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Manuel Kaulich

dblp:370/5491 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-9528-8822ORCID · reported

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › functional genomics
CRISPR screen analysis
0.712023
ReCo: automated NGS re ad- co unting of single and combinatorial CRISPR gRNAs · Bioinform. 2023
Bioinformatics and computational biology › genomics
next-generation sequencing data analysis
0.212023
ReCo: automated NGS re ad- co unting of single and combinatorial CRISPR gRNAs · Bioinform. 2023
Bioinformatics and computational biology
read counting
0.212023
ReCo: automated NGS re ad- co unting of single and combinatorial CRISPR gRNAs · Bioinform. 2023

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

cutadapt · 0.7bowtie2 · 0.7
YearPublicationVenuePosition
2023 ReCo: automated NGS re ad- co unting of single and combinatorial CRISPR gRNAs
abstract
SUMMARY: CRISPR screens are increasingly performed to associate genotypes with genotypes. So far, however, their analysis required specialized computational knowledge to transform high-throughput next-generation sequencing (NGS) data into sequence formats amenable for downstream analysis. We developed ReCo, a stand-alone and user-friendly analytics tool for generating read-count tables of single and combinatorial CRISPR library and screen-based NGS data. Together with cutadapt and bowtie2 for rapid sequence trimming and alignment, ReCo enables the automated generation of read count tables from staggered NGS reads for the downstream identification of gRNA-induced phenotypes. AVAILABILITY AND IMPLEMENTATION: ReCo is published under the MIT license and available at: https://github.com/KaulichLab/ReCo.
Martin Wegner, Manuel Kaulich
Bioinform.2