Recent progress in DNA amplification techniques, particularly multiple displacement
amplification (MDA), has made it possible to sequence and assemble bacterial
genomes from a single cell. However, the quality of single cell genome assembly has
not yet reached the quality of normal multi-cell genome assembly due to the coverage
bias (including uneven depth of coverage and region blackout) and errors caused by
MDA. Computational methods try to mitigates the amplification bias. In this document
we introduce a de novo co-assembly method using colored de Bruijn graph,
which can overcome the problem of blackout regions due to amplification bias. The
algorithm is implemented in a tool named HyDA (Hybrid De novo Assembler). HyDA
can assemble various genome of phylogenetically close species simultaneously whit a
high quality while it can determine the genomic relationship between each pair of
co-assembled dataset based on their common and exclusive contigs. Moreover, co-assembly can provide a high quality genome assembly from a number of guessed to
be identical single cell. Since our algorithm can detect the outlier, it can generate a
non-chimeric result with most recovered genome regions. Various techniques, such as
iterative assembly with multiple k, are employed in HyDA, which makes it a powerful
de novo assembly tool.
","abstract_html":"<p>Recent progress in DNA amplification techniques, particularly multiple displacement</p> <p>amplification (MDA), has made it possible to sequence and assemble bacterial</p> <p>genomes from a single cell. However, the quality of single cell genome assembly has</p> <p>not yet reached the quality of normal multi-cell genome assembly due to the coverage</p> <p>bias (including uneven depth of coverage and region blackout) and errors caused by</p> <p>MDA. Computational methods try to mitigates the amplification bias. In this document</p> <p>we introduce a de novo co-assembly method using colored de Bruijn graph,</p> <p>which can overcome the problem of blackout regions due to amplification bias. The</p> <p>algorithm is implemented in a tool named HyDA (Hybrid De novo Assembler). HyDA</p> <p>can assemble various genome of phylogenetically close species simultaneously whit a</p> <p>high quality while it can determine the genomic relationship between each pair of</p> <p>co-assembled dataset based on their common and exclusive contigs. Moreover, co-assembly can provide a high quality genome assembly from a number of guessed to</p> <p>be identical single cell. Since our algorithm can detect the outlier, it can generate a</p> <p>non-chimeric result with most recovered genome regions. Various techniques, such as</p> <p>iterative assembly with multiple k, are employed in HyDA, which makes it a powerful</p> <p>de novo assembly tool.</p>","abstract_has_math":false,"creators":["Movahedi Tabrizi, Narjes Sadat"],"institution":null,"degree_name":"Ph.D.","degree_level":"Open Access Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Dongxiao Zhu"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-01-01T08:00:00Z","date_published":"2015-01-01T08:00:00Z","updated_at":"2026-07-24T06:00:17Z","subjects":["Co-assembly","Colored De Bruijn Graph","Genome","Sequencing","Single Cell","Bioinformatics","Computer Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wayne.edu/oa_dissertations/1378","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dongxiao Zhu"]},{"key":"dc:creator","label":"Author","values":["Movahedi Tabrizi, Narjes Sadat"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-01-01T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Co-assembly","Colored De Bruijn Graph","Genome","Sequencing","Single Cell","Bioinformatics","Computer Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.wayne.edu/oa_dissertations/1378"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Recent progress in DNA amplification techniques, particularly multiple displacement
amplification (MDA), has made it possible to sequence and assemble bacterial
genomes from a single cell. However, the quality of single cell genome assembly has
not yet reached the quality of normal multi-cell genome assembly due to the coverage
bias (including uneven depth of coverage and region blackout) and errors caused by
MDA. Computational methods try to mitigates the amplification bias. In this document
we introduce a de novo co-assembly method using colored de Bruijn graph,
which can overcome the problem of blackout regions due to amplification bias. The
algorithm is implemented in a tool named HyDA (Hybrid De novo Assembler). HyDA
can assemble various genome of phylogenetically close species simultaneously whit a
high quality while it can determine the genomic relationship between each pair of
co-assembled dataset based on their common and exclusive contigs. Moreover, co-assembly can provide a high quality genome assembly from a number of guessed to
be identical single cell. Since our algorithm can detect the outlier, it can generate a
non-chimeric result with most recovered genome regions. Various techniques, such as
iterative assembly with multiple k, are employed in HyDA, which makes it a powerful
de novo assembly tool.
"]},{"key":"dc:title","label":"Title","values":["Efficient Synergistic De Novo Co-Assembly Of Bacterial Genomes From Single Cells Using Colored De Bruijn Graph"]}]}],"canonical_facts":{"dc:contributor":["Dongxiao Zhu"],"dc:creator":["Movahedi Tabrizi, Narjes Sadat"],"dc:date.available":["2016-01-01T08:00:00Z"],"dc:description.abstract":["Recent progress in DNA amplification techniques, particularly multiple displacement
amplification (MDA), has made it possible to sequence and assemble bacterial
genomes from a single cell. However, the quality of single cell genome assembly has
not yet reached the quality of normal multi-cell genome assembly due to the coverage
bias (including uneven depth of coverage and region blackout) and errors caused by
MDA. Computational methods try to mitigates the amplification bias. In this document
we introduce a de novo co-assembly method using colored de Bruijn graph,
which can overcome the problem of blackout regions due to amplification bias. The
algorithm is implemented in a tool named HyDA (Hybrid De novo Assembler). HyDA
can assemble various genome of phylogenetically close species simultaneously whit a
high quality while it can determine the genomic relationship between each pair of
co-assembled dataset based on their common and exclusive contigs. Moreover, co-assembly can provide a high quality genome assembly from a number of guessed to
be identical single cell. Since our algorithm can detect the outlier, it can generate a
non-chimeric result with most recovered genome regions. Various techniques, such as
iterative assembly with multiple k, are employed in HyDA, which makes it a powerful
de novo assembly tool.
"],"dc:identifier":["https://digitalcommons.wayne.edu/oa_dissertations/1378"],"dc:subject":["Co-assembly","Colored De Bruijn Graph","Genome","Sequencing","Single Cell","Bioinformatics","Computer Sciences"],"dc:title":["Efficient Synergistic De Novo Co-Assembly Of Bacterial Genomes From Single Cells Using Colored De Bruijn Graph"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T06:00:17Z"}