FORGe: prioritizing variants for graph genomes
Abstract There is growing interest in using genetic variants to augment the reference genome into a graph genome, with alternative sequences, to improve read alignment accuracy and reduce allelic bias. While adding a variant has the positive effect of removing an undesirable alignment score penalty,...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2018-12-01
|
| Series: | Genome Biology |
| Online Access: | http://link.springer.com/article/10.1186/s13059-018-1595-x |
| _version_ | 1828409446979600384 |
|---|---|
| author | Jacob Pritt Nae-Chyun Chen Ben Langmead |
| author_facet | Jacob Pritt Nae-Chyun Chen Ben Langmead |
| author_sort | Jacob Pritt |
| collection | DOAJ |
| description | Abstract There is growing interest in using genetic variants to augment the reference genome into a graph genome, with alternative sequences, 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. |
| first_indexed | 2024-12-10T11:55:54Z |
| format | Article |
| id | doaj.art-ba95cdc1b96245d4858f3ff997ddcdb4 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-10T11:55:54Z |
| publishDate | 2018-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-ba95cdc1b96245d4858f3ff997ddcdb42022-12-22T01:49:48ZengBMCGenome Biology1474-760X2018-12-0119111610.1186/s13059-018-1595-xFORGe: prioritizing variants for graph genomesJacob Pritt0Nae-Chyun Chen1Ben Langmead2Department of Computer Science, Johns Hopkins UniversityDepartment of Computer Science, Johns Hopkins UniversityDepartment of Computer Science, Johns Hopkins UniversityAbstract There is growing interest in using genetic variants to augment the reference genome into a graph genome, with alternative sequences, 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.http://link.springer.com/article/10.1186/s13059-018-1595-x |
| spellingShingle | Jacob Pritt Nae-Chyun Chen Ben Langmead FORGe: prioritizing variants for graph genomes Genome Biology |
| title | FORGe: prioritizing variants for graph genomes |
| title_full | FORGe: prioritizing variants for graph genomes |
| title_fullStr | FORGe: prioritizing variants for graph genomes |
| title_full_unstemmed | FORGe: prioritizing variants for graph genomes |
| title_short | FORGe: prioritizing variants for graph genomes |
| title_sort | forge prioritizing variants for graph genomes |
| url | http://link.springer.com/article/10.1186/s13059-018-1595-x |
| work_keys_str_mv | AT jacobpritt forgeprioritizingvariantsforgraphgenomes AT naechyunchen forgeprioritizingvariantsforgraphgenomes AT benlangmead forgeprioritizingvariantsforgraphgenomes |