update WhatsNew

aljabadi · Jul 14, 2021 · 6f4924b · 6f4924b
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diff --git a/README.md b/README.md
@@ -249,10 +249,20 @@ Thank you for using `mixOmics`!
 
 ## What’s New
 
-#### Septermber 2020
-
--   New biplot now available for `pca` family. See the examples in [this
-    issue](https://github.com/mixOmicsTeam/mixOmics/issues/90)
+#### July 2021
+
+-   `tune.spls` now able to tune the selected variables on both `X` and
+    `Y`. See `?tune.spls`
+-   new function `impute.nipals` to impute missing values using the
+    nipals algorithm
+-   new function `tune.spca` to tune the number of selected variables
+    for pca components
+-   `circosPlot` now has methods for `block.spls` objects. It can now
+    handle similar feature names across blocks. It is also much more
+    customisable. See advanced arguments in `?circosPlot`
+-   new `biplot` function for `pca` and `pls` objects. See
+    `?mixOmics::biplot`
+-   `plotDiablo` now takes `col.per.group` (see \#119)
 
 #### April 2020
 
@@ -272,21 +282,3 @@ Thank you for using `mixOmics`!
 -   `perf.block.splsda` now supports calculation of combined AUC
 -   `block.splsda` bug which could drop some classes with
     `near.zero.variance=TRUE` now fixed
-
-#### November 2019
-
--   Parallel computing improved for `tune` and `perf` functions, and
-    even more on Unix-like systems
-
--   Fixed margin error problem with `plotLoadings`. See the example in
-    [this issue](https://github.com/mixOmicsTeam/mixOmics/issues/45)
-
--   `cim` bug which overestimated correlations for single component now
-    fixed
-
--   `perf.sgccda` now supports calculation of average combined AUC
-
-#### September 2019
-
--   You can now customise `auroc` plots in version 6.8.3. See example
-    [here](https://github.com/mixOmicsTeam/mixOmics/issues/35)
diff --git a/inst/README-WhatsNew.Rmd b/inst/README-WhatsNew.Rmd
@@ -17,9 +17,14 @@ opts_chunk$set( echo = TRUE, eval = FALSE, warning = FALSE, message = FALSE)
 
 ## What's New
 
-#### Septermber 2020
+#### July 2021
 
-* New biplot now available for `pca` family. See the examples in [this issue](https://github.com/mixOmicsTeam/mixOmics/issues/90)
+* `tune.spls` now able to tune the selected variables on both `X` and `Y`. See `?tune.spls`
+* new function `impute.nipals` to impute missing values using the nipals algorithm
+* new function `tune.spca` to tune the number of selected variables for pca components
+* `circosPlot` now has methods for `block.spls` objects. It can now handle similar feature names across blocks. It is also much more customisable. See advanced arguments in `?circosPlot`
+* new `biplot` function for `pca` and `pls` objects. See `?mixOmics::biplot`
+* `plotDiablo` now takes `col.per.group` (see #119)
 
 #### April 2020
 
@@ -28,86 +33,9 @@ opts_chunk$set( echo = TRUE, eval = FALSE, warning = FALSE, message = FALSE)
 #### March 2020
 
 * `plotIndiv` now supports (weighted) consensus plots for block analyses. See the example in [this issue](https://github.com/mixOmicsTeam/mixOmics/issues/57)
-
 * `plotIndiv(..., ind.names=FALSE)` [warning issue](https://github.com/mixOmicsTeam/mixOmics/issues/59) now fixed
 
 #### January 2020
 
 * `perf.block.splsda` now supports calculation of combined AUC
 * `block.splsda` bug which could drop some classes with `near.zero.variance=TRUE` now fixed
-
-#### November 2019
-
-* Parallel computing improved for `tune` and `perf` functions, and even more on Unix-like systems
-```{r, eval=FALSE, echo=FALSE}
-library(mixOmics)
-require(microbenchmark)
-require(parallel)
-data(nutrimouse)
-nrep <- 25
-folds <- 2
-Y = nutrimouse$diet
-data = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid)
-design = matrix(c(0,1,1,1,0,1,1,1,0), ncol = 3, nrow = 3, byrow = TRUE)
-
-nutrimouse.sgccda <- block.splsda(X=data,
-                                  Y = Y,
-                                  design = design,
-                                  keepX = list(gene=c(10,10), lipid=c(15,15)),
-                                  ncomp = 2,
-                                  scheme = "horst")
-microbenchmark::microbenchmark(
-  serial =  perf(nutrimouse.sgccda, folds = folds, nrepeat = nrep),
-  parallel =  perf(nutrimouse.sgccda, folds = folds, nrepeat = nrep, cpus = parallel::detectCores()), times = 2
-)
-#> Unit: seconds
-#>      expr      min       lq      mean    median        uq       max neval
-#>    serial 10.09760 10.09760 12.130116 12.130116 14.162629 14.162629     2
-#>  parallel  5.62336  5.62336  5.756024  5.756024  5.888689  5.888689     2
-```
-* Fixed margin error problem with `plotLoadings`. See the example in [this issue](https://github.com/mixOmicsTeam/mixOmics/issues/45)
-
-* `cim` bug which overestimated correlations for single component now fixed
-
-* `perf.sgccda` now supports calculation of average combined AUC
-```{r, eval=FALSE, echo=FALSE}
-library(mixOmics)
-data(nutrimouse)
-nrep <- 4
-folds <- 4
-Y = nutrimouse$diet
-data = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid)
-design = matrix(c(0,1,1,1,0,1,1,1,0), ncol = 3, nrow = 3, byrow = TRUE)
-set.seed(42)
-nutrimouse.sgccda <- block.splsda(X=data,
-                                  Y = Y,
-                                  design = design,
-                                  keepX = list(gene=c(10,10), lipid=c(15,15)),
-                                  ncomp = 2)
-
-perf.res <- perf(nutrimouse.sgccda, folds = folds, nrepeat = nrep, 
-     auc = TRUE, cpus = parallel::detectCores())
-
-perf.res$auc
-#> $comp1
-#>                        AUC   p-value
-#> coc vs Other(s)  0.8769531 0.2125844
-#> fish vs Other(s) 0.6914062 0.4333581
-#> lin vs Other(s)  0.5449219 0.5615303
-#> ref vs Other(s)  0.5000000 0.5086909
-#> sun vs Other(s)  0.6640625 0.4005816
-#> 
-#> $comp2
-#>                        AUC   p-value
-#> coc vs Other(s)  0.9179688 0.1401584
-#> fish vs Other(s) 0.8164062 0.2083663
-#> lin vs Other(s)  0.7089844 0.3245500
-#> ref vs Other(s)  0.5800781 0.4885250
-#> sun vs Other(s)  0.9238281 0.1132753
-```
-
-#### September 2019
-
-* You can now customise `auroc` plots in version 6.8.3. See example [here](https://github.com/mixOmicsTeam/mixOmics/issues/35)
-
-