Deciphering the effects of nanosized polystyrene particles
Autori
Milivojević Dimitrijević, NevenaIvanović, Miloš
Živić, Andreja
Ljujić, Biljana
Gazdić Janković, Marina
Prosenc Zmrzljak, Uršula
Mirić, Ana
Đorđević, Valentina
Puač, Feđa
Živanović, Marko
Filipović, Nenad
Ostala autorstva
Morić, IvanaĐorđević, Valentina
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
Transcriptome 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 neighb...or 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.
Ključne reči:
bioinformatics / single cell / sequencing / scRNA-seq / microfluidicIzvor:
5th Belgrade Bioinformatics Conference, 2024, 61-61Izdavač:
- Belgrade : Institute of Molecular Genetics and Genetic Engineering
Finansiranje / projekti:
- Ministarstvo nauke, tehnološkog razvoja i inovacija Republike Srbije, institucionalno finansiranje - 200378 (Institut za informacione tehnologije, Kragujevac) (RS-MESTD-inst-2020-200378)
- Ministarstvo nauke, tehnološkog razvoja i inovacija Republike Srbije, institucionalno finansiranje - 200111 (Univerzitet u Kragujevcu, Medicinski fakultet) (RS-MESTD-inst-2020-200111)
Napomena:
- Book of abstracts: 5th Belgrade Bioinformatics Conference, Serbia, Belgrade,17-20 june 2024.
Kolekcije
Institucija/grupa
Institut za molekularnu genetiku i genetičko inženjerstvoTY - JOUR AU - Milivojević Dimitrijević, Nevena AU - Ivanović, Miloš AU - Živić, Andreja AU - Ljujić, Biljana AU - Gazdić Janković, Marina AU - Prosenc Zmrzljak, Uršula AU - Mirić, Ana AU - Đorđević, Valentina AU - Puač, Feđa AU - Živanović, Marko AU - Filipović, Nenad PY - 2024 UR - 978-86-82679-16-5 UR - www.belbi.bg.ac.rs UR - https://imagine.imgge.bg.ac.rs/handle/123456789/2456 AB - Transcriptome 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. PB - Belgrade : Institute of Molecular Genetics and Genetic Engineering T2 - 5th Belgrade Bioinformatics Conference T1 - Deciphering the effects of nanosized polystyrene particles EP - 61 SP - 61 UR - https://hdl.handle.net/21.15107/rcub_imagine_2456 ER -
@article{ author = "Milivojević Dimitrijević, Nevena and Ivanović, Miloš and Živić, Andreja and Ljujić, Biljana and Gazdić Janković, Marina and Prosenc Zmrzljak, Uršula and Mirić, Ana and Đorđević, Valentina and Puač, Feđa and Živanović, Marko and Filipović, Nenad", year = "2024", abstract = "Transcriptome 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.", publisher = "Belgrade : Institute of Molecular Genetics and Genetic Engineering", journal = "5th Belgrade Bioinformatics Conference", title = "Deciphering the effects of nanosized polystyrene particles", pages = "61-61", url = "https://hdl.handle.net/21.15107/rcub_imagine_2456" }
Milivojević Dimitrijević, N., Ivanović, M., Živić, A., Ljujić, B., Gazdić Janković, M., Prosenc Zmrzljak, U., Mirić, A., Đorđević, V., Puač, F., Živanović, M.,& Filipović, N.. (2024). Deciphering the effects of nanosized polystyrene particles. in 5th Belgrade Bioinformatics Conference Belgrade : Institute of Molecular Genetics and Genetic Engineering., 61-61. https://hdl.handle.net/21.15107/rcub_imagine_2456
Milivojević Dimitrijević N, Ivanović M, Živić A, Ljujić B, Gazdić Janković M, Prosenc Zmrzljak U, Mirić A, Đorđević V, Puač F, Živanović M, Filipović N. Deciphering the effects of nanosized polystyrene particles. in 5th Belgrade Bioinformatics Conference. 2024;:61-61. https://hdl.handle.net/21.15107/rcub_imagine_2456 .
Milivojević Dimitrijević, Nevena, Ivanović, Miloš, Živić, Andreja, Ljujić, Biljana, Gazdić Janković, Marina, Prosenc Zmrzljak, Uršula, Mirić, Ana, Đorđević, Valentina, Puač, Feđa, Živanović, Marko, Filipović, Nenad, "Deciphering the effects of nanosized polystyrene particles" in 5th Belgrade Bioinformatics Conference (2024):61-61, https://hdl.handle.net/21.15107/rcub_imagine_2456 .