Cargando…
SAUTE: sequence assembly using target enrichment
BACKGROUND: Illumina is the dominant sequencing technology at this time. Short length, short insert size, some systematic biases, and low-level carryover contamination in Illumina reads continue to make assembly of repeated regions a challenging problem. Some applications also require finding multip...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293564/ https://www.ncbi.nlm.nih.gov/pubmed/34289805 http://dx.doi.org/10.1186/s12859-021-04174-9 |
_version_ | 1783725067658592256 |
---|---|
author | Souvorov, Alexandre Agarwala, Richa |
author_facet | Souvorov, Alexandre Agarwala, Richa |
author_sort | Souvorov, Alexandre |
collection | PubMed |
description | BACKGROUND: Illumina is the dominant sequencing technology at this time. Short length, short insert size, some systematic biases, and low-level carryover contamination in Illumina reads continue to make assembly of repeated regions a challenging problem. Some applications also require finding multiple well supported variants for assembled regions. RESULTS: To facilitate assembly of repeat regions and to report multiple well supported variants when a user can provide target sequences to assist the assembly, we propose SAUTE and SAUTE_PROT assemblers. Both assemblers use de Bruijn graph on reads. Targets can be transcripts or proteins for RNA-seq reads and transcripts, proteins, or genomic regions for genomic reads. Target sequences are nucleotide and protein sequences for SAUTE and SAUTE_PROT, respectively. CONCLUSIONS: For RNA-seq, comparisons with Trinity, rnaSPAdes, SPAligner, and SPAdes assembly of reads aligned to target proteins by DIAMOND show that SAUTE_PROT finds more coding sequences that translate to benchmark proteins. Using AMRFinderPlus calls, we find SAUTE has higher sensitivity and precision than SPAdes, plasmidSPAdes, SPAligner, and SPAdes assembly of reads aligned to target regions by HISAT2. It also has better sensitivity than SKESA but worse precision. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04174-9. |
format | Online Article Text |
id | pubmed-8293564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82935642021-07-21 SAUTE: sequence assembly using target enrichment Souvorov, Alexandre Agarwala, Richa BMC Bioinformatics Software BACKGROUND: Illumina is the dominant sequencing technology at this time. Short length, short insert size, some systematic biases, and low-level carryover contamination in Illumina reads continue to make assembly of repeated regions a challenging problem. Some applications also require finding multiple well supported variants for assembled regions. RESULTS: To facilitate assembly of repeat regions and to report multiple well supported variants when a user can provide target sequences to assist the assembly, we propose SAUTE and SAUTE_PROT assemblers. Both assemblers use de Bruijn graph on reads. Targets can be transcripts or proteins for RNA-seq reads and transcripts, proteins, or genomic regions for genomic reads. Target sequences are nucleotide and protein sequences for SAUTE and SAUTE_PROT, respectively. CONCLUSIONS: For RNA-seq, comparisons with Trinity, rnaSPAdes, SPAligner, and SPAdes assembly of reads aligned to target proteins by DIAMOND show that SAUTE_PROT finds more coding sequences that translate to benchmark proteins. Using AMRFinderPlus calls, we find SAUTE has higher sensitivity and precision than SPAdes, plasmidSPAdes, SPAligner, and SPAdes assembly of reads aligned to target regions by HISAT2. It also has better sensitivity than SKESA but worse precision. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04174-9. BioMed Central 2021-07-21 /pmc/articles/PMC8293564/ /pubmed/34289805 http://dx.doi.org/10.1186/s12859-021-04174-9 Text en © This is a U.S. government work and not under copyright protection in the U.S; foreign copyright protection may apply 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Souvorov, Alexandre Agarwala, Richa SAUTE: sequence assembly using target enrichment |
title | SAUTE: sequence assembly using target enrichment |
title_full | SAUTE: sequence assembly using target enrichment |
title_fullStr | SAUTE: sequence assembly using target enrichment |
title_full_unstemmed | SAUTE: sequence assembly using target enrichment |
title_short | SAUTE: sequence assembly using target enrichment |
title_sort | saute: sequence assembly using target enrichment |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8293564/ https://www.ncbi.nlm.nih.gov/pubmed/34289805 http://dx.doi.org/10.1186/s12859-021-04174-9 |
work_keys_str_mv | AT souvorovalexandre sautesequenceassemblyusingtargetenrichment AT agarwalaricha sautesequenceassemblyusingtargetenrichment |