CountDataSet-class(DESeq)
CountDataSet-class()所属R语言包：DESeq
Class "CountDataSet" – a container for count data from HTS experiments
类的“CountDataSet” - 从高温超导实验计数数据的容器
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This is the main class for the present package.
这是目前封装的主类。
类的对象----------Objects from the Class----------
Objects should be created with calls to newCountDataSet (q.v.).
应该创建对象调用newCountDataSet（QV）。
延伸----------Extends----------
Class eSet (package 'Biobase'), directly. Class VersionedBiobase (package 'Biobase'), by class "eSet", distance 2. Class Versioned (package 'Biobase'), by class "eSet", distance 3.
类eSet（包BIOBASE“），直接。类VersionedBiobase（包BIOBASE“类”ESET“，距离2）。类Versioned（包BIOBASE）“ESET”级，距离3。
注意----------Note----------
Note: This is a summary for reference. For an explanation of the actual usage, see the vignette.
注：这是一个供参考的总结。对于实际使用的解释，看到的小插曲。
A CountDataSet object stores counts from an HTS data set and offers further slots which are populated during the analysis.
一个CountDataSet从HTS数据对象存储计数，并提供进一步在分析过程中填充插槽。
After creation with newCountDataSet, a CountDataSet typically contains a count table, i.e., a matrix of integer data, that is accessible with the accessor function counts. Each row of the matrix corresponds to a gene (or binding region, or the like), and each colum to an experimental sample. The experimental conditions of the samples are stored in a factor (with one element for each row of the counts matrix), which can be read with the accessor function conditions.
创建newCountDataSet后，CountDataSet通常包含一个计数表，即一个整数数据矩阵，这是访问存取功能counts。矩阵的每一行对应的基因（或结合区域，或类似），每个实验样品的科拉姆。样品的实验条件下存储中的一个因素（计数矩阵的每一行的一个元素），它可以读取与存取功能conditions。
In the following analysis steps, further data slots are populated. First, the size factors can be estimated with estimateSizeFactors, which are afterwards accessible via sizeFactors. Then, the dispersions (variance fits) are estimated with estimateDispersions. The resulting estimates are stored in phenoData columns, accessible via pData, with the column names staring with disp_. The intermediate steps of the fit are stored in the environment-values slot fitInfo (see estimateDispersions for details).
在下面的分析步骤，进一步的数据填充插槽。首先，规模等因素，可以预计estimateSizeFactors，这是事后通过sizeFactors访问。然后用estimateDispersions估计，分散（方差一刀切）。存储在phenoData列，列名称盯着pDatadisp_，通过访问所产生的估计。环境值槽fitInfo（见estimateDispersions细节）存放在合适的中间步骤。
Internally, the mentioned data is stored in slots as follows:
在内部，上述数据是存储在插槽如下：
As CountDataSet is derived from eSet, it has a phenoData slot which allows to store sample annotation. This is used to store the factor with the conditions, as a data frame column named condition, and to store the size factors, as an numeric data frame column named sizeFactor. If the user creates an object with multivariate design, i.e., passes a data frame instead of a factor for conditions, this data frame's columns are placed in the phenoData slot instead of the condition column. Furthermore, the function estimateDispersions adds columns with the dispersion values to be used by nbinomTest and fitNbinomGLMs. These columns have names starting with disp_.
作为CountDataSet是eSet派生，它有一个phenoData插槽，允许存储样品注解。这是用来储存条件的因素，作为一个数据框的命名列，condition，存储大小的因素，名为sizeFactor作为一个数字数据框列。如果用户创建了一个多元的设计，即对象，通过一个数据框，而不是一个因素conditions，这个数据框的列放在phenoDatacondition列，而不是插槽。此外，功能estimateDispersions添加与分散值要nbinomTest和fitNbinomGLMs使用列。这些列名称disp_开头。
The user may add further columns to the phenoData AnnotatedDataFrame.
用户可以添加进一步列phenoDataAnnotatedDataFrame的。
The counts table is stored in the eSet's assayData locked environment with the name counts.
计数表存储在eSet的assayData锁定的名称counts环境。
The slot dispInfo is an environment containing lists, one for each set of estimated dispersion values and the slot dispTable (with accessor dispTable shows the assignment of conditions to dispersion estimates. See estimateDispersions
槽dispInfo是一个包含列表的环境，每个估计的色散值和插槽dispTable（dispTable显示的条件分配分散的估计。见存取<X >
举例----------Examples----------
# See the vignette[见的小插曲]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
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发表于 2012-2-25 16:31:03
