Assessing N50 and L50 while working on Genome assembly

Question

[Pranathi]

Hello all!

So I have been working on genome assembly. I found my N50 value really small in my contigs results after using Quast to check the quality of my assembly. My question is does the type/ version of trimmer we used for trimming the fastq reads effect the N50 value? I used trimmomatic/0.39 though. Or how can I upgrade my analysis?

Thanks!!

Answer 1

[Istvan Albert]

The N50 value is reflects the quality of the assembly.

The trimmer may or may not affect the quality of the input data used to perform the assembly.

Hence the answer to your question is that:

1. if the trimming improved your data quality then your N50 will be longer,
2. if the trimming made your input data contain less information then your N50 will be shorter.

[Buffo]

Improving the quality of the data does not necessarily improve the quality of the assembly (i.e the N50). Many other variables affect the genome assembly, such as sequence complexity, repeat content, genome size, sequencing length (short/long reads), etc.

if the trimming made your input data contain less information then your N50 will be shorter.

Not necessarily either, it depends on the assembler and the assembly performance.

Answer 2

[Buffo]

You should use trimmomatic when you need to improve the sequence quality. If the quality of the data is good, I would be more focused on the assembler, the assembly performance, and the data itself than on the data pre-processing. The success of a genome assembly depends on many variables, such as:

• Sequencing coverage (it might be the most important variable)
• Specie
• Genome size
• Genome complexity (the second most important variable, in my opinion)
• Sequencing method. Short reads are usually not recommended for genome assembly, but it depends on the genome size and sequence complexity.

All in all, I wouldn't be worried about the use of trimmomatic, the better the quality the more confident the result, whatever it is.