repair readme

README.Rmd

@@ -164,7 +164,7 @@ sample_data(dietswap)$african[c(3, 4)] <- NA
 You have quite a few samples in your phyloseq object, and would like to visualize their compositions.
 Perhaps these example data differ participant nationality?
 
-```{r fig.height=5, fig.width=6, dpi=120}
+```{r, bars, fig.height=5, fig.width=6, dpi=120}
 dietswap %>%
   comp_barplot(
     tax_level = "Genus", n_taxa = 15, other_name = "Other",
@@ -178,7 +178,7 @@ dietswap %>%
   theme(axis.text.y = element_blank(), axis.ticks.y = element_blank())
 ```
 
-```{r, fig.width=5.5, fig.height=3.5, dpi=120}
+```{r, compheatmap, fig.width=5.5, fig.height=3.5, dpi=120}
 htmp <- dietswap %>%
   ps_mutate(nationality = as.character(nationality)) %>%
   tax_transform("log2", add = 1, chain = TRUE) %>%
@@ -307,7 +307,7 @@ perm2 %>%
 
 microViz heatmaps are powered by `ComplexHeatmap` and annotated with taxa prevalence and/or abundance.
 
-```{r heatmap, dpi=120, fig.width=7, fig.height=5.5}
+```{r, corheatmap, dpi=120, fig.width=7, fig.height=5.5}
 # set up the data with numerical variables and filter to top taxa
 psq <- dietswap %>%
   ps_mutate(

README.md

@@ -217,7 +217,7 @@ dietswap %>%
 #>   reorder.hclust vegan
 ```
 
-<img src="man/figures/README-unnamed-chunk-3-1.png" width="100%" />
+<img src="man/figures/README-bars-1.png" width="100%" />
 
 ``` r
 htmp <- dietswap %>%
@@ -242,7 +242,7 @@ ComplexHeatmap::draw(
 )
 ```
 
-<img src="man/figures/README-unnamed-chunk-4-1.png" width="100%" />
+<img src="man/figures/README-compheatmap-1.png" width="100%" />
 
 ### Example ordination plot workflow
 
@@ -321,8 +321,8 @@ aitchison_perm <- aitchison_dists %>%
     n_processes = 1, n_perms = 99, # you should use at least 999!
     variables = "bmi_group"
   )
-#> 2022-10-04 13:58:03 - Starting PERMANOVA with 99 perms with 1 processes
-#> 2022-10-04 13:58:03 - Finished PERMANOVA
+#> 2022-10-04 14:23:48 - Starting PERMANOVA with 99 perms with 1 processes
+#> 2022-10-04 14:23:48 - Finished PERMANOVA
 
 # view the permanova results
 perm_get(aitchison_perm) %>% as.data.frame()
@@ -353,8 +353,8 @@ your permanova directly using the `ord_plot` function with constraints
 perm2 <- aitchison_dists %>% 
   dist_permanova(variables = c("weight", "african", "sex"), seed = 321)
 #> Dropping samples with missings: 2
-#> 2022-10-04 13:58:03 - Starting PERMANOVA with 999 perms with 1 processes
-#> 2022-10-04 13:58:05 - Finished PERMANOVA
+#> 2022-10-04 14:23:48 - Starting PERMANOVA with 999 perms with 1 processes
+#> 2022-10-04 14:23:50 - Finished PERMANOVA
 ```
 
 We’ll visualise the effect of nationality and bodyweight on sample
@@ -418,7 +418,7 @@ cor_heatmap(
 )
 ```
 
-<img src="man/figures/README-heatmap-1.png" width="100%" />
+<img src="man/figures/README-corheatmap-1.png" width="100%" />
 
 ## Citation