# SampleName cell dex albut Run avgLength colData(se) # DataFrame with 8 rows and 9 columns Is a DataFrame that can store any number of descriptive columns for each Sample meta-data describing the samples can be accessed using colData(), and # seqinfo: 722 sequences (1 circular) from an unspecified genome # seqnames ranges strand | exon_id exon_name # GRanges object with 17 ranges and 2 metadata columns: rowRanges(se) # GRangesList object of length 64102: Transcript and the ranges in each GRanges correspond to the exons in the GRangesList object, where each list element corresponds to one gene SummarizedExperiment class we’d use rowData()). The rowRanges() accessor is used to view the range information for a Represents a gene transcript and each column one of the samples. The airway dataset contains only one assay ( counts). An object can have multiple assay datasetsĮach of which can be accessed using the $ operator. To retrieve the experiment data from a SummarizedExperiment object one can In a RangedSummarizedExperiment object which contains 8 differentĮxperimental and assays 64,102 gene transcripts. Read counts per gene for airway smooth muscles. The airway package contains an example dataset from an RNA-Seq experiment of Vertical (column) and horizontal (row) relationships. The following graphic displays the class geometry and highlights the The RangedSummarizedExperiment rangesĪre described by a GRanges or a GRangesList object, accessible using the RangedSummarizedExperiment object represent genomic ranges of interest The fundamental difference between the two classes is that the rows of a Which means that all the methods on SummarizedExperiment also work on a RangedSummarizedExperiment is the child of the SummarizedExperiment class Of the DataFrame represent different attributes of the features of interest, Each row of the DataFrame provides information on theįeature in the corresponding row of the SummarizedExperiment object. InformationĪbout these features is stored in a DataFrame object, accessible using theįunction rowData(). SummarizedExperiment object represent features of interest. Matrix-like object of numeric or other mode. The objects contain one or more assays, each represented by a Of interest (e.g. genes, transcripts, exons, etc.) and columns represent ![]() SummarizedExperiment is a matrix-like container where rows represent features ![]() SummarizedExperiment and RangedSummarizedExperiment. The SummarizedExperiment package contains two classes: Of experiments, particularly sequencing based experiments such as RNA-Seq and This makes it ideally suited to a variety SummarizedExperiment is in many ways similar to the historicalĮxpressionSet, the main distinction being that SummarizedExperiment is moreįlexible in it’s row information, allowing both GRanges based as well as thoseĭescribed by arbitrary DataFrames. Incorrect results and retractions so this is a very desirable ImproperlyĪccounting for meta and observational data has resulted in a number of Which ensures the meta-data and observed data will remain in sync. Given sample you can do for both the meta-data and assay in one operation, With additional meta-data describing both the observations (features) andĪ key aspect of the SummarizedExperiment class is the coordination of the Note that SummarizedExperiment can simultaneously manage severalĮxperimental results or assays as long as they be of the same dimensions.Įach object stores observations of one or more samples, along ![]() The SummarizedExperiment class is used to store rectangular matrices ofĮxperimental results, which are commonly produced by sequencing and microarrayĮxperiments.
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