Bangce Ye Similar Datasets
Project description:MS1-based label-free quantification can compare precursor ion peaks across runs, allowing reproducible protein measurements. Among bioinformatic platforms enabling MS1-based quantification, MaxQuant (MQ) is one of the most used, while Proteome Discoverer (PD) has recently introduced the Minora tool. Here, we present a comparative evaluation of six MS1-based quantification methods available in MQ and PD. Intensity (MQ and PD) and area (PD only) of the precursor ion peaks were measured and then subjected or not to normalization. The six methods were applied to datasets simulating various differential proteomics scenarios and covering a wide range of protein abundance ratios and concentrations. PD outperformed MQ in terms of quantification yield, dynamic range, and reproducibility, although neither platform reached a fully satisfactory quality of measurements at low-concentration ranges. PD methods including normalization were the most accurate in estimating the abundance ratio between groups and the most sensitive when comparing groups with a narrow abundance ratio; on the contrary, MQ methods generally reached slightly higher specificity, accuracy, and precision values. Moreover, we found that applying an optimized log ratio-based threshold can maximize specificity, accuracy, and precision. Taken together, these results can help researchers choose the most appropriate MS1-based protein quantification strategy for their studies.
2021-05-31 | PXD022169 | Pride
Project description:Mycobacterium tuberculosis employs several strategies to combat and adapt to adverse conditions encountered inside the host. The non-replicative dormant state of the bacterium is linked to drug resistance and slower response to anti-tubercular therapy. It is known that alterations in lipid content allow dormant bacteria to acclimatize to cellular stress. Employing comparative lipidomic analysis we profiled the changes in lipid metabolism in M. tuberculosis using a modified Wayne's model of hypoxia-induced dormancy. Further we subjected the dormant bacteria to resuscitation, and analyzed their lipidomes until the lipid profile was similar to that of normoxially grown bacteria. An enhanced degradation of cell wall-associated and cytoplasmic lipids during dormancy, and their gradual restoration during reactivation, were clearly evident. This study throws light on distinct lipid metabolic patterns that M. tuberculosis undergoes to maintain its cellular energetics during dormancy and reactivation.
2018-10-22 | MTBLS304 | MetaboLights
Project description:Ribonucleotides incorporated in the genome are a source of endogenous DNA damage, and also serve as signals for repair. Although recent advances of ribonucleotide detection by sequencing, the balance between incorporation and repair of ribonucleotides has not been elucidated. Here, we describe a competitive sequencing method, Ribonucleotide Scanning Quantification sequencing (RiSQ-seq), which enables absolute quantification of misincorporated ribonucleotides throughout the genome by background normalization and standard adjustment within a single sample. RiSQ-seq analysis of cells harboring wild-type DNA polymerases revealed that ribonucleotides were incorporated non-uniformly in the genome with a 3’-shifted distribution and preference for GC sequences. Although ribonucleotide profiles in wild-type and repair-deficient mutant strains showed a similar pattern, direct comparison of distinct ribonucleotide levels in the strains by RiSQ-seq enabled evaluation of ribonucleotide excision repair activity at base resolution and revealed the strand bias of repair. The distinct preferences of ribonucleotide incorporation and repair create vulnerable regions associated with indel hotspots, suggesting that repair at sites of ribonucleotide misincorporation serves to maintain genome integrity and that RiSQ-seq can provide an estimate of indel risk.
2021-05-21 | GSE85130 | GEO
Project description:The DDA and DIA data for accuracy evaluation of absolute quantification algorithms.
2018-05-08 | PXD009719 |
Project description:Primary outcome(s): Comparative evaluation of the existing cfDNA quantification method based on clinical samples and this method
Study Design: Observational Study Model : Cohort, Time Perspective : Prospective, Enrollment : 20, Biospecimen Retention : Collect & Archive- Sample without DNA, Biospecimen Description : serum
| 2513434 | ecrin-mdr-crc
Project description:Label-free quantification based on data-independent acquisition (DIA) workflows is increasingly popular. Several software tools have been recently published or are commercially available. The present study focuses on the critical evaluation of three different software packages (Progenesis, synapter and ISOQuant) supporting ion-mobility enhanced DIA data. In order to benchmark the label-free quantification performance of the different tools, we generated two hybrid proteome samples of defined quantitative composition containing tryptically digested proteomes of three different species (mouse, yeast, E.coli). This model data set simulates complex biological samples containing large numbers of both unregulated (background) proteins as well as up- and down-regulated proteins with exactly known ratios between samples. We determined the number and dynamic range of quantifiable proteins and analyzed the influence of applied algorithms (retention time alignment, clustering, normalization, etc.) on the variation of reported protein quantities between technical replicates.
2017-04-06 | PXD001240 | Pride
Project description:Heart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of Dyspnea (HFN ROSE-BioLINCC)
| PRJNA1089319 | ENA
Project description:Heart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of Dyspnea (HFN ROSE-BioLINCC)
| PRJNA1089318 | ENA
Project description:In this study, we conducted a systematic investigation into a glycoproteomic workflow. Firstly, Label-free and TMT labeling strategies were utilized for intact N-glycopeptide quantification. A total of 2,924 unique intact N-glycopeptides can be quantified after being labeled using TMT approach. Compared to label-free method, TMT labeling for its high precision with the CV averaging 8% and multiplex analysis capabilities. Subsequently, we compared the capacity of ZIC-HILIC and MAX enrichment methods, revealing that the ZIC- HILIC method demonstrated superior performance in enriching intact N-glycopeptides, which can identify 3,004 GPSMs from a single injection of patient-derived xenograft (PDX) sample. Furthermore, we systematically evaluated different higher-energy collisional dissociation (HCD) collision energies, determining that the stepped collision energy HCD (sceHCD) settings of 25, 35, and 45 was the optimal for both the identification and quantification of intact N-glycopeptides.
2025-05-07 | PXD054874 | Pride
Project description:The performances of 10 different normalization methods on data of endogenous brain peptides produced with label-free nano-LC-MS were evaluated. Data sets originating from three different species (mouse, rat, and Japanese quail), each consisting of 35-45 individual LC-MS analyses, were used in the study. Each sample set contained both technical and biological replicates, and the LC-MS analyses were performed in a randomized block fashion. Peptides in all three data sets were found to display LC-MS analysis order-dependent bias. Global normalization methods will only to some extent correct this type of bias. Only the novel normalization procedure RegrRun (linear regression followed by analysis order normalization) corrected for this type of bias. The RegrRun procedure performed the best of the normalization methods tested and decreased the median S.D. by 43% on average compared with raw data. This method also produced the smallest fraction of peptides with interblock differences while producing the largest fraction of differentially expressed peaks between treatment groups in all three data sets. Linear regression normalization (Regr) performed second best and decreased median S.D. by 38% on average compared with raw data. All other examined methods reduced median S.D. by 20-30% on average compared with raw data.
| S-EPMC2758756 | biostudies-literature