What is DESeq?

What is DESeq?

DESeq is an R package to analyse count data from high-throughput sequencing assays such as RNA-Seq and test for differential expression. The package is available via Bioconductor and can be conveniently installed as follows: Start an R session and type source(“http://www.bioconductor.org/biocLite.R”) biocLite(“DESeq”)

What is a transcriptome analysis?

The transcriptome is the complete set of transcripts in a specific type of cell or tissue. Generally, the goal of transcriptome analysis is to identify genes differentially expressed among different conditions, leading to a new understanding of the genes or pathways associated with the conditions.

How many reads rnaseq?

Generally, we recommend 5-10 million reads per sample for small genomes (e.g. bacteria) and 20-30 million reads per sample for large genomes (e.g. human, mouse). Medium genomes often depend on the project, but we would generally recommend between 15-20 million reads per sample.

What is RPKM in gene expression?

Reads Per Kilobase of transcript, per Million mapped reads (RPKM) is a normalized unit of transcript expression. It scales by transcript length to compensate for the fact that most RNA-seq protocols will generate more sequencing reads from longer RNA molecules.

What is FPKM value?

FPKM stands for Fragments Per Kilobase of transcript per Million mapped reads. In RNA-Seq, the relative expression of a transcript is proportional to the number of cDNA fragments that originate from it.

What is DESeqDataSet?

DESeqDataSet is a subclass of RangedSummarizedExperiment , used to store the input values, intermediate calculations and results of an analysis of differential expression. The DESeqDataSet class enforces non-negative integer values in the “counts” matrix stored as the first element in the assay list.

What is transcriptome and transcriptomics?

The transcriptome is the set of all RNA transcripts, including coding and non-coding, in an individual or a population of cells. Single-cell transcriptomics allows tracking of transcript changes over time within individual cells.

What is Transcriptomics used for?

Transcriptomics allows identification of genes and pathways that respond to and counteract biotic and abiotic environmental stresses. The non-targeted nature of transcriptomics allows the identification of novel transcriptional networks in complex systems.

What is a good sequencing coverage?

For example, a genome sequencing study may sequence a genome to 30× average depth and achieve a 95% breadth of coverage of the reference genome at a minimum depth of ten reads. In real-world sequencing approaches, read lengths are short (that is, ≤250 nucleotides) and can contain sequence errors.

What is a good sequencing depth?

In many cases 5 M – 15 M mapped reads are sufficient. You will be able to get a good snapshot of highly expressed genes. For that reason, many published human RNA-Seq experiments have been sequenced with a sequencing depth between 20 M – 50 M reads per sample.

What is TMM RNA?

TMM (Trimmed Mean of M-values) TMM considers sample RNA population and effective in normalization of samples with diverse RNA repertoires (e.g. samples from different tissues).

What is RPKM and FPKM?

RPKM stands for Reads Per Kilobase of transcript per Million mapped reads. FPKM stands for Fragments Per Kilobase of transcript per Million mapped reads. In RNA-Seq, the relative expression of a transcript is proportional to the number of cDNA fragments that originate from it.