What are the current limiting factors of genome sequencing accuracy? By accuracy I mean a closeness relation between the sequenced genome and the finally assembled (I am not sure whether there is a proper name for this metric). I hope this way of measuring accuracy is useful since it also captures errors introduced during read-alignment (if short-read sequencing technology is used) and assembly.
As I understand it, there are two sources of errors limiting accuracy: errors in determining the correct bases and errors made in data analysis (read alignment, assembly, etc.). Which of these two sources is responsible for most errors in long- and short-read sequencing techniques? Are a significant amount of errors stemming from the data analysis?
As @David guessed correctly, I am a student (engineering) and wondering whether accuracy may be significantly improved by better algorithms.
As I currently understand it, short-read sequencing techniques are accurate but the repetitive regions are hard/impossible to align, while long-read sequencing techniques are more error-prone, and long-read & accurate sequencing (HiFi) is very expensive. Hence, my overly simplified perspective suggests that algorithmic improvements may continue to improve cheap long-read accuracy through hybrid approaches or improve the alignment and assembly of short reads. Is that correct?
The resources I used were:
https://www.pacb.com/blog/understanding-accuracy-in-dna-sequencing/ https://spectrum.ieee.org/tech-talk/biomedical/diagnostics/99-9-percent-accurate-genome-sequencing and the paper recommended by @Maximilian Press