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Eric C. Bretz

dblp:424/3998 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › sequence assembly › genome assembly
de novo assembly
0.912025
Semblans: automated assembly and processing of RNA-seq data · Bioinform. 2025
Bioinformatics and computational biology
sequence analysis
0.912025
Semblans: automated assembly and processing of RNA-seq data · Bioinform. 2025
Bioinformatics and computational biology › sequence analysis › sequence assembly
transcriptome assembly
0.912025
Semblans: automated assembly and processing of RNA-seq data · Bioinform. 2025
Bioinformatics and computational biology › transcriptomics
RNA-seq analysis
0.312025
Semblans: automated assembly and processing of RNA-seq data · Bioinform. 2025

Methods — techniques the papers use, named apart from their topics

error correction · 0.9chimera filtration · 0.9adapter trimming · 0.9
YearPublicationVenuePosition
2025 Semblans: automated assembly and processing of RNA-seq data
abstract
MOTIVATION: Recent advancements in parallel sequencing methods have precipitated a surge in publicly available short-read sequence data. This has encouraged the development of novel computational tools for the de novo assembly of transcriptomes from RNA-seq data. Despite the availability of these tools, performing an end-to-end transcriptome assembly remains a programmatically involved task necessitating familiarity with best practices. Aside from quality control steps, including error correction, adapter trimming, and chimera filtration needing to be correctly used, moving data between programs often requires manual reformatting or restructuring, which can further impede throughput. Here, we introduce Semblans, a tool for streamlining the assembly process that efficiently and consistently produces high-quality transcriptome assemblies. RESULTS: Semblans abstracts the key quality control, reconstitution, and postprocessing steps of transcriptome assembly from raw short-read sequences to annotated coding sequences. Evaluating its performance against previously assembled transcriptomes on the basis of assembly quality, we find that Semblans produced higher quality assemblies for 98 of the 101 short-read runs tested. AVAILABILITY AND IMPLEMENTATION: Semblans is written in C++ and runs on Unix-compliant operating systems. Source code, documentation, and compiled binaries are hosted under the GNU General Public License at https://github.com/gladshire/Semblans.
Miles D. Woodcock-Girard, Eric C. Bretz, Holly M. Robertson, Karolis Ramanauskas, Jarrad T. Hampton-Marcell, Joseph F. Walker
Bioinform.2