📄️ Reference-Based Sequence Analysis
This type of analysis starts with DNA sequencing data in the form of "sequencing reads", typically stored in FASTQ files, which contain both nucleotide sequences and their per-base quality scores. These reads are then mapped (aligned) to a reference genome, a curated, representative genome sequence that serves as a coordinate system for the organism under study.
📄️ De Novo Sequence Analysis
This type of analysis also starts with DNA sequencing data in the form of sequencing reads, typically stored in FASTQ files, which contain both nucleotide sequences and their per-base quality scores. In contrast to reference-based approaches, no suitable reference genome is assumed to be available, or the goal is to reconstruct the genome independently of an existing reference.
📄️ Metagenomic Analysis
This type of analysis starts with DNA sequencing data in the form of sequencing reads, typically stored in FASTQ files, which contain both nucleotide sequences and their per-base quality scores. In metagenomics, these reads originate from a mixture of multiple organisms present in a single sample, such as environmental, clinical, or host-associated communities.
📄️ Transcriptomic Analysis
This type of analysis starts with RNA sequencing data in the form of sequencing reads, typically stored in FASTQ files, which contain both nucleotide sequences and their per-base quality scores. In transcriptomics, these reads represent RNA molecules that were present in a cell or tissue at the time of sampling and are commonly generated through RNA-seq experiments.
📄️ Snakemake Transcriptomic Analysis
In the previous section, we introduced a minimal workflow for transcriptome analysis using bash scripts. There are several issues with that approach that can be solved using a workflow management system, such as Snakemake.