Benchmark of pre-processing pipelines of single cell RNA sequencing data

Single cell RNA sequencing (scRNA-Seq) is a very powerful tool to study the transcriptome. Several tools are available to pre-process the data it produces. However, no standard exists. The objective of this work is to compare four scRNA-Seq pre-processing tools and extract conclusions regarding the...

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Bibliographic Details
Author: Jiménez Sánchez, Dídac
Format: master thesis
Publication Date:2023
Country:España
Institution:Universitat Oberta de Catalunya (UOC)
Repository:O2, repositorio institucional de la UOC
OAI Identifier:oai:openaccess.uoc.edu:10609/148591
Online Access:http://hdl.handle.net/10609/148591
Access Level:Open access
Keyword:scRNA-seq
bioinformatics
preprocessing
Bioinformatics -- TFM
Bioinformàtica -- TFM
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spelling Benchmark of pre-processing pipelines of single cell RNA sequencing dataJiménez Sánchez, DídacscRNA-seqbioinformaticspreprocessingBioinformatics -- TFMBioinformàtica -- TFMSingle cell RNA sequencing (scRNA-Seq) is a very powerful tool to study the transcriptome. Several tools are available to pre-process the data it produces. However, no standard exists. The objective of this work is to compare four scRNA-Seq pre-processing tools and extract conclusions regarding the advancements over recent years, and to determine the superior tool. The tools compared were (i) UMI Tools, one of the first published tools, which served as reference point, (ii) Salmon Alevin, a tool with many interesting features, (iii) Kallisto Bustools, a tool focused on computational efficiency and (iv) STARSolo, a recent implementation to a popular aligner. I designed 4 pipelines in bash to implement each tool, and I implemented a downstream analysis to evaluate the biological significance of the results. I compared the computational speed and efficiency, the count matrices produced and the biological results. For the comparisons, I used the datasets provided by Tabula Muris as ground truth. I found that Kallisto Bustools was significantly more efficient and faster, while UMI Tools was the slowest tool. The count matrices produced were consistent with the ground truth for UMI Tools and Kallisto Bustools while Salmon Alevin and STARSolo presented inconsistencies. The biological results were coherent, although Salmon Alevin showed problematics. I concluded that scRNA-Seq has progressed in recent years but more so in computational efficiency. Kallisto Bustools was the fastest and most consistent tool among those evaluated.El single-cell RNA sequencing (scRNA-Seq) és una eina molt potent per estudiar el transcriptoma. Hi ha diverses eines disponibles per preprocessar les dades que se n'obtenen. Tanmateix, no existeix cap estàndard. L'objectiu d'aquest treball és comparar quatre eines de preprocessament de scRNA-Seq, extreure conclusions sobre els avenços dels darrers anys, i determinar si hi ha una eina superior. Les eines comparades han sigut (i) UMI Tools, una de les primeres eines publicades, que serveix de punt de referència, (ii) Salmon Alevin, una eina amb moltes característiques interessants, (iii) Kallisto Bustools, una eina centrada en l'eficiència computacional i (iv) STARSolo, una implementació recent sobre un aligner popular. He dissenyat 4 pipelines en bash per implementar cada eina i he implementat un anàlisi downstream per a avaluar la significació biològica dels resultats. He comparat la velocitat i l'eficiència computacional, les count matrix produïdes i els resultats biològics. Per a les comparacions, he utilitzat els conjunts de dades proporcionats per Tabula Muris com a ground truth. He trobat que Kallisto Bustools és significativament més ràpid i eficient, mentre que UMI Tools és l'eina més lenta. Les count matrix produïdes per UMI Tools i Kallisto Bustools han estat coherents amb la ground truth, mentre que les produïdes per Salmon Alevin i STARSolo presentaven inconsistències. Els resultats biològics han sigut coherents, tot i que Salmon Alevin ha presentat problemes. Concloc que el preprocessat de dades de scRNA-Seq ha progressat en els darrers anys, però més en eficiència computacional. Kallisto Bustools es l'eina més ràpida i consistent entre les avaluades.Universitat Oberta de Catalunya (UOC)Saera-Vila, Alfonso202320232023info:eu-repo/semantics/masterThesisapplication/pdfapplication/pdfhttp://hdl.handle.net/10609/148591reponame:O2, repositorio institucional de la UOCinstname:Universitat Oberta de Catalunya (UOC)InglésCC BY-NC-NDhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:openaccess.uoc.edu:10609/1485912026-05-28T12:42:01Z
dc.title.none.fl_str_mv Benchmark of pre-processing pipelines of single cell RNA sequencing data
title Benchmark of pre-processing pipelines of single cell RNA sequencing data
spellingShingle Benchmark of pre-processing pipelines of single cell RNA sequencing data
Jiménez Sánchez, Dídac
scRNA-seq
bioinformatics
preprocessing
Bioinformatics -- TFM
Bioinformàtica -- TFM
title_short Benchmark of pre-processing pipelines of single cell RNA sequencing data
title_full Benchmark of pre-processing pipelines of single cell RNA sequencing data
title_fullStr Benchmark of pre-processing pipelines of single cell RNA sequencing data
title_full_unstemmed Benchmark of pre-processing pipelines of single cell RNA sequencing data
title_sort Benchmark of pre-processing pipelines of single cell RNA sequencing data
dc.creator.none.fl_str_mv Jiménez Sánchez, Dídac
author Jiménez Sánchez, Dídac
author_facet Jiménez Sánchez, Dídac
author_role author
dc.contributor.none.fl_str_mv Saera-Vila, Alfonso
dc.subject.none.fl_str_mv scRNA-seq
bioinformatics
preprocessing
Bioinformatics -- TFM
Bioinformàtica -- TFM
topic scRNA-seq
bioinformatics
preprocessing
Bioinformatics -- TFM
Bioinformàtica -- TFM
description Single cell RNA sequencing (scRNA-Seq) is a very powerful tool to study the transcriptome. Several tools are available to pre-process the data it produces. However, no standard exists. The objective of this work is to compare four scRNA-Seq pre-processing tools and extract conclusions regarding the advancements over recent years, and to determine the superior tool. The tools compared were (i) UMI Tools, one of the first published tools, which served as reference point, (ii) Salmon Alevin, a tool with many interesting features, (iii) Kallisto Bustools, a tool focused on computational efficiency and (iv) STARSolo, a recent implementation to a popular aligner. I designed 4 pipelines in bash to implement each tool, and I implemented a downstream analysis to evaluate the biological significance of the results. I compared the computational speed and efficiency, the count matrices produced and the biological results. For the comparisons, I used the datasets provided by Tabula Muris as ground truth. I found that Kallisto Bustools was significantly more efficient and faster, while UMI Tools was the slowest tool. The count matrices produced were consistent with the ground truth for UMI Tools and Kallisto Bustools while Salmon Alevin and STARSolo presented inconsistencies. The biological results were coherent, although Salmon Alevin showed problematics. I concluded that scRNA-Seq has progressed in recent years but more so in computational efficiency. Kallisto Bustools was the fastest and most consistent tool among those evaluated.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv http://hdl.handle.net/10609/148591
url http://hdl.handle.net/10609/148591
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv CC BY-NC-ND
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv CC BY-NC-ND
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universitat Oberta de Catalunya (UOC)
publisher.none.fl_str_mv Universitat Oberta de Catalunya (UOC)
dc.source.none.fl_str_mv reponame:O2, repositorio institucional de la UOC
instname:Universitat Oberta de Catalunya (UOC)
instname_str Universitat Oberta de Catalunya (UOC)
reponame_str O2, repositorio institucional de la UOC
collection O2, repositorio institucional de la UOC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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