Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Optimising Spectronaut search parameters to improve data quality with minimal proteome coverage reductions in DIA analyses of heterogeneous samples

ABSTRACT: Data independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimised to minimise the occurrence of false positives across different samples. Using an immunological model system to demonstrate the impact of adjusting search settings we analysed mouse macrophages and compared their proteome to macrophages spiked with Candida albicans. This experimental system enabled the identification of ‘false positives’ since Candida albicans peptides and proteins should not be present in the mouse only samples. We show that adjusting the search parameters reduced ‘false positive’ identifications by up 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimised parameters incur a moderate cost, only reducing the overall number of ‘true positive’ identifications across each biological replicate by less than 6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any experiment analysing heterogenous populations of cell types or tissues.

INSTRUMENT(S):

ORGANISM(S): Candida Albicans (yeast) Mus Musculus (mouse)

SUBMITTER: Alejandro Brenes

LAB HEAD: Simon Arthur

PROVIDER: PXD045958 | Pride | 2023-10-11

REPOSITORIES: Pride

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	CB-1.raw	Raw
	CB-2.raw	Raw
	CB-3.raw	Raw
	CB-4.raw	Raw
	CB-5.raw	Raw

Items per page:

1 - 5 of 18

Similar Datasets

Staphylococcus carnosus strain:OTT-336

Project description:Strains responsible for false positives or false negative food testing results

| PRJNA271338 | ENA

Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets

Project description:MicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miR’s targets is a considerable bioinformatic challenge of great importance for inferring the miR’s function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methods—it identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs’ function in a specific context.

2012-09-19 | GSE33538 | GEO

Optimizing murine sample sizes for RNA-seq studies revealed from large-scale comparative analysis

Project description:In order to determine the N, the usual approach is to perform a power calculation, which involves understanding the variability between samples and the expected effect size. Here, we focused on bulk RNA-seq experiments, which have become ubiquitous in biology, but which have many unknown or difficult to estimate parameters, and so the required analyses to determine the minimum N is typically lacking. We therefore performed two N=30 profiling studies between wild-type mice and mice in which one copy of a gene had been deleted, to determine how many mice would be required to minimize false positives and to maximize true discoveries found in the N of 30 experiment

2025-02-11 | GSE272152 | GEO

Deep Learning Enhances Precision of Citrullination Identification in Human and Arabidopsis Tissue Proteomes

Project description:Citrullination is a key yet underexplored post-translational modification involved in various biological processes. Its identification via mass spectrometry faces challenges like limited enrichment tools and false positives due to mass overlap with deamidation (+0.9840 Da). To address this, we developed a data analysis pipeline integrating the deep learning model Prosit-Cit, trained on ~53,000 spectra from ~2,500 synthetic citrullinated peptides, which improves sensitivity and precision in identifying citrullination sites. This approach has identified up to 14 times more citrullinated sites in human tissue proteomes and revealed new insights, including the first large-scale citrullination mapping in Arabidopsis. This upload includes: 1) Raw files and search SEARCHs from the evaluation dataset, used to assess the precision of citrullination identifications. 2) Raw files, search SEARCHs, and rescoring outcomes from validation experiments conducted on Arabidopsis flowers. 4) Re-analyzed search and rescoring SEARCHs from human (PXD010154) and Arabidopsis (PXD013868) tissue proteomes.

2025-02-11 | PXD056560 | Pride

S. venezuelae HupS protein acetylated lysine mapping via bottom-up LC-MS

Project description:Nucleoid-associated proteins (NAPs) are critical during the process of chromatin compaction in Streptomyces soil bacteria. HupS is one of the two NAPs encoded in the Streptomyces genome. Its unique C-terminal domain, rich in lysine repeats (LR domain), is alike to the H2B histone found in eukaryotic cells or the HupB protein found in Mycobacterium. Project study aim was to identify post-translationally acetylated lysine residues of HupS via bottom-up LC-MS. Two approaches were uptaken. One was based on HupS enrichment from a strain expressing a recombinant HupS with a C-terminal FLAG tag (TM015) via an antiFLAG pull-down, and the other relied on a proteome-wide search of acetylated peptides in a WT strain lysate. Controls for spectral false-positives were also carried out in parallel, which were an antiFLAG pull-down with a WT strain, and a proteome-wide search of acetylated peptides in a HupS deletion mutant strain (ΔhupS) lysate. 5 lysine acetylation sites were confidently determined for the HupS protein within this study, them being Lys51, Lys85, Lys104, Lys119, and either Lys193 or Lys194.

2024-06-03 | PXD050776 | Pride

Project description:Metabarcoding of a mock community of soil invertebrates: DNA extraction, false-positives, and data filtration

| PRJNA1157715 | ENA

not collected

Project description:Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites

| PRJNA1006621 | ENA

Machine Learning-based Peptide ID Rescoring

Project description:Machine Learning-based Mascot Rescoring to Reduce False Positives in Tumor Immunopeptidomics using Mass Spectrometry

| PXD044852 | JPOST Repository

Tissue disaggregation and isolation of specific cell types from transgenic Xenopus appendages for transcriptional analysis by FACS

Project description:Xenopus embryos and tadpoles are versatile models for embryological, cell biological, and regenerative studies. Genomic and transcriptomic approaches have been increasingly employed in these frogs. Most of these genome-wide analyses have profiled tissues in bulk, but there are many scenarios where isolation of single cells may be advantageous, including isolation of a preferred cell type, or generation of a single-cell suspension for applications such as scRNA-Seq. Here we present a protocol for the disaggregation of complex tail and limb bud tissue, and use cell type-specific fluorescence in transgenic X. tropicalis appendages to isolate specific cell populations using fluorescence activated cell sorting (FACS). Our protocol addresses a specific challenge in Xenopus embryos and tadpoles: the storage of maternal yolk platelets in each cell, which can introduce light scatter and thereby false positives into FACS analysis. Here we gate against both non-transgenic and ubiquitously transgenic animals to reduce both false positives and false negatives. We use the Xtr.Tg(pax6:GFP;cryga:RFP;actc1:RFP)Papal transgenic line as a test case to demonstrate that nucleic acid preparations made from sorted cells are high quality and specific. We anticipate this method will be adaptable to study various cell types that have transgenic reporter lines to better profile cell types of interest.

2020-09-23 | GSE158331 | GEO

Transcriptome sequencing to systematically detect trans-splicing in human embryonic stem cells

Project description:Trans-splicing occurs post-transcriptionally and generates transcripts that are orderly inconsistent with their corresponding DNA templates. Until recently only exceedingly rare trans-splicing events have been experimentally characterized in the mammalian transcriptomes. Although hundreds to thousands of trans-spliced RNA candidates have been nominated by bioinformatics- or NGS (next-generation sequencing)-based approaches, these candidates unavoidably suffered from potential false positives arising from genetic rearrangement events or in vitro artifacts. Here we develop a pipeline (TSscan) based on NGS transcriptome data to identify trans-splicing in human embryonic stem cells (ESCs). TSscan integrates RNA sequencing data derived from different NGS platforms (i.e., Roche 454, SOLiD, and Illumina) and different human ESC lines (i.e., H1 and H9) as well as several in silico filters to minimize these two types of potential false positives. Our result shows that a tremendous amount of apparent experimental artifacts are indeed present in NGS data, which may be the most major false positives of trans-splicing detection. TSscan totally identified 10 trans-spliced RNA candidates in human ESCs, four of which are experimentally validated to be true. Further experiments reveal that these four events represent differential expression during the transition of pluripotent status to differentiate statuses. Especially, we observe that one event (the trans-spliced isoform of NCRMS), which is also a large intergenic non-coding RNA, tends to be specifically transcribed in ESCs and induced pluripotent stem cells and can conspicuously affect the pluripotency maintenance of ESCs. As far as we know, TSscan is the first pipeline for systematic identification of trans-splicing that utilizes NGS data in the human transcriptome, opening up an important class of post-transcriptional events for comprehensive characterization.

2014-02-03 | GSE30557 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data