How to install the standardized package of chip raw data in R language

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In addition to the relevant software, several packages of bioconductor can also be used for quality control standardization after downloading the original data of the chip, but we need to pay attention to the problems between the R version. The installation of the package based on install.packages may not be successful.

The specific installation method had better go to the website to find the R package and the corresponding R version, the R of the new and old versions may be very different.

The following is based on R version 3.5.1. The following is a standardized package based on the raw data of several chips.

1. Affy standardizes the analysis of affymetrix chip CEL files. The standardized algorithms RMA and MAS5 can operate on affybatch directly corresponding to rma and mas5 functions respectively, and the standardized data can be obtained.

If (! requireNamespace ("BiocManager", quietly = TRUE)) install.packages ("BiocManager") BiocManager::install ("affy", version = "3.8")

2. Lumi can preprocess the data whose Illumina microarray is standardized.

If (! requireNamespace ("BiocManager", quietly = TRUE)) install.packages ("BiocManager") BiocManager::install ("lumi", version = "3.8")

Illumina beadarray can also be preprocessed based on beadarray packages.

3. Limma can not only screen the differential expression of chip data, but also standardize chip data, including agilent chip.

If (! requireNamespace ("BiocManager", quietly = TRUE)) install.packages ("BiocManager") BiocManager::install ("limma", version = "3.8") the above is about" how to install chip raw data standardization package in R language ". I believe we all have some understanding. I hope the content shared by the editor will be helpful to you. If you want to know more about it, please pay attention to the industry information channel.