RT Journal Article
SR Electronic
T1 FORGe: prioritizing variants for graph genomes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 311720
DO 10.1101/311720
A1 Jacob Pritt
A1 Ben Langmead
YR 2018
UL http://biorxiv.org/content/early/2018/04/30/311720.abstract
AB There is growing interest in using genetic variants to augment the reference genome into a “graph genome” to improve read alignment accuracy and reduce allelic bias. While adding a variant has the positive effect of removing an undesirable alignment-score penalty, it also increases both the ambiguity of the reference genome and the cost of storing and querying the genome index. We introduce methods and a software tool called FORGe for modeling these effects and prioritizing variants accordingly. We show that FORGe enables a range of advantageous and measurable trade-offs between accuracy and computational overhead.