Dataset Information

InSPIRE Spectral Rescoring Tool

ABSTRACT: inSPIRE is an open-source tool for spectral rescoring of mass spectrometry search results. For this project, inSPIRE was applied to MaxQuant, PEAKS DB, and Mascot search results from a tryptic digestion of the K562 proteome. Here we provide the RAW files and search results using MaxQuant, PEAKS DB, and Mascot. We also reprocessed RAW data from the PXD031709 and PXD031812 repositories for which we provide the search result files. Additionally, we provide PEAKS search results from RAW files from the PXD015489 repository which was used as training data for a predictor used within inSPIRE. Michele Mishto, Head of the research group Molecular Immunology at King’s College London and the Francis Crick Institute, London (UK). Email: michele.mishto@kcl.ac.uk,

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Michele Mishto

LAB HEAD: Juliane Liepe

PROVIDER: PXD034056 | Pride | 2022-10-26

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	K562_RNA_based_db.fasta	Fasta
	PaesBorrows_DB_search_psm.csv	Csv
	PaesBorrows_RNA_based_db.fasta	Fasta
	SPL_modified_db.fasta	Fasta
	WSoh__281021_181221_Expl3_A1_tryp_pt5ug_R1.raw	Raw

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Project description:Chromatin accessibility captures the binding status of protein factors to chromosomes in vivo, and has been considered a highly informative proxy for functional protein-DNA interactions. Existing DNase I and Tn5 transposase based assays generally require tens of thousands to millions of fresh cells. Applying Tn5 tagmentation to single cells yields very sparse maps. Here we present a transposome hypersensitive sites sequencing assay (THS-seq) for highly sensitive characterizations of chromatin accessibility. Validation of THS-seq method, and comparison of DNase-seq, ATAC-seq and THS-seq methods for quantitation of chromatin accessibility. GSE47753, GSM1155957 GM12878_ATACseq_50k_Rep1, data downsampled to 8,351,125 reads for analysis: pub_SRR891268_ATAC-seq_50k_cells_Rep1_downsampled_dfilter_peaks.bed.gz GSE47753, GSM1155958 GM12878_ATACseq_50k_Rep2, data downsampled to 8,351,125 reads for analysis: pub_SRR891269_ATAC-seq_50k_cells_Rep2_downsampled_dfilter_peaks.bed.gz GSE47753, GSM1155959 GM12878_ATACseq_50k_Rep3, data downsampled to 8,351,125 reads for analysis: pub_SRR891270_ATAC-seq_50k_cells_Rep3_downsampled_dfilter_peaks.bed.gz GSE47753, GSM1155960 GM12878_ATACseq_50k_Rep4, data downsampled to 8,351,125 reads for analysis: pub_SRR891271_ATAC-seq_50k_cells_Rep4_downsampled_dfilter_peaks.bed.gz GSE47753, GSM1155961 GM12878_ATACseq_500_Rep1, data downsampled to 8,351,125 reads for analysis: pub_SRR891272_ATAC-seq_500_cells_Rep1_downsampled_dfilter_peaks.bed.gz GSE47753, GSM1155962 GM12878_ATACseq_500_Rep2, data downsampled to 8,351,125 reads for analysis: pub_SRR891273_ATAC-seq_500_cells_Rep2_downsampled_dfilter_peaks.bed.gz raw data files were merged, alignment with bowtie 1.3 using parameters, bowtie -n1 -k1 --best --chunkmbs 10240 --strata -l32 -m1 -p4 --nomaqround --sam, followed by clonal read removal for the final data file for further analysis. GSM816665, raw data obtained from UCSC genome browser, https://genome.ucsc.edu/cgi-bin/hgFileUi?db=hg19&g=wgEncodeOpenChromDnase: wgEncodeOpenChromDnaseGm12878RawData_merged_unique_dfilter_peaks.bed.gz raw data files were merged, alignment with bowtie 1.3 using parameters, bowtie -n1 -k1 --best --chunkmbs 10240 --strata -l32 -m1 -p4 --nomaqround --sam, followed by clonal read removal for the final data file for further analysis. GSM864360, raw data obtained from UCSC genome browser, https://genome.ucsc.edu/cgi-bin/hgFileUi?db=hg19&g=wgEncodeOpenChromFaire: wgEncodeOpenChromFaireGm12878RawData_merged_unique_dfilter_peaks.bed.gz raw data files were merged, alignment with bowtie 1.3 using parameters, bowtie -n1 -k1 --best --chunkmbs 10240 --strata -l32 -m1 -p4 --nomaqround --sam, followed by clonal read removal for the final data file for further analysis. GSM736496, GSM736620, raw data obtained from UCSC genome browser, https://genome.ucsc.edu/cgi-bin/hgFileUi?db=hg19&g=wgEncodeUwDnase: wgEncodeUwDnaseGm12878RawData_merged_unique_dfilter_peaks.bed.gz

Project description:In this project, we aim to pair-wise analyze the genomes, transcriptomes and proteomes of in-bred rats originating from two different genetic backgrounds. These two strains are Brown Norway (BN-Lx) and Spontaneously Hypertensive Rats (SHR). First, we re-sequenced the genomes for both BN and SHR rats, followed by RNA-seq and proteomics of their liver tissues. We then append novel predicted gene models, non-synonymous SNPs and INDELs (derived from genome re-sequencing), as well as transcript variants such as RNA-editing and alternative splicing (derived from RNA-seq) that can diversify existing protein sequences onto the ENSEMBL rat FASTA (Build 68) to build an enhanced database. For proteomics studies, equal amount of liver lysates were digested with trypsin, LysC, GluC, AspN and chymotrypsin and were individually fractionated with strong cationic exchange chromatography. Doubly- and triply-charged fractions were analyzed with an Triple-TOF 5600 with collision-activated dissociation (CAD); while electron-transfer dissociation (ETD) was applied for fractions containing triple charges and above with a LTQ-Orbitrap Velos. Data analysis: Peak List generation: For Wiff files generated from TripleTOF 5600, tandem MS spectra were de-isotoped, charge- deconvoluted and peak lists converted to Mascot generic format (MGF) files using AB Sciex Data Converter (version 1.1). For data generated from the LTQ-Orbitrap Velos, Raw files were converted to MGF files using Proteome Discoverer (version 1.3). The non-fragment filter was used to simplify ETD spectra and the Top N filter for the HCD spectra. Three MGF files were generated (one for HCD, one for ETD IT and one for ETD FT). The files with an orbitrap readout were deisotoped and charge de-convoluted. Database Searching: All MGF files were queried with Mascot search engine (version 2.3) via Proteome Discoverer version 1.3 (PD 1.3, Thermo Fisher) for submission. The spectra were searched against in-house database (NGS_COMBINED). One of the five different enzymes used (Trypsin/P, LysC/P, Chymotrypsin, GluC-DE and AspN_ambic) were selected for each file and up to 9 missed cleavages were allowed. Cysteine carbamidomethylation was set as fixed modification, and oxidation of methionine and acetylation of the N-term as variable modifications. Peptide tolerance was initially set to 50 ppm and the MS/MS tolerance was set to 0.1 Da (for TOF readout), 0.02 Da (orbitrap readout) and 0.5 Da (ion trap readout). All peptide-spectrum matches (PSMs) were evaluated with Percolator for validation. We classified each PSM based on their q value. For proteins identification, we used set a high stringency filter of q = 0 (0% FDR). For peaks lists that do not yield any peptide matches, we exported them with PD 1.3 for further analysis. De novo search with PEAKS: Unassigned peak lists that are exported were re-analyzed with another software suite i.e. PEAKS Studio (version 6.0). The identification workflows is as follows. Peak lists were first filtered with a quality value of 0.65 as suggested by the manufacturer followed by de novo spectra interpretation. In this step, both peptide tolerance and MS/MS tolerance were set according to MASCOT search. To broaden the search space for these unassigned spectra, we additionally set de-amidation of asparagine and glutamine, and pyro-glu from glutamic acid and glutamine as variable modifications, on top of the other modifications indicated above. Maximum allowed variable PTM per peptide was set to 3. Finally de novo interpreted PSMs were submitted to PEAKS DB database matching, this time allowing semi-enzymatic specificity and a maximum cleavages per peptide of 2. Database used was set to NGS_COMBINED. FDR was estimated using decoy-fusion. The genomics and transcriptomics data are already deposited in the respective EBI repositories. Some of these data are derived from an already published manuscript. For the genomics data (from: Genetic basis of transcriptome differences between the founder strains of the rat HXB/BXH recombinant inbred panel by Simonis et al PMID:22541052) DNA data in Sequence Read Archive (SRA): BN-Lx genome: ERP001355 http://www.ebi.ac.uk/ena/data/view/ERP001355, SHR genome: ERP001371, BN reference genome: ERP000510, http://www.ebi.ac.uk/ena/data/view/ERP000510. RNA data in ArrayExpress: BN-Lx and SHR fragment RNA-seq data: E-MTAB-1029 http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1029, BN-Lx and SHR paired-end RNA-seq data: to be submitted.

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InSPIRE Spectral Rescoring Tool

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