What does the DESeq function do?

By default, DESeq will replace outliers if the Cook’s distance is large for a sample which has 7 or more replicates (including itself). This replacement is performed by the replaceOutliers function. This default behavior helps to prevent filtering genes based on Cook’s distance when there are many degrees of freedom.

How do you DESeq in R?

DESEQ2 R Tutorial

1. Quality assess and clean raw sequencing data.
2. Align reads to a reference.
3. Count the number of reads assigned to each contig/gene.
4. Extract counts and store in a matrix.
5. Create column metadata table.
6. Analyze count data using DESEQ2.
7. Install packages and load libraries.
8. Download data.

What is DESeq analysis?

DESeq is an R package to analyse count data from high-throughput sequencing assays such as RNA-Seq and test for differential expression.

What is a DESeq2 object?

The object class used by the DESeq2 package to store the read counts and the intermediate estimated quantities during statistical analysis is the DESeqDataSet, which will usually be represented in the code here as an object dds .

What do you need to know about deseq2?

As input, the DESeq2 package expects count data as obtained, e.g., from RNA-seq or another high-throughput sequencing experiment, in the form of a matrix of integer values. The value in the i -th row and the j -th column of the matrix tells how many reads can be assigned to gene i in sample j .

How to run differential expression analysis with deseq2?

Each individual has a primary colorectal cancer sample, a metastatic liver sample, and a normal sample of the surrounding colonic epithilium. The quantification data required to run differential expression analysis using DEseq2 are raw readcounts for either genes or transcripts. We will use the output from HTseq as a starting point.

How does deseq2 work with the count matrix?

For DEseq2 to work properly the column names of the count matrix must be in the same order as the row names of the sample mapping data, to ensure this we re-order the column names of the count data and run a check to ensure this has occurred correctly.

When is deseq2 course at University of Munster?

The following workflow has been designed as teaching instructions for an introductory course to RNA-seq data analysis with DESeq2. The course is designed for PhD students and will be given at the University of Münster from 10th to 21st of October 2016. For questions or other comments, please contact me.