Identifying genes with location dependent noise variance in spatial transcriptomics data
This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022.
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| Jazyk: | English |
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Brac University
2023
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| On-line přístup: | http://hdl.handle.net/10361/18685 |
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10361-186852023-07-09T21:04:21Z Identifying genes with location dependent noise variance in spatial transcriptomics data Abrar, Mohammed Abid Kaykobad, Mohammad Samee, Md. Abul Hassan Department of Computer Science and Engineering, Brac University Spatial transcriptomics Computational biology This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 34-42). Spatial transcriptomics (ST) holds the promise to identify the existence and extent of spatial variation of gene expression in complex tissues. Such analyses could help identify gene expression signatures that distinguish between physiology and disease. Existing tools to detect spatially variable genes assume a constant noise variance across location (homoscedastic). This assumption might miss important biological signals when the variance could change across locations, e.g., in the tumor microenvironment. As an alternative, we propose NoVaTeST, a novel method to identify genes with location-dependent noise variance in ST data. NoVaTeST models gene expression as a function of location with a heteroscedastic noise. It then compares the model to one with homoscedastic noise to detect genes that show significant spatial variation in noise. Our results show genes detected by NoVaTeST provide complimentary information to existing tools while providing important biological insights. Mohammed Abid Abrar M. Computer Science and Engineering 2023-07-09T06:34:24Z 2023-07-09T06:34:24Z 2023 2022-12 Thesis ID 20366020 http://hdl.handle.net/10361/18685 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 42 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Spatial transcriptomics Computational biology |
| spellingShingle |
Spatial transcriptomics Computational biology Abrar, Mohammed Abid Identifying genes with location dependent noise variance in spatial transcriptomics data |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022. |
| author2 |
Kaykobad, Mohammad |
| author_facet |
Kaykobad, Mohammad Abrar, Mohammed Abid |
| format |
Thesis |
| author |
Abrar, Mohammed Abid |
| author_sort |
Abrar, Mohammed Abid |
| title |
Identifying genes with location dependent noise variance in spatial transcriptomics data |
| title_short |
Identifying genes with location dependent noise variance in spatial transcriptomics data |
| title_full |
Identifying genes with location dependent noise variance in spatial transcriptomics data |
| title_fullStr |
Identifying genes with location dependent noise variance in spatial transcriptomics data |
| title_full_unstemmed |
Identifying genes with location dependent noise variance in spatial transcriptomics data |
| title_sort |
identifying genes with location dependent noise variance in spatial transcriptomics data |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/18685 |
| work_keys_str_mv |
AT abrarmohammedabid identifyinggeneswithlocationdependentnoisevarianceinspatialtranscriptomicsdata |
| _version_ |
1814307206873481216 |