forked from vincentarelbundock/Rdatasets
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathmetals.html
92 lines (60 loc) · 3.12 KB
/
metals.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><title>R: Data from heavy metal mixture experiments</title>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes" />
<link rel="stylesheet" type="text/css" href="R.css" />
</head><body><div class="container">
<table width="100%" summary="page for metals"><tr><td>metals</td><td style="text-align: right;">R Documentation</td></tr></table>
<h2>
Data from heavy metal mixture experiments
</h2>
<h3>Description</h3>
<p>Data are from a study of the response of the cyanobacterial self-luminescent metallothionein-based whole-cell biosensor Synechoccocus elongatus PCC 7942 pBG2120 to binary mixtures of 6 heavy metals (Zn, Cu, Cd, Ag, Co and Hg).
</p>
<h3>Usage</h3>
<pre>data("metals")</pre>
<h3>Format</h3>
<p>A data frame with 543 observations on the following 3 variables.
</p>
<dl>
<dt><code>metal</code></dt><dd><p>a factor with levels <code>Ag</code> <code>AgCd</code> <code>Cd</code> <code>Co</code> <code>CoAg</code> <code>CoCd</code> <code>Cu</code> <code>CuAg</code> <code>CuCd</code> <code>CuCo</code> <code>CuHg</code> <code>CuZn</code> <code>Hg</code> <code>HgCd</code> <code>HgCo</code> <code>Zn</code> <code>ZnAg</code> <code>ZnCd</code> <code>ZnCo</code> <code>ZnHg</code></p>
</dd>
<dt><code>conc</code></dt><dd><p>a numeric vector of concentrations</p>
</dd>
<dt><code>BIF</code></dt><dd><p>a numeric vector of luminescence induction factors</p>
</dd>
</dl>
<h3>Details</h3>
<p>Data are from the study described by Martin-Betancor et al. (2015).
</p>
<h3>Source</h3>
<p>Martin-Betancor, K. and Ritz, C. and Fernandez-Pinas, F. and Leganes, F. and Rodea-Palomares, I. (2015)
Defining an additivity framework for mixture research in inducible whole-cell biosensors,
<em>Scientific Reports</em>
<b>17200</b>.</p>
<h3>Examples</h3>
<pre>
## One example from the paper by Martin-Betancor et al (2015)
## Figure 2
## Fitting a model for "Zn"
Zn.lgau <- drm(BIF ~ conc, data = subset(metals, metal == "Zn"),
fct = lgaussian(), bcVal = 0, bcAdd = 10)
## Plotting data and fitted curve
plot(Zn.lgau, log = "", type = "all",
xlab = expression(paste(plain("Zn")^plain("2+"), " ", mu, "", plain("M"))))
## Calculating effective doses
ED(Zn.lgau, 50, interval = "delta")
ED(Zn.lgau, -50, interval = "delta", bound = FALSE)
ED(Zn.lgau, 99.999,interval = "delta") # approx. for ED0
## Fitting a model for "Cu"
Cu.lgau <- drm(BIF ~ conc, data = subset(metals, metal == "Cu"),
fct = lgaussian())
## Fitting a model for the mixture Cu-Zn
CuZn.lgau <- drm(BIF ~ conc, data = subset(metals, metal == "CuZn"),
fct = lgaussian())
## Calculating effects needed for the FA-CI plot
CuZn.effects <- CIcompX(0.015, list(CuZn.lgau, Cu.lgau, Zn.lgau),
c(-5, -10, -20, -30, -40, -50, -60, -70, -80, -90, -99, 99, 90, 80, 70, 60, 50, 40, 30, 20, 10))
## Reproducing the FA-cI plot shown in Figure 5d
plotFACI(CuZn.effects, "ED", ylim = c(0.8, 1.6), showPoints = TRUE)
</pre>
</div></body></html>