Comparison of confound adjustment methods in the construction of gene co-expression networks
Abstract Adjustment for confounding sources of expression variation is an important preprocessing step in large gene expression studies, but the effect of confound adjustment on co-expression network analysis has not been well-characterized. Here, we demonstrate that the choice of confound adjustment method can have a considerable effect on the architecture of the resulting co-expression network. We compare standard and alternative confound adjustment methods and provide recommendations for their use in the construction of gene co-expression networks from bulk tissue RNA-seq datasets..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
bioRxiv.org - (2022) vom: 25. Mai Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Cote, A.C. [VerfasserIn] |
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| Links: |
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| doi: |
10.1101/2021.05.18.444709 |
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| PPN (Katalog-ID): |
XBI020607512 |
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| 520 | |a Abstract Adjustment for confounding sources of expression variation is an important preprocessing step in large gene expression studies, but the effect of confound adjustment on co-expression network analysis has not been well-characterized. Here, we demonstrate that the choice of confound adjustment method can have a considerable effect on the architecture of the resulting co-expression network. We compare standard and alternative confound adjustment methods and provide recommendations for their use in the construction of gene co-expression networks from bulk tissue RNA-seq datasets. | ||
| 700 | 1 | |a Young, H.E. |e verfasserin |4 aut | |
| 700 | 1 | |a Huckins, L.M. |e verfasserin |4 aut | |
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