... | ... |
@@ -5,23 +5,23 @@ |
5 | 5 |
\alias{AD_data} |
6 | 6 |
\title{Anaerobic digestion study} |
7 | 7 |
\format{ |
8 |
-A list containing three sub-lists of data \code{FullData}, |
|
9 |
-\code{EgData} and \code{CorrectData}: |
|
8 |
+A list containing three TreeSummarizedExperiment objects |
|
9 |
+\code{FullData}, \code{EgData} and \code{CorrectData}: |
|
10 | 10 |
\describe{ |
11 |
-\item{FullData}{A list containing three data sets: \code{X.count} |
|
12 |
-which are the raw data represented as a matrix with 75 samples and 567 OTUs; |
|
13 |
-\code{metadata} which is a data frame containing the meta data information |
|
14 |
-of samples in \code{X.count}; \code{taxa} which is a data frame containing |
|
15 |
-the taxonomy of each OTU in \code{X.count}.} |
|
16 |
-\item{EgData}{A list containing three data sets: \code{X.clr} which are the |
|
17 |
-filtered and centered log ratio transformed data including 75 samples and |
|
18 |
-231 OTUs from the raw data in the \code{FullData} list; \code{Y.trt} which |
|
19 |
-is a factor of phenol concentrations for each sample that is the effect of |
|
20 |
-interest in the AD study; \code{Y.bat} which is a factor of sample |
|
21 |
-processing dates for each sample treated as the batch effect.} |
|
22 |
-\item{CorrectData}{A list containing seven data sets before or after batch |
|
23 |
-effect correction using different methods. Each data set includes 75 samples |
|
24 |
-and 231 OTUs.}} |
|
11 |
+\item{FullData}{A TreeSummarizedExperiment object containing the counts of 75 |
|
12 |
+samples and 567 OTUs. The meta data information of each sample is stored in |
|
13 |
+the rowData, while the taxonomy of each OTU is stored in the colData.} |
|
14 |
+\item{EgData}{A TreeSummarizedExperiment object containing the values of 75 |
|
15 |
+samples and 231 OTUs filtered and centered log ratio transformed from the |
|
16 |
+\code{FullData} with raw counts.The rowData includes \code{Y.trt} and |
|
17 |
+\code{Y.bat}. \code{Y.trt} is the effect of interest, which is a factor of |
|
18 |
+phenol concentrations for each sample in the AD study; \code{Y.bat} is the |
|
19 |
+batch effect, which is a factor of sample processing dates for each sample. |
|
20 |
+The taxonomy of each OTU is stored in the colData. The rowTree is built based |
|
21 |
+on the \code{Y.bat}.} |
|
22 |
+\item{CorrectData}{A TreeSummarizedExperiment object containing seven |
|
23 |
+datasets before or after batch effect correction using different methods. |
|
24 |
+Each assay includes 75 samples and 231 OTUs.}} |
|
25 | 25 |
} |
26 | 26 |
\source{ |
27 | 27 |
The raw data were provided by Dr. Olivier Chapleur and published at |
1 | 1 |
new file mode 100644 |
... | ... |
@@ -0,0 +1,48 @@ |
1 |
+% Generated by roxygen2: do not edit by hand |
|
2 |
+% Please edit documentation in R/data-AD_data.r |
|
3 |
+\docType{data} |
|
4 |
+\name{AD_data} |
|
5 |
+\alias{AD_data} |
|
6 |
+\title{Anaerobic digestion study} |
|
7 |
+\format{ |
|
8 |
+A list containing three sub-lists of data \code{FullData}, |
|
9 |
+\code{EgData} and \code{CorrectData}: |
|
10 |
+\describe{ |
|
11 |
+\item{FullData}{A list containing three data sets: \code{X.count} |
|
12 |
+which are the raw data represented as a matrix with 75 samples and 567 OTUs; |
|
13 |
+\code{metadata} which is a data frame containing the meta data information |
|
14 |
+of samples in \code{X.count}; \code{taxa} which is a data frame containing |
|
15 |
+the taxonomy of each OTU in \code{X.count}.} |
|
16 |
+\item{EgData}{A list containing three data sets: \code{X.clr} which are the |
|
17 |
+filtered and centered log ratio transformed data including 75 samples and |
|
18 |
+231 OTUs from the raw data in the \code{FullData} list; \code{Y.trt} which |
|
19 |
+is a factor of phenol concentrations for each sample that is the effect of |
|
20 |
+interest in the AD study; \code{Y.bat} which is a factor of sample |
|
21 |
+processing dates for each sample treated as the batch effect.} |
|
22 |
+\item{CorrectData}{A list containing seven data sets before or after batch |
|
23 |
+effect correction using different methods. Each data set includes 75 samples |
|
24 |
+and 231 OTUs.}} |
|
25 |
+} |
|
26 |
+\source{ |
|
27 |
+The raw data were provided by Dr. Olivier Chapleur and published at |
|
28 |
+the referenced article. Filtering and normalisation described in our package |
|
29 |
+vignette. |
|
30 |
+} |
|
31 |
+\usage{ |
|
32 |
+data('AD_data') |
|
33 |
+} |
|
34 |
+\value{ |
|
35 |
+None. |
|
36 |
+} |
|
37 |
+\description{ |
|
38 |
+This study explored the microbial indicators that could improve the efficacy |
|
39 |
+of anaerobic digestion (AD) bioprocess and prevent its failure. The samples |
|
40 |
+were treated with two different ranges of phenol concentration (effect of |
|
41 |
+interest) and processed at five different dates (batch effect). This study |
|
42 |
+includes a clear and strong batch effect with an approx. balanced |
|
43 |
+batch x treatment design. |
|
44 |
+} |
|
45 |
+\references{ |
|
46 |
+\insertRef{chapleur2016increasing}{PLSDAbatch} |
|
47 |
+} |
|
48 |
+\keyword{datasets} |