Evidence map›Paper›PMID 36798308›Full record

ArticlebioRxiv : the preprint server for biology2023

IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets.

Sadjad Fakouri Baygi, Yashwant Kumar, Dinesh Kumar Barupal

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Sadjad Fakouri BaygiDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
Yashwant KumarNon-communicable Diseases Division, Translational Health Science and Technology Institute, Faridabad, Haryana, 121001, India.
Dinesh Kumar BarupalDepartment of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Funding

Conduits: Mount Sinai Health System Translational Science HubUL1TR004419 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$46.4M
MSHS Translational Science HubUL1TR001433 · NCATS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI WRIGHT, ROSALIND J · 2015 to 2019
$26.6M
Statistical Services and Methods Development ResourceU2CES026555 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI TEITELBAUM, SUSAN L · 2015 to 2025
$26.4M
Untargeted Analysis ResourceU2CES026561 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI WRIGHT, ROBERT O · 2015 to 2025
$24.5M
The Mount Sinai Transdisciplinary Center on Early Environmental ExposuresP30ES023515 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Maria Jose Rosa · 2014 to 2026
$21.3M
Untargeted Analysis ResourceU2CES030859 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI ARORA, MANISH · 2019 to 2025
$8.2M
Research Training Program in Pediatric ExposomicsT32HD049311 · NICHD · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KECIA Nicole CARROLL, Robert O Wright · 2007 to 2026
$7.4M
Perfluoroalkyl substances and incident type 2 diabetes in a US population: A metabolome-genome investigationR01ES033688 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Damaskini Valvi · 2022 to 2026
$3.2M
Mapping the blood cancer exposome for environmental risk profiles of mature B-cell neoplasmsR01ES032831 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Douglas Ian Walker · 2022 to 2026
$2.3M
Scholars in Environmental Pediatrics, Reproductive Health, and Life Course ScienceK12ES033594 · NIEHS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Rosalind J Wright · 2022 to 2026
$2.3M
NCATS NIH HHS UL1 TR001433NCATS NIH HHS UL1 TR004419NICHD NIH HHS T32 HD049311NIEHS NIH HHS K12 ES033594NIEHS NIH HHS P30 ES023515NIEHS NIH HHS R01 ES032831NIEHS NIH HHS R01 ES033688NIEHS NIH HHS U2C ES026555NIEHS NIH HHS U2C ES026561NIEHS NIH HHS U2C ES030859
6 · The paper itself

Abstract

Poor chemical annotation of high-resolution mass spectrometry data limit applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics - Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of LC/HRMS peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus MS/MS libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography instruments. The cross-applicability of these libraries across independent studies may provide access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R CRAN repository at https://cran.r-project.org/package=IDSL.CSA . Detailed documentation and tutorials are provided at https://github.com/idslme/IDSL.CSA . For Table of Contents Only:

Identifiers

PMID36798308
PMCPMC9934657

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.