hybrid · semantic + lexical · 21 datasets ranked · 1.00s
Toro, Nicolas · Molina-Sánchez, Maria Dolores
1 files · 1.9 MB · zip
This dataset contains the sequencing reads and mapping-derived coverage files corresponding to the UG5 genomic island of Sinorhizobium meliloti RMO17. Paired-end reads mapped to the UG5 region were extracted and processed using Bowtie2, Samtools, Bedtools and deepTools. The dataset includes raw FASTQ.gz files (R1, R2 and unpaired), the reference sequence of the UG5 genomic island (FASTA), genomic annotations (BED), genome size file, and all mapping-derived products (sorted BAM/BAl, bedGraph, and bigWig files with raw and CPM-normalized coverage). The dataset is organised in a structured directory (raw_reads, reference, mapping_products, metadata) to facilitate reuse and reproducibility. This resource supports the analyses reported in the associated manuscript.
Kim, Kwanho · Lin, Zechuan · Simmons, Sean · et al.
1 files · 37 KB · pdf
This dataset contains CCS corrected HiFi long-read DNA sequencing (lrDNAseq) in FASTQ format for 100 PMDBS samples from Parkinson's patients and healthy controls. It's part of the PD5D atlas, where the same subjects were also profiled with other omics assays including genotyping, single-cell ATACseq, and spatial transcriptomics.
Kim, Kwanho · Lin, Zechuan · Simmons, Sean · et al.
1 files · 37 KB · pdf
This dataset contains raw FASTQ files from the midbrain single-nucleus RNA sequencing (snRNAseq) dataset with hybrid selection for the matching PMDBS samples from the PD5D chort. The same subjects were also profiled with other omics assays including genomic DNAseq, genotyping, single-cell ATACseq, and spatial transcriptomics.
Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.
1 files · 37 KB · pdf
This dataset consists of raw sequencing snRNA-seq data (10x Genomics Chromium Next GEM Single Cell 3ʹ). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.
Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.
1 files · 36 KB · pdf
This dataset consists of raw sequencing snRNA-seq data using ParseBio Evercode Whole Transcriptome. The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a specific ParseBio barcode. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.
Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.
1 files · 36 KB · pdf
This dataset consists of raw sequencing snATAC-seq data (10x Genomics Chromium Next GEM Single Cell ATAC v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors. (edited)
Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.
1 files · 36 KB · pdf
This dataset consists of raw sequencing snATAC-seq data (HyDrop v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.
Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.
1 files · 36 KB · pdf
This dataset consists of raw sequencing ATAC-seq data (Scale-ATAC pre-indexing followed by 10x Genomics snATAC v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.
Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.
1 files · 36 KB · pdf
This dataset consists of raw sequencing ATAC-seq data (Scale-ATAC + HyDrop v2). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocols followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108 ) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors.
Pančíková, Alexandra · Theunis, Koen · Hulselmans, Gert · et al.
1 files · 37 KB · pdf
This dataset consists of raw sequencing snRNA-seq data and snATAC-seq data (10x Genomics Chromium Next GEM Multiome ATAC/GEX). The data is part of an overall set of samples derived from postmortem midbrain (n=140), cingulate cortex (n=190) and motor cortex (n=4) of healthy donors (n=114), patients with Parkinson's disease (n=75) or patients with other neurological disorder (n=1). The protocol followed to isolate nuclei from postmortem brain samples and to prepare sequencing libraries can be found below. To increase throughput and to decrease batch effects, several donors have been pooled together into a single sequencing library. To computationally demultiplex the nuclei to their corresponding donors, cellsnp-lite (version commit: aad18644adcde853c313362a856a24245c9b91f7) followed by vireo (https://github.com/single-cell-genetics/vireo/pull/108 ) has been used. The population VCF with the donor genotypes derived from whole genome sequencing data has been used to assign nuclei back to their donors. (edited)
MacDonald, Adam · Stratton, Jo Anne
1 files · 35 KB · pdf
We performed 10X Genomics single-cell RNAsequencing of human prepheral blood mononuclear cells from healthy control, PD and RBD patients. This dataset contains raw FASTQ files. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the human GRCh38 reference genome using STAR algorithm 2.7.3a.
Stratton, Jo Anne · Mukherjee, Sriparna · Trudeau, Louis-Eric
1 files · 5.0 KB · pdf
We performed bulk RNAsequencing of substantia nigra from wild type and PINK1 KO mice 26-days post C.rodentium infection. This dataset contains raw fastq files from striatal cells, sorted into 4 groups namely wild type and PINK1 KO uninfected and infected mice. Sequencing was performed using NextSeq500. FASTQs generated from sequencing output were aligned to the mm10 reference genome using STAR aligner.
Stratton, Jo Anne · Mukherjee, Sriparna · Trudeau, Louis-Eric
1 files · 6.1 KB · pdf
We performed bulk RNAsequencing of striatum from wild type and PINK1 KO mice 26-days post C.rodentium infection. This dataset contains raw fastq files from striatal cells, sorted into 4 groups namely wild type and PINK1 KO uninfected and infected mice. Sequencing was performed using NextSeq500. FASTQs generated from sequencing output were aligned to the mm10 reference genome using STAR aligner.
Recinto, Sherilyn · Stratton, Jo Anne
1 files · 6.1 KB · pdf
We performed 10X Genomics single-cell RNAsequencing of human iSPC-derived monocytes and macrophages in vitro. Cells were treated with 500 ng/mL lipopolysaccharide (LPS) and 50 ng/mL interleukin-1 beta (IL1b) for 24 hours. This dataset contains raw FASTQ files from myeloid cells, sorted into 4 groups namely monocytes (Mono) and Macrophages (Mac) non-stimulated (NS) and LPS+IL1b-stimulated cells. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the human GRCh38 reference genome using STAR algorithm 2.7.3a.
Recinto, Sherilyn · Stratton, Jo Anne · Pei, Jessica · et al.
2 files · 6.0 KB · pdf
We performed 10X Genomics single-cell RNAsequencing of colonic lamina propria cells from wild type and LRRK2 G2019S mice following 1-week post C. rodentium infection. The cells were pooled from 3 mice per group of both sexes at 8-12 weeks of age. This dataset contains raw FASTQ files from mouse colonic lamina propria, sorted into 4 groups namely wild type and LRRK2 G2019S uninfected and infected mice. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the mouse GRCm38 reference genome using STAR algorithm 2.7.3a.
Recinto, Sherilyn · Stratton, Jo Anne
1 files · 5.7 KB · pdf
We performed 10X Genomics single-cell RNA sequencing of colonic lamina propria cells from wild type and PINK1 KO mice following either 1-week or 2-weeks post C. rodentium infection. The cells were pooled from 3 mice per group of both sexes at 8-12 weeks of age. This dataset contains raw FASTQ files from mouse colonic lamina propria, sorted into 8 groups namely wild type and PINK1 KO uninfected and infected mice at 1- or 2-weeks post-infection. Sequencing was performed using NovaSeq 6000 S4 PE 100bp. Reads were processed using the 10X Genomics Cell Ranger Single Cell 2.0.0 pipeline. FASTQs generated from sequencing output were aligned to the mouse GRCm38 reference genome using STAR algorithm 2.7.3a.
Budzinski, Lisa · Beenken, Anne Elisabeth · Sempert, Toni · et al.
9 rows × 1 cols · 743 B · csv, docx, zip
1 categorical
We have investigated an IgG4-RD (IgG4-RD) cohort by our multi-parameter microbiota flow cytometry approach to characterise the microbiota on single-cell level for attributes of the disease. The microbiota is isolated from stool samples and stained according to the published protocol for (a) host immunoglobulins IgA1, IgA2, IgM, IgG and (b) agglutinin binding to mannose, galactose or N-Acetyl-glucosamine surface sugar moieties. For all samples we also determined the microbiome composition by 16S rRNA (V3-V4) sequencing on the illumina MiSeq platform. We provide the raw .fcs and FASTQ files of 40 IgG4-RD patients. For comparison we additionally analysed 36 healthy donors. All .fcs files were generated on BD Influx®. The metadata is collected in the provided meta.csv. The staining parameters are summarized in provided panel.csv.
Saha, Sudipto · Raghava, Gajendra
1 files · 186 KB · zip
VICMpred: SVM-Based Prediction of Functional Proteins of Gram-Negative Bacteria Using Amino Acid Patterns and Composition VICMpred is a computational web server developed for predicting the major functional classes of Gram-negative bacterial proteins from amino acid sequences. The tool classifies Gram-negative bacterial proteins into four broad functional categories: virulence factors, information molecules, cellular process proteins, and metabolism-related proteins. VICMpred uses support vector machine-based models trained on amino acid composition, dipeptide composition, and class-specific tetrapeptide patterns. Web Server: https://webs.iiitd.edu.in/raghava/vicmpred/ Citation Saha, S., and Raghava, G. P. S. VICMpred: An SVM-based method for the prediction of functional proteins of Gram-negative bacteria using amino acid patterns and composition. Genomics, Proteomics & Bioinformatics, 4(1), 42-47, 2006. https://doi.org/10.1016/S1672-0229(06)60015-6 About the Research Functional annotation of proteins is one of the major challenges in the post-genomic era. Due to the rapid growth of protein sequence databases, experimental functional characterization of every newly discovered protein is not practical. Traditional methods such as BLAST, FASTA, and PSI-BLAST depend on sequence similarity. However, proteins with similar functions may show poor sequence similarity, making direct function prediction difficult. VICMpred was developed as a direct function prediction method for Gram-negative bacterial proteins. Instead of only predicting subcellular localization, it predicts broad biological functions directly from protein sequence features. Data Compilation: The final dataset contained 670 non-redundant Gram-negative bacterial proteins. These included 255 cellular process proteins, 60 information molecules, 285 metabolism proteins, and 70 virulence factors. Methodology: VICMpred uses support vector machine-based models trained on amino acid composition, dipeptide composition, PSI-BLAST similarity search, class-specific tetrapeptide patterns, and hybrid combinations of these features.
Sikking, Maurits · Peisker, Fabian · Maatz, Henrike · et al.
1 files · 100 MB · zip
Project description: See related publication Code repository of the related publication: https://github.com/fpeisker303/IVIG_snRNA_project/ Methods use to generate the Single nuclear RNA sequencing data Endomyocardial biopsies (EMB) were taken from the right ventricular septum and collected via the internal jugular vein using a transcatheter bioptome (Cordis, Miami, FL., USA) at baseline before the IVIg treatment and at the standardized six-months follow-up timepoint of the original study (i.e., median 6.4 [5.9-7.3] months). EMB were evaluated regarding viral persistent and immunohistology markers of inflammation and fibrosis. Spare cardiac biopsies were stored at -80°C until preparation of snRNA sequencing. The isolation of cardiac nuclei and the 10x library preparation were performed at the Max Delbrück Center for Molecular Medicine following a published protocol (1) with adaptations to low-sized tissue pieces (2). In brief, 1-4-mg-sized flash-frozen cardiac biopsies were placed in a pre-cooled dish and an equally sized droplet of homogenization buffer (250 mM sucrose, 25 mM KCl, 5 mM MgCl 2 , 10 mM Tris-HCl, 1 μM DTT, 1× protease inhibitor, 0.4 U μl -1 RNaseIn, 0.2 U μl -1 SUPERaseIn and 0.1% Triton X-100 in nuclease-free water) was added. Buffer-encapsulated tissue pieces were sliced with a scalpel. The tissue pieces were then transferred to a 7-ml glass Dounce tissue grinder (Merck), and nuclei were isolated and stained with NucBlue Live ReadyProbes Reagent (Thermo Fisher Scientific). Hoechst + single nuclei were sorted via fluorescence-activated cell sorting (FACS) (BD Biosciences, FACSAria Fusion). Purity and integrity of nuclei were confirmed microscopically, and nuclei numbers were counted using a Countess II (Life Technologies) before processing with the Chromium Controller (10x Genomics) per the manufacturer's protocol. Single-nucleus 3' gene expression libraries were created using version 3.1 Chromium Single Cell Reagent Kits (10x Genomics) following the manufacturer's instructions. cDNA library quality control was performed using Bioanalyzer High Sensitivity DNA Analysis (Agilent Technologies) and a KAPA Library Quantification Kit. cDNA libraries were sequenced on an Illumina NovaSeq with a targeted read number of 30,000-50,000 reads per nucleus. Fastq files with sequencing results were processed using cellranger version 6.1.2 with the GRCh38-2020-A reference provided by 10x Genomics. References 1. Nadelmann ER, Gorham JM, Reichart D, Delaughter DM, Wakimoto H, Lindberg EL, et al. Isolation of Nuclei from Mammalian Cells and Tissues for Single-Nucleus Molecular Profiling. Curr Protoc. 2021;1(5):e132. 2. Maatz H, Lindberg EL, Adami E, López-Anguita N, Perdomo-Sabogal A, Cocera Ortega L, et al. The cellular and molecular cardiac tissue responses in human inflammatory cardiomyopathies after SARS-CoV-2 infection and COVID-19 vaccination. Nat Cardiovasc Res. 2025;4(3):330-45.
Li, Xuankun · Tu, Yuezheng · Plotkin, David · et al.
5 files · 100 MB · zip
Raw molecular data for 90 newly-sequenced specimens of Eupterotidae (and related families of Lepidoptera) used to generate a molecular phylogeny for the study "Phylogeny and biogeographic history of monkey moths (Lepidoptera: Eupterotidae)" (currently under peer review as of May 2026). File names contain the sequence ID and taxonomic information for each specimen. Data files are in fastq format and have been compressed; there are two files per specimen (labelled "R1" and "R2"). Data files have been organized into five .zip files, based on family-group taxonomy, as follows: Eupterotidae: Eupterotinae (25 specimens, 50 files) Eupterotidae: Ganisa Group (15 specimens, 30 files) Eupterotidae: Janinae (27 specimens, 54 files) Eupterotidae: Striphnopteryginae (15 specimens, 30 files) Other Lepidoptera families (outgroup taxa): Anthelidae, Bombycidae, Lasiocampidae, Saturniidae (8 specimens, 16 files)