Suvo Chatterjee on Muck Rack

Suvo Chatterjee

As seen in: Wiley Online Library, Frontiers
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Articles

Repurposing without Reinventing the Wheel - Ensemble Models for Differential Analysis

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By Suvo Chatterjee, Erina Paul, Ziyu Liu, Jialin Gao
| biorxiv.org
Abstract Inspired by ensemble models in machine learning, we propose a general framework for aggregating multiple distinct base models to enhance the power of published differential association analysis (DAA) methods. We demonstrate this approach by augmenting popular DAA models with one or more biologically motivated alternatives.
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Group Heteroscedasticity - A Silent Saboteur of Power and False Discovery in RNA-Seq Differential Expression

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By Suvo Chatterjee, Arindam Fadikar, Vrushab Hanumesh, Siddhant Sunil Meshram
| biorxiv.org
Abstract Despite the availability of several high-profile, state-of-the-art methods, analyzing bulk RNA-Seq data continues to face significant challenges. Evidence from recent studies has highlighted that popular differential expression (DE) tools, such as edgeR and DESeq2, are susceptible to an alarmingly high false discovery rate (FDR).
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Bayesian functional data analysis over dependent regions and its application for identification of differentially methylated regions

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By Suvo Chatterjee, Biostatistics Indiana, Shrabanti Chowdhury, Duchwan Ryu
| Wiley Online Library Verified
Get access to the full version of this article. View access options below. Purchase Instant Access Item saved, go to cart 48-Hour online access $12.00 Details View the article/chapter PDF and any associated supplements and figures for a period of 48 hours. Article/Chapter can not be printed. Article/Chapter can not be downloaded. Article/Chapter can not be redistributed. Online-only access $20.00 Details Unlimited viewing of the article/chapter PDF and any associated supplements and figures.
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