Next Generation Sequencing (NGS)/Expression quantification

RNA-seq expression quantification

Overview

• Objective: to estimate the relative abundance of transcripts from an rna-seq sample.
• Biological questions?

• Inputs:

• Reference:

• Annotated Genome (fasta/gff)
• Transcriptome (fasta)
• RNA-seq raw reads (fastq, Ilumina).

• Outputs:

• Relative abundance per transcript.

Experimental Design

See (link) RNA sequencing

Typical Steps in the Method: (table or workflow or paragraph?)

• Data generation | Get some data. | Seq (link) Sequencing RNA technologies,
• Get a reference | You need a reference with all the involved transcripts for which you want relative abundance |
• RNA-seq read QC | Check the quality of the sequencing itself. |
• Adaptor trimming / quality filtering / contamination filtering | Reads will contain sequence that is not from the transcript but from the technology. |
• Mapping | Align your reads to the reference |

- Quantification | Get transcript abundance |

Workflows

Real life workflows

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Command line scripts

Example workflow:

Real life workflows:
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Some tools and resources

• Get a reference: MetaDB (link)genome assembly and annotation (link) transcriptome denovo assembly ....
• QC: SeqWiki: FastQC, KAT
• Trimming: SeqWiki; Trimmomatic, Sickle, Cutadapt....
• Mapping: Seqwiki: tools...... ... ... ... ... ... ... .. ....
• Quant: Seqwiki: tools