Pregled bibliografske jedinice broj: 816850
Normalization and batch correction methods for high-throughput glycomics
Normalization and batch correction methods for high-throughput glycomics // XXIII International Symposium on Glycoconjugates (GLYCO 23) / Glycoconjugate Journal 32 (2015) (5) 173-312 (ur.).
Split, Hrvatska, 2015. str. 242-242 (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 816850 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Normalization and batch correction methods for high-throughput glycomics
Autori
Vučković, Frano ; Ugrina, Ivo ; Lauc, Gordan ; Aulchenko, Yurii
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
XXIII International Symposium on Glycoconjugates (GLYCO 23)
/ Glycoconjugate Journal 32 (2015) (5) 173-312 - , 2015, 242-242
Skup
XXIII International Symposium on Glycoconjugates (GLYCO 23)
Mjesto i datum
Split, Hrvatska, 15.09.2015. - 20.09.2015
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
batch effects; normalization; noise; glycomics
Sažetak
Glycomics is rapidly emerging field in high-throughput biology that aims to systematically study glycan structures of a given protein, cell type or organic system. As it is characteristic for any other high-throughput method in biology (microarrays, next-generation sequencing, mass spectrometry), accuracy of high-throughput glycomics methods is highly affected by complicated experimental procedure. Standard experiment requires highly trained personnel, complicated sample collection and preparation procedure, large set of chemicals and calibrated machines. Standard study includes 1000 to 2000 samples, experiment can take several months and during that time many experimental conditions can vary. As a consequence, differences in experimental procedure represent huge source of variation and need for normalization and batch correction arises naturally. We compared most popular normalization and batch correction methods, from microarray and metabolomics field, on several glycomics datasets. We evaluated them based on variation of standards and correlation of replicates. According to standard variation and replicate correlation measures, every normalization and batch correction method performs relatively well, showing that use of any preprocessing method decreases experimental variation and increases the statistical power of the analysis.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Biologija
POVEZANOST RADA
Ustanove:
Farmaceutsko-biokemijski fakultet, Zagreb,
GENOS d.o.o.
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE