التفاصيل البيبلوغرافية
| العنوان: |
Learning single-cell chromatin accessibility profiles using meta-analytic marker genes. |
| المؤلفون: |
Kawaguchi, Risa Karakida1 (AUTHOR), Tang, Ziqi1 (AUTHOR), Fischer, Stephan1 (AUTHOR), Rajesh, Chandana1 (AUTHOR), Tripathy, Rohit1 (AUTHOR), Koo, Peter K1 (AUTHOR), Gillis, Jesse1,2 (AUTHOR) jesse.gillis@utoronto.ca |
| المصدر: |
Briefings in Bioinformatics. Jan2023, Vol. 24 Issue 1, p1-12. 12p. |
| مصطلحات موضوعية: |
MACHINE learning, CHROMATIN, NUCLEOTIDE sequence, BINDING sites, GENES, TRANSCRIPTION factors |
| مستخلص: |
Motivation Single-cell assay for transposase accessible chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate. Results In this study, we perform a systematic comparison of seven scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta%5fscATACTest. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner. [ABSTRACT FROM AUTHOR] |
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