What is the difference analysis of sleuth based on TPM value sleuth?

In this issue, the editor will bring you about the difference analysis of sleuth based on TPM value sleuth. The article is rich in content and analyzed and described from a professional point of view. I hope you can get something after reading this article.

Kallisto and other alignment-free transcript quantitative software will give the quantitative results of TPM value. When analyzing differences based on this type of results, there are two strategies to choose from.

The first is to use the tximportR package to import the results into the DESeq2 species for analysis; the second is to directly use the sleuthR package for difference analysis. This chapter mainly introduces the use of sleuth.

The source code for this package is stored on github with the following link

Https://github.com/pachterlab/sleuth

R package on github is installed in a special way, and the specific process is as follows

Source ("http://bioconductor.org/biocLite.R")biocLite("rhdf5")library(devtools)install_github("pachterlab/sleuth")"

First install the dependent rhdf5 package from Bioconductor, because the quantitative result of kallisto is in HDF5 format, this R package is used to read the data, and then using the R package devtools, it is automatically installed from the source code of github.

All difference analysis requires two basic elements: quantitative results and sample grouping, but different R packets require different formats. In sleuth, these two types of information are stored in a three-column data box, as shown in the following example

S2C samples group paths1 control-1 control kallisto/control-12 control-2 control kallisto/control-23 control-3 control kallisto/control-34 case-1 case kallisto/case-15 case-2 case kallisto/case-26 case-3 case kallisto/case-3

The first column is the name of the sample, the second is the grouping information corresponding to the sample, and the third is the folder of the quantitative results of each sample kallisto. Through such a data box, it contains all the information needed for difference analysis.

Assuming that there are six samples, divided into two groups of control,case, each with 3 biological repeats, you can build the above data box with the following code

Samples = c ("control-1", "control-2", "control-3", "case-1", "case-2", "case-3") S2C