Conducting gene set tests in meta‐analyses of transcriptome expression data-Reference-Cited by-同舟云学术

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Conducting gene set tests in meta‐analyses of transcriptome expression data

Published:2019-02-07 Issue:1 Volume:10 Page:99-112
ISSN:1759-2879
Container-title:Research Synthesis Methods
language:en
Short-container-title:Res Syn Meth

Author:

Kosch Robin¹^ORCID,Jung Klaus¹^ORCID

Affiliation:

1. Institute for Animal Breeding and GeneticsUniversity of Veterinary Medicine Hannover Hannover Germany

Funder

Ministry of Science and Culture of Lower Saxony, Germany

Publisher

Wiley

Subject

Education

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jrsm.1337

Reference45 articles.

1. Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray

2. Next-generation sequencing transforms today's biology

3. Methods to increase reproducibility in differential gene expression via meta-analysis

4. Repeatability of published microarray gene expression analyses

5. Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data

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1. Batch normalization followed by merging is powerful for phenotype prediction integrating multiple heterogeneous studies;PLOS Computational Biology;2023-10-16

2. Batch Normalization Followed by Merging Is Powerful for Phenotype Prediction Integrating Multiple Heterogeneous Studies;2022-09-28

3. The Tsallis generalized entropy enhances the interpretation of transcriptomics datasets;PLOS ONE;2022-04-21

4. Large-scale comparative transcriptomic analysis of temperature-responsive genes in Arabidopsis thaliana;Plant Molecular Biology;2022-01-01

5. Comparison of merging strategies for building machine learning models on multiple independent gene expression data sets;Statistical Analysis and Data Mining: The ASA Data Science Journal;2021-09-13

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