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Effect of single-cell RNA sequencing parameters on cluster stability
Thesis (MSc)--Stellenbosch University, 2025.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : Stellenbosch University
2025
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| _version_ | 1867613918920179712 |
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| access_status_str | Open Access |
| author | Potgieter, Tiqvah Talya |
| author2 | Maasdorp, Elizna |
| author_browse | Maasdorp, Elizna Potgieter, Tiqvah Talya |
| author_facet | Maasdorp, Elizna Potgieter, Tiqvah Talya |
| author_sort | Potgieter, Tiqvah Talya |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MSc)--Stellenbosch University, 2025. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/132494 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:43:47.401Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/132494 Effect of single-cell RNA sequencing parameters on cluster stability Potgieter, Tiqvah Talya Maasdorp, Elizna Patterton, Hugh Stellenbosch University. Faculty of Science. Center for Bioinformatics and Computational Biology. Gene expression -- Data processing Cluster analysis -- Data processing Stability Nucleotide sequence -- Technique Cells -- Analysis Single-cell RNA sequencing UCTD Thesis (MSc)--Stellenbosch University, 2025. Potgieter, T. T. 2025. Effect of Single-Cell RNA Sequencing Parameters on Cluster Stability. Unpublished masters thesis. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/7220d82f-7182-4eb7-8dfd-90bd03c01c16 ENGLISH ABSTRACT: Single-cell RNA sequencing has allowed us to study gene expression at a single-cell level, enabling researchers to unravel the heterogeneity and complexity within individual cells. Clustering has made this possible as it identifies and groups different cells based on their expression profiles, clustering also plays a critical role in exploratory research and thus, understanding the quality of clustering and clustering outcomes is essential. However, cluster analysis remains one of the most challenging and fundamental tasks in a scRNA-seq analysis. This is mainly due to the fact that there is no ground truth or gold standard by which performance can be measured. Additionally, clustering itself is governed by a range of parameters and processing methods. Cluster stability assessments aim to address these challenges by defining how robust clustering results are under perturbations to the original dataset. The assumption is that stable clustering results represent the underlying structure of the data and thus should be consistent across an ensemble of perturbed datasets. We investigated the effects of various processing parameters on cluster stability in scRNA-seq data. For each parameter, cluster stability was quantified by generating a cluster ensemble with respect to different initializations and calculating the average scores using relevant stability metrics. Results presented here showed great variability, indicating that cluster stability is sensitive to the choices of parameter setting as well as the type of dataset. We emphasize that users should not rely on a once-off application of a clustering algorithm to their data but explore various parameter possibilities and assess the robustness of clustering partitions with respect to changes in these parameters. AFRIKAANSE OPSOMMING: Enkel sel-RNS-volgorde bepaling het ons in staat gestel om selle op ’n enkel vlak te bestudeer. Hierdie bemagtig navorsers om die heterogeniteit en kompleksiteit binne individuele selle te ontrafel. Groepering (clustering) het dit moontlik gemaak deur verskillende selle te identifiseer en te groepeer op grond van hul uitdrukkings profiele. Groepering speel ook ’n kritieke rol in verkennende navorsing, en daarom is dit noodsaaklik om die kwaliteit en uitkomste van groepering te verstaan. Tog bly groeperings analise een van die mees uitdagende en fundamentele take in ’n enkelsel-RNA- volgorde-analise. Dit is hoofsaaklik omdat daar geen vaste waarheid of goue standaard is waarteen prestasie gemeet kan word nie. Verder word groepering beïnvloed deur ’n reeks parameters en verwerkings metodes. Groeperings stabiliteits assesserings poog om hierdie uitdagings aan te spreek om te bepaal hoe robuust groeperings resultate is onder versteurings aan die oorspronklike datastel. Die aanname is dat stabiele groeperings resultate die onderliggende struktuur van die data weerspieël en dus behoort dit stabiel te wees oor ’n versameling van versteurde datastelle. Ons het die effek van verskeie verwerkings parameters op groeperings stabiliteit in enkelsel-RNS- volgorde data ondersoek. Vir elke parameter is groeperings stabiliteit gekwantifiseer deur ’n groeperings data te genereer met betrekking tot verskillende initialiserings en die gemiddelde tellings met toepaslike stabiliteits metings te bereken. Die resultate wat hier aangebied word, het groot variasie getoon, wat aandui dat groeperings stabiliteit sensitief is vir die keuse van parameter instellings sowel as die tipe datastel. Ons beklemtoon dat gebruikers nie op ’n eenmalige toepassing van ’n groeperings algoritme op hul data moet staatmaak nie, maar eerder verskeie parameter opsies moet ondersoek en die robuustheid van groeperings afdelings met betrekking tot veranderinge in hierdie parameters moet evalueer. Masters 2025-06-10T06:17:00Z 2025-06-10T06:17:00Z 2025-03 Thesis https://scholar.sun.ac.za/handle/10019.1/132494 en Stellenbosch University xi, 90 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Gene expression -- Data processing Cluster analysis -- Data processing Stability Nucleotide sequence -- Technique Cells -- Analysis Single-cell RNA sequencing UCTD Potgieter, Tiqvah Talya Effect of single-cell RNA sequencing parameters on cluster stability |
| title | Effect of single-cell RNA sequencing parameters on cluster stability |
| title_full | Effect of single-cell RNA sequencing parameters on cluster stability |
| title_fullStr | Effect of single-cell RNA sequencing parameters on cluster stability |
| title_full_unstemmed | Effect of single-cell RNA sequencing parameters on cluster stability |
| title_short | Effect of single-cell RNA sequencing parameters on cluster stability |
| title_sort | effect of single cell rna sequencing parameters on cluster stability |
| topic | Gene expression -- Data processing Cluster analysis -- Data processing Stability Nucleotide sequence -- Technique Cells -- Analysis Single-cell RNA sequencing UCTD |
| url | https://scholar.sun.ac.za/handle/10019.1/132494 |
| work_keys_str_mv | AT potgietertiqvahtalya effectofsinglecellrnasequencingparametersonclusterstability |