E
Erik Borgström
Researcher at Royal Institute of Technology
Publications - 15
Citations - 390
Erik Borgström is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Genomics & Genome. The author has an hindex of 6, co-authored 14 publications receiving 316 citations. Previous affiliations of Erik Borgström include Science for Life Laboratory.
Papers
More filters
Journal ArticleDOI
Large Scale Library Generation for High Throughput Sequencing
TL;DR: The method utilizes selective precipitation of certain sizes of DNA molecules on to paramagnetic beads for cleanup and selection after standard enzymatic reactions to generate libraries for de novo and re-sequencing on the Illumina HiSeq 2000 instrument.
Journal ArticleDOI
Transplanted Bone Marrow-Derived Cells Contribute to Human Adipogenesis.
Mikael Rydén,Mehmet Uzunel,Joanna Hård,Erik Borgström,Jeff E. Mold,Erik Arner,Niklas Mejhert,Daniel P. Andersson,Yvonne Widlund,Moustapha Hassan,Christina Victoria Jones,Kirsty L. Spalding,Britt-Marie Svahn,Afshin Ahmadian,Jonas Frisén,Samuel Bernard,Jonas Mattsson,Peter Arner +17 more
TL;DR: Exome and whole-genome sequencing of single adipocytes suggests that BM/PBSC-derived progenitors contribute to adipose tissue via both differentiation and cell fusion, and at least in the setting of transplantation, BM serves as a reservoir for adipocyte progenitor cells, particularly in obese subjects.
Journal ArticleDOI
Comparison of whole genome amplification techniques for human single cell exome sequencing
TL;DR: Conclusively, the products from the AMPLI1 and MALBAC kits were shown to be most similar to the bulk samples and are therefore recommended for WGA of single cells.
Journal ArticleDOI
Phasing of single DNA molecules by massively parallel barcoding
Erik Borgström,David Redin,Sverker Lundin,Emelie Berglund,Anders F. Andersson,Afshin Ahmadian +5 more
TL;DR: The method enables use of widely available short-read-sequencing platforms to study long single molecules within a complex sample, without losing phase information.
Journal ArticleDOI
Conbase: a software for unsupervised discovery of clonal somatic mutations in single cells through read phasing
Joanna Hård,Ezeddin Al Hakim,Marie Kindblom,Åsa K. Björklund,Bengt Sennblad,Ilke Demirci,Marta Paterlini,Pedro Réu,Erik Borgström,Patrik L. Ståhl,Jakob Michaëlsson,Jeff E. Mold,Jonas Frisén +12 more
TL;DR: Conbase leverages phased read data from multiple samples in a dataset to achieve increased confidence in somatic variant calls and genotype predictions and provides superior robustness on simulated data, in vitro expanded fibroblasts and clonal lymphocyte populations isolated directly from a healthy human donor.