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DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.

ABSTRACT: We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves the identification and quantification performance in conventional DIA proteomic applications, and is particularly beneficial for high-throughput applications, as it is fast and enables deep and confident proteome coverage when used in combination with fast chromatographic methods.

SUBMITTER: Demichev V

PROVIDER: S-EPMC6949130 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.

Demichev Vadim V Messner Christoph B CB Vernardis Spyros I SI Lilley Kathryn S KS Ralser Markus M

Nature methods 20191125 1

We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves the identification and quantification performance in conventional DIA proteomic applications, and is particularly beneficial for high-throughput applications, as it is fast and enables deep and confident proteome coverage when used in combination with ...[more]

PMID: 31768060

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