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Introduction
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You can start working in Galaxy by getting familiar to importing data, using history, and manipulating workflows.
Tools such as Nanoplot and Kraken2 can give you information about the quantity (yield), quality (Q-score, N50, and read distribution), and possible contamination.
QC are valuable to decide how the assembly process should be approached. It can tell us whether more sequencing data need to be generated or a certain part of the data need to be filtered. Overall, the decision might be a case by case basis.
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Filtering and Assembly
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Before assembling a genome, make sure to do a proper filtering and trimming to achieve the best assembly possible. There are various algorithm and tools to assemble and polish your genome. Decide which one suits your need.
You can do a sanity check of your assembly by using prior knowledge such as: (1) expected genome size, (2) expected structure of the genome (circular or linear), (3) compare contigs length and depth distribution, and (4) make sense of the assembly graph. From this information, you can decide whether you need to add more depths (by re-sequencing) or do another run if the result is too fragmented.
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Taxonomic Placement
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Genome Annotation
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Genome annotation starts by identifying genes and other functional elements (rRNA, tRNA, etc.) within the nucleotides. This is followed by comparison with databases of interest to predict the functions encoded in the genes.
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Tools for analysing genomes
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Genome annotation starts by identifying genes and other functional elements (rRNA, tRNA, etc.) within the nucleotides. This is followed by comparison with databases of interest to predict the functions encoded in the genes.
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Extra
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