Evaluation of imputation methods through differential expression analysis on H1-EC dataset.

<p>The ACC (<b>A</b>) and AUC (<b>B</b>) scores of which the reference are set as the top 200, 400, 600, 800 and 1000 genes sorted by adjusted <i>P</i> values from the bulk data.</p> <p>(PDF)</p>

Publication Details

Journal
Figshare
Published
2024-08-08
DOI
https://doi.org/10.1371/journal.pcbi.1012339.s011
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluation of imputation methods through differential expression analysis on H1-EC dataset.

Figshare
Gene expression and cancer classification
article

Evaluation of imputation methods through differential expression analysis on H1-EC dataset.

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Abstract

<p>The ACC (<b>A</b>) and AUC (<b>B</b>) scores of which the reference are set as the top 200, 400, 600, 800 and 1000 genes sorted by adjusted <i>P</i> values from the bulk data.</p> <p>(PDF)</p>

Figshare
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Openalex Percentile: Top 72%
Gene expression and cancer classification
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Evaluation of imputation methods through differential expression analysis on H1-EC dataset. · Figshare (2024) | TGRS Research Map | TGRS