MassIVE MSV000088373

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Proteomic-based identification of APCS as candidate protein for diagnosis of patients exhibiting Anti-tubercular drug induced liver injury

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Description

In the present study, the proteomics approach identified potential protein signatures with high discriminative ability in TB patients with and without drug-induced liver injury which might play a crucial role in developing Anti-tubercular drug-induced liver injury. [doi:10.25345/C5HV96] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: tuberculosis ; anti-tubercular drug-induced liver injury ; human serum ; label-free quantitative proteomics ; liquid chromatography tandem mass spectrometry

Contact

Principal Investigators:
(in alphabetical order) 		Sadhna Sharma, Postgraduate Institute of Medical Education and Research, Chandigarh (160012)., India
Submitting User: bhav1200

Publications

Bhavneet Kaur, Ravi Dixit, Shikha Bakshi, Monidipa Konar, Saroj K. Sinha, Ajay Kumar Duseja & Sadhna Sharma.
Proteomic-based identification of APCS as candidate protein for diagnosis of patients exhibiting anti-tubercular drug induced liver injury.
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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.