التفاصيل البيبلوغرافية
| العنوان: |
malbacR: A Package for Standardized Implementation of Batch Correction Methods for Omics Data. |
| المؤلفون: |
Leach DT; Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99354, United States., Stratton KG; Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99354, United States., Irvahn J; Artificial Intelligence and Data Analytics Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99354, United States., Richardson R; Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99354, United States., Webb-Robertson BM; Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99354, United States., Bramer LM; Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, Washington 99354, United States. |
| المصدر: |
Analytical chemistry [Anal Chem] 2023 Aug 22; Vol. 95 (33), pp. 12195-12199. Date of Electronic Publication: 2023 Aug 08. |
| نوع المنشور: |
Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: American Chemical Society Country of Publication: United States NLM ID: 0370536 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1520-6882 (Electronic) Linking ISSN: 00032700 NLM ISO Abbreviation: Anal Chem Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: Washington, American Chemical Society. |
| مواضيع طبية MeSH: |
Algorithms* , Research Design*, Chromatography, Liquid/methods ; Mass Spectrometry/methods ; Gas Chromatography-Mass Spectrometry |
| مستخلص: |
Mass spectrometry is a powerful tool for identifying and analyzing biomolecules such as metabolites and lipids in complex biological samples. Liquid chromatography and gas chromatography mass spectrometry studies quite commonly involve large numbers of samples, which can require significant time for sample preparation and analyses. To accommodate such studies, the samples are commonly split into batches. Inevitably, variations in sample handling, temperature fluctuation, imprecise timing, column degradation, and other factors result in systematic errors or biases of the measured abundances between the batches. Numerous methods are available via R packages to assist with batch correction for omics data; however, since these methods were developed by different research teams, the algorithms are available in separate R packages, each with different data input and output formats. We introduce the malbacR package, which consolidates 11 common batch effect correction methods for omics data into one place so users can easily implement and compare the following: pareto scaling, power scaling, range scaling, ComBat, EigenMS, NOMIS, RUV-random, QC-RLSC, WaveICA2.0, TIGER, and SERRF. The malbacR package standardizes data input and output formats across these batch correction methods. The package works in conjunction with the pmartR package, allowing users to seamlessly include the batch effect correction in a pmartR workflow without needing any additional data manipulation. |
| تواريخ الأحداث: |
Date Created: 20230808 Date Completed: 20230823 Latest Revision: 20230823 |
| رمز التحديث: |
20230823 |
| DOI: |
10.1021/acs.analchem.3c01289 |
| PMID: |
37551970 |
| قاعدة البيانات: |
MEDLINE |
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