wis

Author: WisamSaleem

Atlas.html

@@ -121,7 +121,7 @@ df <- meta(pseq) %>% arrange(time)
 beta <- c() # Baseline similarity
 s0 <- subset(df, time == 0)$sample
 # Let us transform to relative abundance for Bray-Curtis calculations
-a <- abundances(transform(pseq, "compositional")) 
+a <-microbiome::abundances(microbiome::transform(pseq, "compositional")) 
 for (tp in df$time[-1]) {
   # Pick the samples for this subject
   # If the same time point has more than one sample,

Betadiversity.Rmd

@@ -95,7 +95,7 @@ For examples on tipping point detection, see
 [Stability](Stability). We set the tipping point manually in the
 following example.
 
-```{r stability-variationplot, message=FALSE, warning=FALSE, fig.show='hold', out.width="430px"}
+```{r stability-variationplot, message=FALSE, warning=FALSE, fig.show='hold', out.width="430px", eval=FALSE}
 # Bimodality hotplot:
 # Consider a unique sample from each subject: the baseline time point 
 p <- hotplot(pseq0, tax, tipping.point = 0.005)

Betadiversity.html

@@ -76,8 +76,8 @@ bic  <- sapply(fit, BIC) # AIC / BIC / Laplace
 
 Pick the optimal model
 
-```{r DMM3, fig.width=6, fig.height=5, warning=FALSE, message=FALSE, eval=TRUE}
-best <- fit[[which.min(lplc)]]
+```{r DMM3, fig.width=6, fig.height=5, warning=FALSE, message=FALSE,error=FALSE, eval=FALSE}
+best <- fit[[which.min(unlist(lplc))]]
 ```
 
 Mixture parameters pi and theta

Bimodality.Rmd

@@ -41,7 +41,7 @@ pseq <- dietswap
 A comprehensive list of global indicators of the ecosystem state can be obtained as follows. This includes various measures of richness, evenness, diversity, dominance, and rarity with default parameters. See the individual functions for more options regarding parameter tuning.
 
 ```{r alpha, warning=FALSE, message=FALSE, fig.height=3, fig.width=5, results="asis"}
-tab <- alpha(pseq, index = "all")
+tab <-microbiome::alpha(pseq, index = "all")
 kable(head(tab))
 ```
 
@@ -51,7 +51,7 @@ kable(head(tab))
 This returns a table with selected diversity indicators. See a separate page on [Beta diversity](Betadiversity.html).
 
 ```{r alpha2, warning=FALSE, message=FALSE, fig.height=3, fig.width=5, results="asis"}
-tab <- alpha(pseq, index = "all")
+tab <-microbiome::alpha(pseq, index = "all")
 kable(head(tab))
 ```
 

Bimodality.html

@@ -9,9 +9,9 @@
 <meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
 
 
-<meta name="author" content="Leo Lahti, Sudarshan Shetty et al. 2020-05-25" />
+<meta name="author" content="Leo Lahti, Sudarshan Shetty et al. 2020-06-12" />
 
-<meta name="date" content="2020-05-25" />
+<meta name="date" content="2020-06-12" />
 
 <title>Diversity</title>
 
@@ -1912,8 +1912,8 @@
 
 
 <h1 class="title toc-ignore">Diversity</h1>
-<p class="author-name">Leo Lahti, Sudarshan Shetty et al. 2020-05-25</p>
-<h4 class="date">25 May 2020</h4>
+<p class="author-name">Leo Lahti, Sudarshan Shetty et al. 2020-06-12</p>
+<h4 class="date">12 June 2020</h4>
 
 </div>
 
@@ -1935,7 +1935,7 @@ <h2>Global Ecosystem State Variables</h2>
 <div id="global-indicators" class="section level2">
 <h2>Global indicators</h2>
 <p>A comprehensive list of global indicators of the ecosystem state can be obtained as follows. This includes various measures of richness, evenness, diversity, dominance, and rarity with default parameters. See the individual functions for more options regarding parameter tuning.</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" title="1">tab &lt;-<span class="st"> </span><span class="kw">alpha</span>(pseq, <span class="dt">index =</span> <span class="st">&quot;all&quot;</span>)</a>
+<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb2-1" title="1">tab &lt;-microbiome<span class="op">::</span><span class="kw">alpha</span>(pseq, <span class="dt">index =</span> <span class="st">&quot;all&quot;</span>)</a>
 <a class="sourceLine" id="cb2-2" title="2"><span class="kw">kable</span>(<span class="kw">head</span>(tab))</a></code></pre></div>
 <div class='horizontal-scroll'><table>
 <thead>
@@ -2122,7 +2122,7 @@ <h2>Global indicators</h2>
 <div id="alpha-diversity" class="section level2">
 <h2>Alpha diversity</h2>
 <p>This returns a table with selected diversity indicators. See a separate page on <a href="Betadiversity.html">Beta diversity</a>.</p>
-<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">tab &lt;-<span class="st"> </span><span class="kw">alpha</span>(pseq, <span class="dt">index =</span> <span class="st">&quot;all&quot;</span>)</a>
+<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb3-1" title="1">tab &lt;-microbiome<span class="op">::</span><span class="kw">alpha</span>(pseq, <span class="dt">index =</span> <span class="st">&quot;all&quot;</span>)</a>
 <a class="sourceLine" id="cb3-2" title="2"><span class="kw">kable</span>(<span class="kw">head</span>(tab))</a></code></pre></div>
 <div class='horizontal-scroll'><table>
 <thead>

Clustering.html

@@ -327,8 +327,8 @@ Long tails of rare taxa:
 ```{r tail, warning=FALSE, message=print, fig.width=16, fig.height=8, out.width="200px"}
 medians <- apply(abundances(d),1,median)/1e3
 library(reshape2)
-A <- melt(abundances(d))
-A$Var1 <- factor(A$Var1, levels = rev(names(sort(medians))))
+A <- melt(microbiome::abundances(d))
+A$Var1 <- factor(A$X1, levels = rev(names(sort(medians))))
 p <- ggplot(A, aes(x = Var1, y = value)) +
         geom_boxplot() +
 	labs(y = "Abundance (reads)", x = "Taxonomic Group") +