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Batch correction
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To fully utilize the power of single-cell RNA sequencing (scRNA-seq) technologies for identifying cell lineages and bona fide transcriptional signals, it is necessary to combine data from multiple experiments. We present BERMUDA (Batch Effect ReMoval Using Deep Autoencoders), a novel transfer-learning-based method for batch effect correction in scRNA-seq data.
15p
vielonmusk
30-01-2022
13
0
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The incorporation of unique molecular identifiers (UMIs) in single-cell RNA-seq assays makes possible the identification of duplicated molecules, thereby facilitating the counting of distinct molecules from sequenced reads.
18p
viarchimedes
26-01-2022
7
0
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Large-scale single-cell transcriptomic datasets generated using different technologies contain batchspecific systematic variations that present a challenge to batch-effect removal and data integration. With continued growth expected in scRNA-seq data, achieving effective batch integration with available computational resources is crucial.
32p
viarchimedes
26-01-2022
15
0
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Genomic data production is at its highest level and continues to increase, making available novel primary data and existing public data to researchers for exploration. Here we explore the consequences of “batch” correction for biological discovery in two publicly available expression datasets.
10p
vioklahoma2711
19-11-2020
7
2
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Batch effects are a persistent and pervasive form of measurement noise which undermine the scientific utility of high-throughput genomic datasets. At their most benign, they reduce the power of statistical tests resulting in actual effects going unidentified.
17p
vioklahoma2711
19-11-2020
10
1
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Batch effects were not accounted for in most of the studies of computational drug repositioning based on gene expression signatures. It is unknown how batch effect removal methods impact the results of signature-based drug repositioning.
14p
vicolorado2711
23-10-2020
8
1
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Systematic technical effects-also called batch effects-are a considerable challenge when analyzing DNA methylation (DNAm) microarray data, because they can lead to false results when confounded with the variable of interest.
15p
vicolorado2711
22-10-2020
9
0
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Our previous publications and the data presented here provide evidences on the ability of plantbased culture media to optimize the cultivability of rhizobacteria and to support their recovery from plant-soil environments. Compared to the tested chemically-synthetic culture media (e.g. nutrient agar and N-deficient combined-carbon sources media), slurry homogenates, crude saps, juices and powders of cactus (Opuntia ficus-indica) and succulent plants (Aloe vera and Aloe arborescens) were rich enough to support growth of rhizobacteria. Representative isolates of Enterobacter spp.
12p
kequaidan1
16-11-2019
21
1
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Which of the following is a correct statement in regard to prototyping? a) It is more suitable for batch systems than GUI-based interactive systems. b) Effectiveness can be increased by repeatedly remaking the prototype.
0p
kimku1
28-08-2011
49
8
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