Systematically evaluating interfaces for RNA-seq analysis from a life scientist perspective
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Systematically evaluating interfaces for RNA-seq analysis from a life scientist perspective. / Poplawski, Alicia; Marini, Federico; Hess, Moritz; Zeller, Tanja; Mazur, Johanna; Binder, Harald.
in: BRIEF BIOINFORM, Jahrgang 17, Nr. 2, 03.2016, S. 213-223.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Review › Forschung
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TY - JOUR
T1 - Systematically evaluating interfaces for RNA-seq analysis from a life scientist perspective
AU - Poplawski, Alicia
AU - Marini, Federico
AU - Hess, Moritz
AU - Zeller, Tanja
AU - Mazur, Johanna
AU - Binder, Harald
N1 - © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
PY - 2016/3
Y1 - 2016/3
N2 - RNA-sequencing (RNA-seq) has become an established way for measuring gene expression in model organisms and humans. While methods development for refining the corresponding data processing and analysis pipeline is ongoing, protocols for typical steps have been proposed and are widely used. Several user interfaces have been developed for making such analysis steps accessible to life scientists without extensive knowledge of command line tools. We performed a systematic search and evaluation of such interfaces to investigate to what extent these can indeed facilitate RNA-seq data analysis. We found a total of 29 open source interfaces, and six of the more widely used interfaces were evaluated in detail. Central criteria for evaluation were ease of configuration, documentation, usability, computational demand and reporting. No interface scored best in all of these criteria, indicating that the final choice will depend on the specific perspective of users and the corresponding weighting of criteria. Considerable technical hurdles had to be overcome in our evaluation. For many users, this will diminish potential benefits compared with command line tools, leaving room for future improvement of interfaces.
AB - RNA-sequencing (RNA-seq) has become an established way for measuring gene expression in model organisms and humans. While methods development for refining the corresponding data processing and analysis pipeline is ongoing, protocols for typical steps have been proposed and are widely used. Several user interfaces have been developed for making such analysis steps accessible to life scientists without extensive knowledge of command line tools. We performed a systematic search and evaluation of such interfaces to investigate to what extent these can indeed facilitate RNA-seq data analysis. We found a total of 29 open source interfaces, and six of the more widely used interfaces were evaluated in detail. Central criteria for evaluation were ease of configuration, documentation, usability, computational demand and reporting. No interface scored best in all of these criteria, indicating that the final choice will depend on the specific perspective of users and the corresponding weighting of criteria. Considerable technical hurdles had to be overcome in our evaluation. For many users, this will diminish potential benefits compared with command line tools, leaving room for future improvement of interfaces.
KW - Algorithms
KW - Biological Science Disciplines/methods
KW - Data Mining/methods
KW - Databases, Genetic
KW - High-Throughput Nucleotide Sequencing/methods
KW - Sequence Analysis, RNA/methods
KW - Software
KW - User-Computer Interface
U2 - 10.1093/bib/bbv036
DO - 10.1093/bib/bbv036
M3 - SCORING: Review article
C2 - 26108229
VL - 17
SP - 213
EP - 223
JO - BRIEF BIOINFORM
JF - BRIEF BIOINFORM
SN - 1467-5463
IS - 2
ER -
