
-#' @export |
|
45 |
+#' @rdname union-GMQLDataset-method |
|
46 |
+#' @aliases union, union-method, |
|
47 |
+#' @export |
|
48 | 48 |
#' |
49 | 49 |
setMethod("union", c("GMQLDataset","GMQLDataset"), |
50 | 50 |
function(x, y) |
... | ... |
@@ -59,11 +59,11 @@ |
59 | 59 |
|
60 | 60 |
|
61 | 61 |
# meta join condition |
62 |
-.join_condition <- function(conditions) |
|
62 |
+.join_condition <- function(cond) |
|
63 | 63 |
{ |
64 |
- if(is.list(conditions)) |
|
64 |
+ if(is.list(cond)) |
|
65 | 65 |
{ |
66 |
- join_condition_matrix <- t(sapply(conditions, function(x) { |
|
66 |
+ join_condition_matrix <- t(sapply(cond, function(x) { |
|
67 | 67 |
new_value = as.character(x) |
68 | 68 |
if(length(new_value)==1) |
69 | 69 |
new_value = c("DEF",new_value) |
... | ... |
@@ -73,15 +73,15 @@ |
73 | 73 |
matrix <- matrix(new_value) |
74 | 74 |
})) |
75 | 75 |
} |
76 |
- else if(is.character(conditions)) |
|
76 |
+ else if(is.character(cond)) |
|
77 | 77 |
{ |
78 |
- conditions = conditions[!conditions %in% ""] |
|
79 |
- conditions = conditions[!duplicated(conditions)] |
|
80 |
- if(length(conditions)<=0) |
|
78 |
+ cond = cond[!cond %in% ""] |
|
79 |
+ cond = cond[!duplicated(cond)] |
|
80 |
+ if(length(cond)<=0) |
|
81 | 81 |
join_condition_matrix <- "" |
82 | 82 |
else |
83 | 83 |
{ |
84 |
- join_condition_matrix <- t(sapply(conditions, function(x) { |
|
84 |
+ join_condition_matrix <- t(sapply(cond, function(x) { |
|
85 | 85 |
new_value = c("DEF",x) |
86 | 86 |
matrix <- matrix(new_value) |
87 | 87 |
})) |
... | ... |
@@ -86,7 +86,7 @@ take_value.META_AGGREGATES <- function(obj){ |
86 | 86 |
#' ## then calculates new metadata attributes for each of them: |
87 | 87 |
#' ## sum_score is the sum of score of the sample regions. |
88 | 88 |
#' |
89 |
-#' res = mutate(input_data = exp, list(sum_score = SUM("score"))) |
|
89 |
+#' res = extend(exp, sum_score = SUM("score")) |
|
90 | 90 |
#' |
91 | 91 |
#' @export |
92 | 92 |
#' |
... | ... |
@@ -128,7 +128,7 @@ SUM <- function(value) |
128 | 128 |
#' ## and then calculates new metadata attributes for each of them: |
129 | 129 |
#' ## MinP is the minimum pvalue of the sample regions. |
130 | 130 |
#' |
131 |
-#' res = mutate(input_data = exp, list(minP = MIN("pvalue"))) |
|
131 |
+#' res = extend(exp, minP = MIN("pvalue")) |
|
132 | 132 |
#' |
133 | 133 |
#' @export |
134 | 134 |
#' |
... | ... |
@@ -171,7 +171,7 @@ MIN <- function(value) |
171 | 171 |
#' ## and then calculates new metadata attributes for each of them: |
172 | 172 |
#' ## max_score is the maximum score of the sample regions. |
173 | 173 |
#' |
174 |
-#' res = mutate(input_data = exp, list(max_score = MAX("score"))) |
|
174 |
+#' res = extend(exp, max_score = MAX("score")) |
|
175 | 175 |
#' |
176 | 176 |
#' |
177 | 177 |
#' @export |
... | ... |
@@ -215,7 +215,7 @@ MAX <- function(value) |
215 | 215 |
#' ## attributes the average signal of the overlapping regions; |
216 | 216 |
#' ## the result has one sample for each input cell. |
217 | 217 |
#' |
218 |
-#' res = cover(input_data = exp,2,3, c("cell"), |
|
218 |
+#' res = cover(exp, 2, 3, c("cell"), |
|
219 | 219 |
#' list(avg_signal = AVG("signal"))) |
220 | 220 |
#' |
221 | 221 |
#' @export |
... | ... |
@@ -259,7 +259,7 @@ AVG <- function(value) |
259 | 259 |
#' ## which is the aggregation comma-separated list of all the values |
260 | 260 |
#' ## that the region attribute score takes in the sample. |
261 | 261 |
#' |
262 |
-#' out = mutate(input_data = data, list(allScore = BAG("score"))) |
|
262 |
+#' out = extend(data, allScore = BAG("score")) |
|
263 | 263 |
#' |
264 | 264 |
#' @export |
265 | 265 |
#' |
... | ... |
@@ -297,7 +297,7 @@ BAG <- function(value) |
297 | 297 |
#' ## counts the regions in each sample and stores their number as value |
298 | 298 |
#' ## of the new metadata RegionCount attribute of the sample. |
299 | 299 |
#' |
300 |
-#' out = mutate(input_data = exp, list(RegionCount = COUNT())) |
|
300 |
+#' out = extend(exp, RegionCount = COUNT()) |
|
301 | 301 |
#' |
302 | 302 |
#' @export |
303 | 303 |
#' |
... | ... |
@@ -342,7 +342,7 @@ check.COUNT <- function(obj){} |
342 | 342 |
#' ## and then calculates new metadata attributes for each of them: |
343 | 343 |
#' ## std_score is the standard deviation score of the sample regions. |
344 | 344 |
#' |
345 |
-#' res = mutate(input_data = exp, list(std_score = STD("score"))) |
|
345 |
+#' res = extend(exp, std_score = STD("score")) |
|
346 | 346 |
#' |
347 | 347 |
#' @export |
348 | 348 |
#' |
... | ... |
@@ -383,7 +383,7 @@ STD <- function(value) |
383 | 383 |
#' ## and then calculates new metadata attributes for each of them: |
384 | 384 |
#' ## m_score is the median score of the sample regions. |
385 | 385 |
#' |
386 |
-#' res = mutate(input_data = exp, list(m_score = MEDIAN("score"))) |
|
386 |
+#' res = extend(exp, m_score = MEDIAN("score")) |
|
387 | 387 |
#' |
388 | 388 |
#' @export |
389 | 389 |
#' |
... | ... |
@@ -424,7 +424,7 @@ MEDIAN <- function(value) |
424 | 424 |
#' ## and then calculates new metadata attributes for each of them: |
425 | 425 |
#' ## q1_score is the first quartile of score of the sample regions. |
426 | 426 |
#' |
427 |
-#' res = mutate(input_data = exp, list(q1_score = Q1("score"))) |
|
427 |
+#' res = extend(exp, q1_score = Q1("score")) |
|
428 | 428 |
#' |
429 | 429 |
#' |
430 | 430 |
#' @export |
... | ... |
@@ -466,7 +466,7 @@ Q1 <- function(value) |
466 | 466 |
#' ## and then calculates new metadata attributes for each of them: |
467 | 467 |
#' ## q2_score is the second quartile of score of the sample regions. |
468 | 468 |
#' |
469 |
-#' res = mutate(input_data = exp, list(q2_score = Q2("score"))) |
|
469 |
+#' res = extend(exp, q2_score = Q2("score")) |
|
470 | 470 |
#' |
471 | 471 |
#' @export |
472 | 472 |
#' |
... | ... |
@@ -506,7 +506,7 @@ Q2 <- function(value) |
506 | 506 |
#' ## and then calculates new metadata attributes for each of them: |
507 | 507 |
#' ## q3_score is the third quartile of score of the sample regions. |
508 | 508 |
#' |
509 |
-#' res = mutate(input_data = exp, list(q3_score = Q3("score"))) |
|
509 |
+#' res = extend(exp, q3_score = Q3("score")) |
|
510 | 510 |
#' |
511 | 511 |
#' @export |
512 | 512 |
#' |
... | ... |
@@ -549,7 +549,7 @@ Q3 <- function(value) |
549 | 549 |
#' ## aggregation comma-separated list of all the distinct values that |
550 | 550 |
#' ## the region attribute score takes in the sample. |
551 | 551 |
#' |
552 |
-#' out = mutate(input_data = data, list(allScore = BAGD("score"))) |
|
552 |
+#' out = extend(data, allScore = BAGD("score")) |
|
553 | 553 |
#' |
554 | 554 |
#' @export |
555 | 555 |
#' |
... | ... |
@@ -32,15 +32,21 @@ if(getRversion() >= "3.1.0") |
32 | 32 |
#' @return None |
33 | 33 |
#' |
34 | 34 |
#' @examples |
35 |
-#' |
|
36 |
-#' ### login as guest |
|
35 |
+#' ## login as guest |
|
37 | 36 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
37 |
+#' \dontrun{ |
|
38 | 38 |
#' login_gmql(remote_url) |
39 |
-#' |
|
39 |
+#' } |
|
40 | 40 |
#' @export |
41 |
-#' |
|
41 |
+ |
|
42 |
+#' |
|
42 | 43 |
login_gmql <- function(url, username = NULL, password = NULL) |
43 | 44 |
{ |
45 |
+ if(exists("authToken",envir = .GlobalEnv)) |
|
46 |
+ { |
|
47 |
+ print("You are already logged") |
|
48 |
+ return(invisible(NULL)) |
|
49 |
+ } |
|
44 | 50 |
as_guest <- TRUE |
45 | 51 |
|
46 | 52 |
if(!is.null(username) || !is.null(password)) |
... | ... |
@@ -77,7 +83,7 @@ login_gmql <- function(url, username = NULL, password = NULL) |
77 | 83 |
#' |
78 | 84 |
#' Logout from GMQL REST services suite |
79 | 85 |
#' using the proper GMQL web service available on a remote server |
80 |
-#' |
|
86 |
+#' |
|
81 | 87 |
#' @import httr |
82 | 88 |
#' @importFrom rJava J |
83 | 89 |
#' |
... | ... |
@@ -92,12 +98,12 @@ login_gmql <- function(url, username = NULL, password = NULL) |
92 | 98 |
#' If error occures a specific error is printed |
93 | 99 |
#' |
94 | 100 |
#' @examples |
95 |
-#' |
|
96 |
-#' #### login as guest, then logout |
|
101 |
+#' #' ## login as guest, then logout |
|
97 | 102 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
103 |
+#' \dontrun{ |
|
98 | 104 |
#' login_gmql(remote_url) |
99 | 105 |
#' logout_gmql(remote_url) |
100 |
-#' |
|
106 |
+#' } |
|
101 | 107 |
#' @return None |
102 | 108 |
#' |
103 | 109 |
#' @export |
... | ... |
@@ -2,7 +2,7 @@ |
2 | 2 |
#' |
3 | 3 |
#' It shows all the GMQL query saved on repository |
4 | 4 |
#' using the proper GMQL web service available on a remote server |
5 |
-#' |
|
5 |
+#' |
|
6 | 6 |
#' @import httr |
7 | 7 |
#' |
8 | 8 |
#' @param url string url of server: It must contain the server address |
... | ... |
@@ -19,13 +19,13 @@ |
19 | 19 |
#' @details |
20 | 20 |
#' if error occures, a specific error is printed |
21 | 21 |
#' |
22 |
-#' @examples |
|
23 |
-#' |
|
22 |
+#' @examples |
|
24 | 23 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
25 | 24 |
#' |
25 |
+#' \dontrun{ |
|
26 | 26 |
#' login_gmql(remote_url) |
27 | 27 |
#' list <- show_queries_list(remote_url) |
28 |
-#' |
|
28 |
+#' } |
|
29 | 29 |
#' @export |
30 | 30 |
#' |
31 | 31 |
show_queries_list <- function(url) |
... | ... |
@@ -44,7 +44,7 @@ show_queries_list <- function(url) |
44 | 44 |
#' |
45 | 45 |
#' It saves the GMQL query into repository |
46 | 46 |
#' using the proper GMQL web service available on a remote server |
47 |
-#' |
|
47 |
+#' |
|
48 | 48 |
#' @import httr |
49 | 49 |
#' |
50 | 50 |
#' @param url string url of server: It must contain the server address |
... | ... |
@@ -63,12 +63,13 @@ show_queries_list <- function(url) |
63 | 63 |
#' if no error occures print "Saved" otherwise print the content error |
64 | 64 |
#' |
65 | 65 |
#' @examples |
66 |
-#' |
|
67 | 66 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
67 |
+#' \dontrun{ |
|
68 |
+#' |
|
68 | 69 |
#' login_gmql(remote_url) |
69 | 70 |
#' save_query(remote_url, "dna_query", "DATASET = SELECT() HG19_TCGA_dnaseq; |
70 | 71 |
#' MATERIALIZE DATASET INTO RESULT_DS;") |
71 |
-#' |
|
72 |
+#' } |
|
72 | 73 |
#' @export |
73 | 74 |
#' |
74 | 75 |
save_query <- function(url, queryName, queryTxt) |
... | ... |
@@ -90,7 +91,8 @@ save_query <- function(url, queryName, queryTxt) |
90 | 91 |
#' It saves the GMQL query into repository taken from file |
91 | 92 |
#' using the proper GMQL web service available on a remote server |
92 | 93 |
#' |
93 |
-#' |
|
94 |
+#' |
|
95 |
+#' |
|
94 | 96 |
#' @param url string url of server: It must contain the server address |
95 | 97 |
#' and base url; service name is added automatically |
96 | 98 |
#' @param queryName string name of the GMQL query |
... | ... |
@@ -106,14 +108,14 @@ save_query <- function(url, queryName, queryTxt) |
106 | 108 |
#' if no error occures print "Saved" otherwise print the content error |
107 | 109 |
#' |
108 | 110 |
#' @examples |
109 |
-#' |
|
110 | 111 |
#' test_path <- system.file("example", package = "RGMQL") |
111 | 112 |
#' test_query <- file.path(test_path, "query1.txt") |
112 |
-#' |
|
113 | 113 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
114 |
+#' \dontrun{ |
|
115 |
+#' |
|
114 | 116 |
#' login_gmql(remote_url) |
115 | 117 |
#' save_query_fromfile(remote_url, "query1", test_query) |
116 |
-#' |
|
118 |
+#' } |
|
117 | 119 |
#' @export |
118 | 120 |
#' |
119 | 121 |
save_query_fromfile <- function(url, queryName, filePath) |
... | ... |
@@ -22,13 +22,16 @@ print.CONDITION <- function(obj){ |
22 | 22 |
} |
23 | 23 |
|
24 | 24 |
c.CONDITION <- function(...){ |
25 |
- a <- list(...) |
|
25 |
+ cond <- list(...) |
|
26 | 26 |
} |
27 | 27 |
|
28 | 28 |
check.CONDITION <- function(value) |
29 | 29 |
{ |
30 |
- if(!is.character(value) || length(value)>1) |
|
31 |
- stop("value: no valid input or length > 1") |
|
30 |
+ if(is.character(value) && length(value)>1) |
|
31 |
+ stop("value: no multiple string") |
|
32 |
+ |
|
33 |
+ if(!is.character(value)) |
|
34 |
+ stop("value: is not a string") |
|
32 | 35 |
} |
33 | 36 |
|
34 | 37 |
|
... | ... |
@@ -40,7 +40,7 @@ print.PARAMETER <- function(obj){ |
40 | 40 |
#' init_gmql() |
41 | 41 |
#' test_path <- system.file("example", "DATASET", package = "RGMQL") |
42 | 42 |
#' exp = read_dataset(test_path) |
43 |
-#' res = cover(input_data = exp, 2, ALL()) |
|
43 |
+#' res = cover(exp, 2, "ALL") |
|
44 | 44 |
#' |
45 | 45 |
#' @export |
46 | 46 |
#' |
... | ... |
@@ -72,8 +72,8 @@ ALL <- function() |
72 | 72 |
#' |
73 | 73 |
#' init_gmql() |
74 | 74 |
#' test_path <- system.file("example", "DATASET", package = "RGMQL") |
75 |
-#' exp = read_dataset(test_path) |
|
76 |
-#' res = cover(input_data = exp, 2, ANY()) |
|
75 |
+#' dataset = read_dataset(test_path) |
|
76 |
+#' res = cover(dataset, 2, "ANY") |
|
77 | 77 |
#' |
78 | 78 |
#' |
79 | 79 |
#' @export |
... | ... |
@@ -2,7 +2,8 @@ |
2 | 2 |
#' |
3 | 3 |
#' It show all GMQL dataset stored in repository using the proper GMQL |
4 | 4 |
#' web service available on a remote server |
5 |
-#' |
|
5 |
+#' |
|
6 |
+#' |
|
6 | 7 |
#' @import httr |
7 | 8 |
#' @param url single string url of server: It must contain the server address |
8 | 9 |
#' and base url; service name is added automatically |
... | ... |
@@ -21,13 +22,13 @@ |
21 | 22 |
#' If error occures a specific error is printed |
22 | 23 |
#' |
23 | 24 |
#' @examples |
24 |
-#' |
|
25 |
-#' ## show dataset when logged as guest |
|
26 | 25 |
#' |
27 |
-#' remote_url <- "http://130.186.13.219/gmql-rest" |
|
26 |
+#' @examples |
|
27 |
+#' remote_url = "http://130.186.13.219/gmql-rest" |
|
28 |
+#' \dontrun{ |
|
28 | 29 |
#' login_gmql(remote_url) |
29 | 30 |
#' list <- show_datasets_list(remote_url) |
30 |
-#' |
|
31 |
+#' } |
|
31 | 32 |
#' @export |
32 | 33 |
#' |
33 | 34 |
show_datasets_list <- function(url) |
... | ... |
@@ -47,7 +48,7 @@ show_datasets_list <- function(url) |
47 | 48 |
#' |
48 | 49 |
#' It show all sample from a specific GMQL dataset using the proper |
49 | 50 |
#' GMQL web service available on a remote server |
50 |
-#' |
|
51 |
+#' |
|
51 | 52 |
#' @import httr |
52 | 53 |
#' |
53 | 54 |
#' @param url string url of server: It must contain the server address |
... | ... |
@@ -69,11 +70,11 @@ show_datasets_list <- function(url) |
69 | 70 |
#' If error occures a specific error is printed |
70 | 71 |
#' |
71 | 72 |
#' @examples |
72 |
-#' |
|
73 |
-#' remote_url <- "http://130.186.13.219/gmql-rest" |
|
73 |
+#' remote_url = "http://130.186.13.219/gmql-rest" |
|
74 |
+#' \dontrun{ |
|
74 | 75 |
#' login_gmql(remote_url) |
75 | 76 |
#' list <- show_samples_list(remote_url, "public.HG19_BED_ANNOTATION") |
76 |
-#' |
|
77 |
+#' } |
|
77 | 78 |
#' @export |
78 | 79 |
#' |
79 | 80 |
show_samples_list <- function(url,datasetName) |
... | ... |
@@ -93,7 +94,7 @@ show_samples_list <- function(url,datasetName) |
93 | 94 |
#' |
94 | 95 |
#' It shows the region attribute schema of a specific GMQL dataset using |
95 | 96 |
#' the proper GMQL web service available on a remote server |
96 |
-#' |
|
97 |
+#' |
|
97 | 98 |
#' @import httr |
98 | 99 |
#' @param url string url of server: It must contain the server address |
99 | 100 |
#' and base url; service name is added automatically |
... | ... |
@@ -114,12 +115,11 @@ show_samples_list <- function(url,datasetName) |
114 | 115 |
#' |
115 | 116 |
#' |
116 | 117 |
#' @examples |
117 |
-#' |
|
118 |
-#' ### show schema of public dataset |
|
119 |
-#' remote_url <- "http://130.186.13.219/gmql-rest" |
|
118 |
+#' remote_url = "http://130.186.13.219/gmql-rest" |
|
119 |
+#' \dontrun{ |
|
120 | 120 |
#' login_gmql(remote_url) |
121 | 121 |
#' list <- show_schema(remote_url, "public.HG19_BED_ANNOTATION") |
122 |
-#' |
|
122 |
+#'} |
|
123 | 123 |
#' @export |
124 | 124 |
#' |
125 | 125 |
show_schema <- function(url,datasetName) |
... | ... |
@@ -142,8 +142,7 @@ show_schema <- function(url,datasetName) |
142 | 142 |
#' It uploads a folder (GMQL or not) containing sample files using |
143 | 143 |
#' the proper GMQL web service available on a remote server: |
144 | 144 |
#' a new dataset is created on repository |
145 |
-#' |
|
146 |
-#' |
|
145 |
+#' |
|
147 | 146 |
#' @param url string url of server: It must contain the server address |
148 | 147 |
#' and base url; service name is added automatically |
149 | 148 |
#' @param datasetName name of dataset to get |
... | ... |
@@ -259,7 +258,7 @@ upload_dataset <- function(url,datasetName,folderPath,schemaName=NULL, |
259 | 258 |
#' |
260 | 259 |
#' It deletes single private dataset specified by name from repository |
261 | 260 |
#' using the proper GMQL web service available on a remote server |
262 |
-#' |
|
261 |
+#' |
|
263 | 262 |
#' @import httr |
264 | 263 |
#' |
265 | 264 |
#' @param url string url of server: It must contain the server address |
... | ... |
@@ -279,7 +278,7 @@ upload_dataset <- function(url,datasetName,folderPath,schemaName=NULL, |
279 | 278 |
#' |
280 | 279 |
#' \dontrun{ |
281 | 280 |
#' |
282 |
-#' ### This dataset does not exist |
|
281 |
+#' ## This dataset does not exist |
|
283 | 282 |
#' |
284 | 283 |
#' remote_url <- "http://130.186.13.219/gmql-rest" |
285 | 284 |
#' login_gmql(remote_url) |
... | ... |
@@ -306,7 +305,7 @@ delete_dataset <- function(url,datasetName) |
306 | 305 |
#' |
307 | 306 |
#' It donwloads private dataset as zip file from repository to local path |
308 | 307 |
#' specified using the proper GMQL web service available on a remote server |
309 |
-#' |
|
308 |
+#' |
|
310 | 309 |
#' @import httr |
311 | 310 |
#' @importFrom utils unzip |
312 | 311 |
#' |
... | ... |
@@ -323,13 +322,15 @@ delete_dataset <- function(url,datasetName) |
323 | 322 |
#' |
324 | 323 |
#' @examples |
325 | 324 |
#' |
326 |
-#' #### download dataset in r working directory |
|
327 |
-#' #### in this case we try to download public dataset |
|
325 |
+#' ## download dataset in r working directory |
|
326 |
+#' ## in this case we try to download public dataset |
|
327 |
+#' |
|
328 |
+#' \dontrun{ |
|
328 | 329 |
#' |
329 | 330 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
330 | 331 |
#' login_gmql(remote_url) |
331 | 332 |
#' download_dataset(remote_url, "public.HG19_BED_ANNOTATION", path = getwd()) |
332 |
-#' |
|
333 |
+#' } |
|
333 | 334 |
#' @export |
334 | 335 |
#' |
335 | 336 |
download_dataset <- function(url,datasetName,path = getwd()) |
... | ... |
@@ -355,7 +356,7 @@ download_dataset <- function(url,datasetName,path = getwd()) |
355 | 356 |
#' |
356 | 357 |
#' It donwloads private dataset from repository saving into R environemnt |
357 | 358 |
#' as GrangesList |
358 |
-#' |
|
359 |
+#' |
|
359 | 360 |
#' @import httr |
360 | 361 |
#' @importClassesFrom GenomicRanges GRangesList |
361 | 362 |
#' @importFrom S4Vectors metadata |
... | ... |
@@ -415,7 +416,7 @@ download_as_GRangesList <- function(url,datasetName) |
415 | 416 |
#' |
416 | 417 |
#' It retrieves metadata for a specific sample in dataset using the proper |
417 | 418 |
#' GMQL web service available on a remote server |
418 |
-#' |
|
419 |
+#' |
|
419 | 420 |
#' @import httr |
420 | 421 |
#' |
421 | 422 |
#' @param url string url of server: It must contain the server address |
... | ... |
@@ -429,12 +430,11 @@ download_as_GRangesList <- function(url,datasetName) |
429 | 430 |
#' If error occures a specific error is printed |
430 | 431 |
#' |
431 | 432 |
#' @examples |
432 |
-#' |
|
433 |
-#' ## download metadata with real test login |
|
434 | 433 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
434 |
+#' \dontrun{ |
|
435 | 435 |
#' login_gmql(remote_url) |
436 | 436 |
#' sample_metadata(remote_url, "public.HG19_BED_ANNOTATION", "genes") |
437 |
-#' |
|
437 |
+#'} |
|
438 | 438 |
#' @export |
439 | 439 |
#' |
440 | 440 |
sample_metadata <- function(url, datasetName,sampleName) |
... | ... |
@@ -459,14 +459,13 @@ sample_metadata <- function(url, datasetName,sampleName) |
459 | 459 |
|
460 | 460 |
|
461 | 461 |
#' Shows regions from a dataset sample |
462 |
-#' |
|
463 |
-#' |
|
462 |
+#' |
|
464 | 463 |
#' It retrieves regions for a specific sample |
465 | 464 |
#' (whose name is specified in the paramter "sampleName") |
466 | 465 |
#' in a specific dataset |
467 | 466 |
#' (whose name is specified in the parameter "datasetName") |
468 | 467 |
#' using the proper GMQL web service available on a remote server |
469 |
-#' |
|
468 |
+#' |
|
470 | 469 |
#' @import httr |
471 | 470 |
#' @importFrom rtracklayer import |
472 | 471 |
#' @importFrom data.table fread |
... | ... |
@@ -484,12 +483,11 @@ sample_metadata <- function(url, datasetName,sampleName) |
484 | 483 |
#' If error occures a specific error is printed |
485 | 484 |
#' |
486 | 485 |
#' @examples |
487 |
-#' |
|
488 |
-#' |
|
489 | 486 |
#' remote_url = "http://130.186.13.219/gmql-rest" |
487 |
+#' \dontrun{ |
|
490 | 488 |
#' login_gmql(remote_url) |
491 | 489 |
#' sample_region(remote_url, "public.HG19_BED_ANNOTATION", "genes") |
492 |
-#' |
|
490 |
+#' } |
|
493 | 491 |
#' |
494 | 492 |
#' @export |
495 | 493 |
#' |
... | ... |
@@ -58,14 +58,7 @@ as.character.OPERATOR <- function(obj) { |
58 | 58 |
#' init_gmql() |
59 | 59 |
#' test_path <- system.file("example", "DATASET", package = "RGMQL") |
60 | 60 |
#' exp = read_dataset(test_path) |
61 |
-#' data = filter(exp, region_predicate = score > META("avg_score")); |
|
62 |
-#' |
|
63 |
-#' |
|
64 |
-#' ## It define a new region attribute with the value of a metadata attribute |
|
65 |
-#' ## using the syntax region_attribute AS META(metadata_attribute, type) |
|
66 |
-#' |
|
67 |
-#' out = subset(exp, regions_update = list(signal = META("avg_signal", |
|
68 |
-#' "DOUBLE"))) |
|
61 |
+#' data = filter(exp, r_predicate = score > META("avg_score")) |
|
69 | 62 |
#' |
70 | 63 |
#' |
71 | 64 |
#' @export |
... | ... |
@@ -21,12 +21,12 @@ check.ORDER <- function(value) |
21 | 21 |
} |
22 | 22 |
|
23 | 23 |
print.ORDER <- function(obj) { |
24 |
- as.character(obj) |
|
24 |
+ as.character(as.character.ORDER(obj)) |
|
25 | 25 |
} |
26 | 26 |
|
27 |
-c.ORDER <- function(...) { |
|
28 |
- a <- list(...) |
|
29 |
-} |
|
27 |
+#c.ORDER <- function(...) { |
|
28 |
+# a <- list(...) |
|
29 |
+#} |
|
30 |