iSwathX 2.0 for Processing DDA Spectral Libraries for DIA Data Analysis

Abstract An overwhelming number of proteomics software tools and algorithms have been published for different steps of Data Independent Acquisition analysis of clinical samples. Nonetheless, there is still a lack of comprehensive benchmark studies evaluating which combinations of those isolated components perform best. Here, we used 92 lymph nodes from distinct patients to create a unique benchmark dataset representing real-world inter-individual heterogeneity. The publicly available dataset comprises 118 LC-MS/MS runs with > 12 million MS2 spectra and allowed us to objectively evaluate how well different combinations of spectral libraries, DIA software, sparsity reduction, normalization and statistical tests can detect differentially abundant proteins, while also taking sample size into account. Evaluation of 2 million data analysis workflows showed that a gas phase fractionation refined spectral library in combination with DIA-NN and Significance Analysis of Microarrays reliably detected differentially abundant proteins. Furthermore, DIA-NN and Spectronaut robustly avoided the false detection of truly absent proteins.

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Deep representation features from DreamDIAXMBD improve the analysis of data-independent acquisition proteomics

Communications Biology ◽

10.1038/s42003-021-02726-6 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Mingxuan Gao ◽

Wenxian Yang ◽

Chenxin Li ◽

Yuqing Chang ◽

Yachen Liu ◽

...

Keyword(s):

Data Analysis ◽

State Of The Art ◽

Data Driven ◽

High Coverage ◽

Discriminative Models ◽

Data Independent Acquisition ◽

Fragment Ions ◽

Comprehensive Information ◽

Spectral Libraries ◽

Negative Controls

AbstractWe developed DreamDIAXMBD (denoted as DreamDIA), a software suite based on a deep representation model for data-independent acquisition (DIA) data analysis. DreamDIA adopts a data-driven strategy to capture comprehensive information from elution patterns of peptides in DIA data and achieves considerable improvements on both identification and quantification performance compared with other state-of-the-art methods such as OpenSWATH, Skyline and DIA-NN. Specifically, in contrast to existing methods which use only 6 to 10 selected fragment ions from spectral libraries, DreamDIA extracts additional features from hundreds of theoretical elution profiles originated from different ions of each precursor using a deep representation network. To achieve higher coverage of target peptides without sacrificing specificity, the extracted features are further processed by nonlinear discriminative models under the framework of positive-unlabeled learning with decoy peptides as affirmative negative controls. DreamDIA is publicly available at https://github.com/xmuyulab/DreamDIA-XMBD for high coverage and accuracy DIA data analysis.

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Removing the hidden data dependency of DIA with predicted spectral libraries

10.1101/681429 ◽

2019 ◽

Author(s):

B. Van Puyvelde ◽

S. Willems ◽

R. Gabriels ◽

S. Daled ◽

L. De Clerck ◽

...

Keyword(s):

Data Analysis ◽

Clinical Proteomics ◽

Spectrometric Data ◽

Stochastic Sampling ◽

Data Independent Acquisition ◽

Use Of Data ◽

Analysis Strategies ◽

Stochastic Data ◽

Hidden Data ◽

Spectral Libraries

Data-Independent Acquisition (DIA) generates comprehensive yet complex mass spectrometric data, which imposes the use of data-dependent acquisition (DDA) libraries for deep peptide-centric detection. We here show that DIA can be redeemed from this dependency by combining predicted fragment intensities and retention times with narrow window DIA. This eliminates variation in library building and omits stochastic sampling, finally making the DIA workflow fully deterministic. Especially for clinical proteomics, this has the potential to facilitate inter-laboratory comparison.Significance of the StudyData-independent acquisition (DIA) is quickly developing into the most comprehensive strategy to analyse a sample on a mass spectrometer. Correspondingly, a wave of data analysis strategies has followed suit, improving the yield from DIA experiments with each iteration. As a result, a worldwide wave of investments in DIA is already taking place in anticipation of clinical applications. Yet, there is considerable confusion about the most useful and efficient way to handle DIA data, given the plethora of possible approaches with little regard for compatibility and complementarity. In our manuscript, we outline the currently available peptide-centric DIA data analysis strategies in a unified graphic called the DIAmond DIAgram. This leads us to an innovative and easily adoptable approach based on predicted spectral information. Most importantly, our contribution removes what is arguably the biggest bottleneck in the field: the current need for Data Dependent Acquisition (DDA) prior to DIA analysis. Fractionation, stochastic data acquisition, processing and identification all introduce bias in the library. By generating libraries through data independent, i.e. deterministic acquisition, stochastic sampling in the DIA workflow is now fully omitted. This is a crucial step towards increased standardization. Additionally, our results demonstrate that a proteome-wide predicted spectral library can surrogate an exhaustive DDA Pan-Human library that was built based on 331 prior DDA runs.

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DIAproteomics: A multi-functional data analysis pipeline for data-independent-acquisition proteomics and peptidomics

10.1101/2020.12.08.415844 ◽

2020 ◽

Author(s):

Leon Bichmann ◽

Shubham Gupta ◽

George Rosenberger ◽

Leon Kuchenbecker ◽

Timo Sachsenberg ◽

...

Keyword(s):

Data Analysis ◽

Large Scale ◽

Dynamic Range ◽

Expert Knowledge ◽

Data Sets ◽

Data Independent Acquisition ◽

Large Scale Data ◽

False Discovery ◽

Spectral Libraries ◽

Scale Data

ABSTRACTData-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. Main advantages include greater reproducibility, sensitivity and dynamic range compared to data-dependent acquisition (DDA). However, data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics a multi-functional, automated high-throughput pipeline implemented in Nextflow that allows to easily process proteomics and peptidomics DIA datasets on diverse compute infrastructures. Central components are well-established tools such as the OpenSwathWorkflow for DIA spectral library search and PyProphet for false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and carry out retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from statistical post-processing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is open-source software and available under a permissive license to the scientific community at https://www.openms.de/diaproteomics/.

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Microchemical imaging in biomedical research

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100130225 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1118-1119

Author(s):

P. Ingram

Keyword(s):

Data Analysis ◽

Electron Probe ◽

The Other ◽

X Ray ◽

Cell Element ◽

Physiological Information ◽

Functional States ◽

Elemental Maps ◽

Electron Energy Loss ◽

Secondary Ion

It is well established that unique physiological information can be obtained by rapidly freezing cells in various functional states and analyzing the cell element content and distribution by electron probe x-ray microanalysis. (The other techniques of microanalysis that are amenable to imaging, such as electron energy loss spectroscopy, secondary ion mass spectroscopy, particle induced x-ray emission etc., are not addressed in this tutorial.) However, the usual processes of data acquisition are labor intensive and lengthy, requiring that x-ray counts be collected from individually selected regions of each cell in question and that data analysis be performed subsequent to data collection. A judicious combination of quantitative elemental maps and static raster probes adds not only an additional overall perception of what is occurring during a particular biological manipulation or event, but substantially increases data productivity. Recent advances in microcomputer instrumentation and software have made readily feasible the acquisition and processing of digital quantitative x-ray maps of one to several cells.

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Perceptions of a Collaborative Professional Learning Program: Seeing the “Bigger Picture”

Perspectives of the ASHA Special Interest Groups ◽

10.1044/2019_persp-19-00041 ◽

2020 ◽

Vol 5 (1) ◽

pp. 290-303

Author(s):

P. Charlie Buckley ◽

Kimberly A. Murza ◽

Tami Cassel

Keyword(s):

Data Analysis ◽

Professional Learning ◽

Social Communication ◽

Special Educators ◽

Service Providers ◽

Integrative Approach ◽

Theory Approach ◽

Learning Program ◽

Speech Language Pathologists ◽

Related Service

Purpose The purpose of this study was to explore the perceptions of special education practitioners (i.e., speech-language pathologists, special educators, para-educators, and other related service providers) on their role as communication partners after participation in the Social Communication and Engagement Triad (Buckley et al., 2015 ) yearlong professional learning program. Method A qualitative approach using interviews and purposeful sampling was used. A total of 22 participants who completed participation in either Year 1 or Year 2 of the program were interviewed. Participants were speech-language pathologists, special educators, para-educators, and other related service providers. Using a grounded theory approach (Glaser & Strauss, 1967 ) to data analysis, open, axial, and selective coding procedures were followed. Results Three themes emerged from the data analysis and included engagement as the goal, role as a communication partner, and importance of collaboration. Conclusions Findings supported the notion that educators see the value of an integrative approach to service delivery, supporting students' social communication and engagement across the school day but also recognizing the challenges they face in making this a reality.

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Communicative Performance of Adolescents with Severe Speech Impairment

Journal of Speech and Hearing Disorders ◽

10.1044/jshd.5403.403 ◽

1989 ◽

Vol 54 (3) ◽

pp. 403-421 ◽

Cited By ~ 7

Author(s):

Beth M. Dalton ◽

Jan L. Bedrosian

Keyword(s):

Data Analysis ◽

Peer Interactions ◽

Consistent Pattern ◽

Clinical Implications ◽

Speech Impairment ◽

Communication Mode ◽

Mode Function ◽

Communicative Performance ◽

Therapy Room ◽

Communication Board

The communicative performance of 4 preoperational-level adolescents, using limited speech, gestures, and communication board techniques, was examined in a two-part investigation. In Part 1, each subject participated in an academic interaction with a teacher in a therapy room. Data were transcribed and coded for communication mode, function, and role. Two subjects were found to predominantly use the speech mode, while the remaining 2 predominantly used board and one other mode. The majority of productions consisted of responses to requests, and the initiator role was infrequently occupied. These findings were similar to those reported in previous investigations conducted in classroom settings. In Part 2, another examination of the communicative performance of these subjects was conducted in spontaneous interactions involving speaking and nonspeaking peers in a therapy room. Using the same data analysis procedures, gesture and speech modes predominated for 3 of the subjects in the nonspeaking peer interactions. The remaining subject exhibited minimal interaction. No consistent pattern of mode usage was exhibited across the speaking peer interactions. In the nonspeaking peer interactions, requests predominated. In contrast, a variety of communication functions was exhibited in the speaking peer interactions. Both the initiator and the maintainer roles were occupied in the majority of interactions. Pertinent variables and clinical implications are discussed.

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