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Luis García-Jimeno

dblp:313/4932 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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 · 50% Computational science and engineering · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › single-cell analysis › single-cell RNA sequencing
single-cell RNA-seq analysis
0.612022
bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses · Bioinform. 2022
Computational science and engineering
workflow management
0.612022
bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses · Bioinform. 2022

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

snakemake · 0.6
YearPublicationVenuePosition
2022 bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses
abstract
SUMMARY: bollito is an automated, flexible and parallelizable computational pipeline for the comprehensive analysis of single-cell RNA-seq data. Starting from FASTQ files or preprocessed expression matrices, bollito performs both basic and advanced tasks in single-cell analysis integrating >30 state-of-the-art tools. This includes quality control, read alignment, dimensionality reduction, clustering, cell-marker detection, differential expression, functional analysis, trajectory inference and RNA velocity. bollito is built using the Snakemake workflow management system, which easily connects each execution step and facilitates the reproducibility of results. bollito's modular design makes it easy to incorporate other packages into the pipeline enabling its expansion with new functionalities. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://gitlab.com/bu_cnio/bollito under the MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Luis García-Jimeno, Coral Fustero Torre, María José Jiménez-Santos, Gonzalo Gómez-López, Tomás Di Domenico, Fátima Al-Shahrour
Bioinform.1