randel/MIND: Using Tissue Expression to Estimate Sample-/Subject- And Cell-Type-Specific Gene Expression via Deconvolution
Methods to glean more insights from bulk gene expression: MIND and bMIND. MIND borrows information across multiple measurements of the same tissue per subject, such as multiple regions of the brain, using an empirical Bayes approach to estimate subject- and cell-type-specific (CTS) gene expression via deconvolution. The bMIND algorithm provides Bayesian estimates of sample-level CTS expression for each bulk sample.
Getting started
Browse package contents
Package details |
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| Author | Jiebiao Wang |
| Maintainer | Jiebiao Wang <randel.wang@gmail.com> |
| License | GPL |
| Version | 0.3.3 |
| URL | https://github.com/randel/MIND |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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