ArticleGigaScience2013
Lessons learned from implementing a national infrastructure in Sweden for storage and analysis of next-generation sequencing data.
Article in GigaScience, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed.
- Eras of bioinformatics technologies from command-line interfaces to artificial intelligence (AI) chatbots.Briefings in bioinformatics · 2026Review
- Article
- Feasibility to use whole-genome sequencing as a sole diagnostic method to detect genomic aberrations in pediatric B-cell acute lymphoblastic leukemia.Frontiers in oncology · 2023Article
- A simple guide to de novo transcriptome assembly and annotation.Briefings in bioinformatics · 2022Review
- 0s and 1s in marine molecular research: a regional HPC perspective.GigaScience · 2021Article
- ELIXIR-IT HPC@CINECA: high performance computing resources for the bioinformatics community.BMC bioinformatics · 2020Article
- Transcriptome Profiling and Toxicity Following Long-Term, Low Dose Exposure of Human Lung Cells to Ni and NiO Nanoparticles-Comparison with NiClNanomaterials (Basel, Switzerland) · 2020Article
- Tumorigenic effects of TLX overexpression in HEK 293T cells.Cancer reports (Hoboken, N.J.) · 2019Article
- Article
- Establishing a distributed national research infrastructure providing bioinformatics support to life science researchers in Australia.Briefings in bioinformatics · 2019Article
- Article
- On-demand virtual research environments using microservices.PeerJ. Computer science · 2019Article
- Clonal relatedness in tumour pairs of breast cancer patients.Breast cancer research : BCR · 2018Article
- Mitochondrial genomes reveal an east to west cline of steppe ancestry in Corded Ware populations.Scientific reports · 2018Article
- Article
- Tracking the NGS revolution: managing life science research on shared high-performance computing clusters.GigaScience · 2018Article
- RNA-sequencing reveals long-term effects of silver nanoparticles on human lung cells.Scientific reports · 2018Article
- Heterogeneous Patterns of Genetic Diversity and Differentiation in European and Siberian Chiffchaff (G3 (Bethesda, Md.) · 2017Article
- A female Viking warrior confirmed by genomics.American journal of physical anthropology · 2017Article
- Diatoms dominate the eukaryotic metatranscriptome during spring in coastal 'dead zone' sediments.Proceedings. Biological sciences · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
: Analyzing and storing data and results from next-generation sequencing (NGS) experiments is a challenging task, hampered by ever-increasing data volumes and frequent updates of analysis methods and tools. Storage and computation have grown beyond the capacity of personal computers and there is a need for suitable e-infrastructures for processing. Here we describe UPPNEX, an implementation of such an infrastructure, tailored to the needs of data storage and analysis of NGS data in Sweden serving various labs and multiple instruments from the major sequencing technology platforms. UPPNEX comprises resources for high-performance computing, large-scale and high-availability storage, an extensive bioinformatics software suite, up-to-date reference genomes and annotations, a support function with system and application experts as well as a web portal and support ticket system. UPPNEX applications are numerous and diverse, and include whole genome-, de novo- and exome sequencing, targeted resequencing, SNP discovery, RNASeq, and methylation analysis. There are over 300 projects that utilize UPPNEX and include large undertakings such as the sequencing of the flycatcher and Norwegian spruce. We describe the strategic decisions made when investing in hardware, setting up maintenance and support, allocating resources, and illustrate major challenges such as managing data growth. We conclude with summarizing our experiences and observations with UPPNEX to date, providing insights into the successful and less successful decisions made.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.