Data from quantitative label free proteomics analysis of rat spleen

نویسندگان

  • Khadar Dudekula
  • Thierry Le Bihan
چکیده

The dataset presented in this work has been obtained using a label-free quantitative proteomic analysis of rat spleen. A robust method for extraction of proteins from rat spleen tissue and LC-MS-MS analysis was developed using a urea and SDS-based buffer. Different fractionation methods were compared. A total of 3484 different proteins were identified from the pool of all experiments run in this study (a total of 2460 proteins with at least two peptides). A total of 1822 proteins were identified from nine non-fractionated pulse gels, 2288 proteins and 2864 proteins were identified by SDS-PAGE fractionation into three and five fractions respectively. The proteomics data are deposited in ProteomeXchange Consortium via PRIDE PXD003520, Progenesis and Maxquant output are presented in the supported information. The generated list of proteins under different regimes of fractionation allow assessing the nature of the identified proteins; variability in the quantitative analysis associated with the different sampling strategy and allow defining a proper number of replicates for future quantitative analysis.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Quantitative proteomics of rat and human pancreatic beta cells

Data set description: This data set is composed by label-free alternate-scanning LC-MS/MS proteomics analysis human and Wistar rat pancreatic islet endocrine cells. The mass spectrometry data of the human and rat pancreatic beta cells and the resulting proteome search output from ProteinLynx GlobalSERVER (PLGS) have been deposited to the ProteomeXchange Consortium [1] via the PRIDE partner repo...

متن کامل

PSEA-Quant: A Protein Set Enrichment Analysis on Label-Free and Label-Based Protein Quantification Data

The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enri...

متن کامل

Quantitative profile of five murine core proteomes using label-free functional proteomics.

Analysis of primary animal and human tissues is key in biological and biomedical research. Comparative proteomics analysis of primary biological material would benefit from uncomplicated experimental work flows capable of evaluating an unlimited number of samples. In this report we describe the application of label-free proteomics to the quantitative analysis of five mouse core proteomes. We de...

متن کامل

Representation of selected-reaction monitoring data in the mzQuantML data standard.

The mzQuantML data standard was designed to capture the output of quantitative software in proteomics, to support submissions to public repositories, development of visualization software and pipeline/modular approaches. The standard is designed around a common core that can be extended to support particular types of technique through the release of semantic rules that are checked by validation...

متن کامل

Tools for label-free peptide quantification.

The increasing scale and complexity of quantitative proteomics studies complicate subsequent analysis of the acquired data. Untargeted label-free quantification, based either on feature intensities or on spectral counting, is a method that scales particularly well with respect to the number of samples. It is thus an excellent alternative to labeling techniques. In order to profit from this scal...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2016