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The rapid evolution of long read sequencing technologies toward more accurate long reads, coupled with the continued use of short read technologies, has created a unique need for hybrid assembly workflows. The construction of accurate genomic scaffolds in hybrid workflows is complicated due to scale, sequencing technology diversity (e.g., short vs. long reads, contigs or partial assemblies), and repetitive regions within a target genome.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In this paper, we present a new parallel workflow for hybrid genome scaffolding that would allow combining pre-constructed partial assemblies with newly sequenced long reads toward an improved assembly. More specifically, the workflow, called , is aimed at generating long scaffolds of a target genome, from two sets of input sequences\u2014an already constructed partial assembly of contigs, and a set of newly sequenced long reads. Our scaffolding approach internally uses an alignment-free mapping step to build a\n                      <jats:inline-formula>\n                        <jats:alternatives>\n                          <jats:tex-math>$$\\langle $$<\/jats:tex-math>\n                          <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                            <mml:mo>\u27e8<\/mml:mo>\n                          <\/mml:math>\n                        <\/jats:alternatives>\n                      <\/jats:inline-formula>\n                      contig,contig\n                      <jats:inline-formula>\n                        <jats:alternatives>\n                          <jats:tex-math>$$\\rangle $$<\/jats:tex-math>\n                          <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                            <mml:mo>\u27e9<\/mml:mo>\n                          <\/mml:math>\n                        <\/jats:alternatives>\n                      <\/jats:inline-formula>\n                      graph using long reads as linking information. Subsequently, this graph is used to generate scaffolds. We present and evaluate a graph-theoretic \u201cwiring\u201d heuristic to perform this scaffolding step. To enable efficient workload management in a parallel setting, we use a batching technique that partitions the scaffolding tasks so that the more expensive alignment-based assembly step at the end can be efficiently parallelized. This step also allows the use of any standalone assembler for generating the final scaffolds.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      Our experiments with  on a variety of input genomes, and comparison against two state-of-the-art hybrid scaffolders demonstrate that  is able to generate longer and more accurate scaffolds substantially faster. In almost all cases, the scaffolds produced by  are at least an order of magnitude longer (in some cases two orders) than the scaffolds produced by state-of-the-art tools.  runs significantly faster too, reducing time-to-solution from hours to minutes for most input cases. We also performed a coverage experiment by varying the sequencing coverage depth for long reads, which demonstrated the potential of  to generate significantly longer scaffolds in low coverage settings (\n                      <jats:inline-formula>\n                        <jats:alternatives>\n                          <jats:tex-math>$$1\\times $$<\/jats:tex-math>\n                          <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                            <mml:mrow>\n                              <mml:mn>1<\/mml:mn>\n                              <mml:mo>\u00d7<\/mml:mo>\n                            <\/mml:mrow>\n                          <\/mml:math>\n                        <\/jats:alternatives>\n                      <\/jats:inline-formula>\n                      \u2013\n                      <jats:inline-formula>\n                        <jats:alternatives>\n                          <jats:tex-math>$$10\\times $$<\/jats:tex-math>\n                          <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                            <mml:mrow>\n                              <mml:mn>10<\/mml:mn>\n                              <mml:mo>\u00d7<\/mml:mo>\n                            <\/mml:mrow>\n                          <\/mml:math>\n                        <\/jats:alternatives>\n                      <\/jats:inline-formula>\n                      ).\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-024-05878-4","type":"journal-article","created":{"date-parts":[[2024,8,8]],"date-time":"2024-08-08T15:03:12Z","timestamp":1723129392000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Maptcha: an efficient parallel workflow for hybrid genome scaffolding"],"prefix":"10.1186","volume":"25","author":[{"given":"Oieswarya","family":"Bhowmik","sequence":"first","affiliation":[]},{"given":"Tazin","family":"Rahman","sequence":"additional","affiliation":[]},{"given":"Ananth","family":"Kalyanaraman","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,8,8]]},"reference":[{"issue":"D1","key":"5878_CR1","doi-asserted-by":"publisher","first-page":"D36","DOI":"10.1093\/nar\/gks1195","volume":"41","author":"DA Benson","year":"2012","unstructured":"Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW. 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