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Processed datasets and codes for differential expression analysis on polulation-level RNA-seq data

This version includes codes and data necessary to reproduce all results in our response to the correspondences ("Response to 'Neglecting normalization impact in semi‑synthetic RNA‑seq data simulation generates artificial false positives' and 'Winsorization greatly reduces false positives by popul

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CreatorYumei Li
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Published2024-12-24
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DOI10.5281/zenodo.14550340
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Downloads3,226
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Licensecc-by-4.0
File Size2.0 MB
Data TypeDataset
Published2024
Licensecc-by-4.0
Total Views2,491
Total Downloads3,226

This version includes codes and data necessary to reproduce all results in our response to the correspondences (“Response to ‘Neglecting normalization impact in semi‑synthetic RNA‑seq data simulation generates artificial false positives’ and ‘Winsorization greatly reduces false positives by popular differential expression methods when analyzing human population samples'”) (https://doi.org/10.1186/s13059-024-03232-8).

It also includes a README file to guide the reproduction of the results in our original publication and resources for the goodness of fit test in the original publication, “Exaggerated False Positives by Popular Differential Expression Methods When Analyzing Human Population Samples” (https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02648-4).

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Processed datasets and codes for differential expression analysis… (Full Dataset)2.0 MB
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Files are hosted on the source repository. Click download to access the full dataset.

Yumei Li (2024). Processed datasets and codes for differential expression analysis on polulation-level RNA-seq data. https://doi.org/10.5281/zenodo.14550340