Correcting Illumina sequencing errors for human data
Abstract
Summary: We present a new tool to correct sequencing errors in Illumina data produced from high-coverage whole-genome shotgun resequencing. It uses a non-greedy algorithm and shows comparable performance and higher accuracy in an evaluation on real human data. This evaluation has the most complete collection of high-performance error correctors so far. Availability and implementation: https://github.com/lh3/bfc Contact: hengli@broadinstitute.org
0
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.