Academic Journal

NoVaTeST: identifying genes with location-dependent noise variance in spatial transcriptomics data

التفاصيل البيبلوغرافية
العنوان: NoVaTeST: identifying genes with location-dependent noise variance in spatial transcriptomics data
المؤلفون: Abrar, Mohammed Abid, Kaykobad, M, Rahman, M Saifur, Samee, Md Abul Hassan
المساهمون: Robinson, Peter
المصدر: Bioinformatics ; volume 39, issue 6 ; ISSN 1367-4811
بيانات النشر: Oxford University Press (OUP)
سنة النشر: 2023
الوصف: Motivation Spatial transcriptomics (ST) can reveal the existence and extent of spatial variation of gene expression in complex tissues. Such analyses could help identify spatially localized processes underlying a tissue’s function. Existing tools to detect spatially variable genes assume a constant noise variance across spatial locations. This assumption might miss important biological signals when the variance can change across locations. Results In this article, we propose NoVaTeST, a framework to identify genes with location-dependent noise variance in ST data. NoVaTeST models gene expression as a function of spatial location and allows the noise to vary spatially. NoVaTeST then statistically compares this model to one with constant noise and detects genes showing significant spatial noise variation. We refer to these genes as “noisy genes.” In tumor samples, the noisy genes detected by NoVaTeST are largely independent of the spatially variable genes detected by existing tools that assume constant noise, and provide important biological insights into tumor microenvironments. Availability and implementation An implementation of the NoVaTeST framework in Python along with instructions for running the pipeline is available at https://github.com/abidabrar-bracu/NoVaTeST.
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.1093/bioinformatics/btad372
DOI: 10.1093/bioinformatics/btad372/50530873/btad372.pdf
الاتاحة: http://dx.doi.org/10.1093/bioinformatics/btad372
https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btad372/50530873/btad372.pdf
https://academic.oup.com/bioinformatics/article-pdf/39/6/btad372/50664606/btad372.pdf
Rights: https://creativecommons.org/licenses/by/4.0/
رقم الانضمام: edsbas.8F4BF440
قاعدة البيانات: BASE
الوصف
DOI:10.1093/bioinformatics/btad372