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dc.contributorMorić, Ivana
dc.contributorĐorđević, Valentina
dc.creatorMilivojević Dimitrijević, Nevena
dc.creatorIvanović, Miloš
dc.creatorŽivić, Andreja
dc.creatorLjujić, Biljana
dc.creatorGazdić Janković, Marina
dc.creatorProsenc Zmrzljak, Uršula
dc.creatorMirić, Ana
dc.creatorĐorđević, Valentina
dc.creatorPuač, Feđa
dc.creatorŽivanović, Marko
dc.creatorFilipović, Nenad
dc.date.accessioned2024-07-24T21:56:50Z
dc.date.available2024-07-24T21:56:50Z
dc.date.issued2024
dc.identifier.uri978-86-82679-16-5
dc.identifier.uriwww.belbi.bg.ac.rs
dc.identifier.urihttps://imagine.imgge.bg.ac.rs/handle/123456789/2456
dc.description.abstractTranscriptome profiling at the single cell level is crucial for understanding complex biological systems and molecular mechanisms. We wanted to unravel the influence of polystyrene nanoparticles on peripheral blood mononuclear cells (PBMCs), using microfluidic technology. A total of 4 single-cell sequencing libraries were analyzed (one control and three different treatments). Thousands of individual cells per sample are Barcoded separately to index the transcriptome of each cell individually. Raw sequencing data were analyzed with the Cell Ranger software and visualized using Loupe Browser software. Set of analysis pipelines processes Chromium Single Gene Expression data to align reads, generate Feature Barcode matrices, and perform clustering and gene expression analysis. Each element of the matrix is the number of UMIs (Unique Molecular Identifier) associated with a feature (row) and a barcode (column). Principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) algorithms on single-cell sequencing samples were carried out. The expressed cells were clustered during which typical cell marker genes were used for annotation. Genes showing adjusted p-value < 0.05 and |log2 (fold change) | > 0.5 were considered to be marker genes. Loupe Browser was used for visualization of clusters and analysis of the single-cell data. In this way, gene markers for individual cell types obtained by single-cell sequencing represent a good model for the analysis of biological events.sr
dc.language.isoensr
dc.publisherBelgrade : Institute of Molecular Genetics and Genetic Engineeringsr
dc.relationinfo:eu-repo/grantAgreement/MESTD/inst-2020/200378/RS//sr
dc.relationinfo:eu-repo/grantAgreement/MESTD/inst-2020/200111/RS//sr
dc.rightsopenAccesssr
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source5th Belgrade Bioinformatics Conferencesr
dc.subjectbioinformaticssr
dc.subjectsingle cellsr
dc.subjectsequencingsr
dc.subjectscRNA-seqsr
dc.subjectmicrofluidicsr
dc.titleDeciphering the effects of nanosized polystyrene particlessr
dc.typearticlesr
dc.rights.licenseBY-NC-NDsr
dc.citation.epage61
dc.citation.spage61
dc.description.otherBook of abstracts: 5th Belgrade Bioinformatics Conference, Serbia, Belgrade,17-20 june 2024.sr
dc.identifier.fulltexthttps://imagine.imgge.bg.ac.rs/bitstream/id/845705/BelBi2024-Book-of-Abstracts_1-16,77,141-142.pdf
dc.identifier.rcubhttps://hdl.handle.net/21.15107/rcub_imagine_2456
dc.type.versionpublishedVersionsr


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