Find research datasets worth reusing

Multimodal single cell analysis of the paediatric lower airway reveals novel immune cell phenotypes in early life health and disease

RDS files of SingleCellExperiment objects containing raw single cell RNA-seq count data required to replicate the analyses presented at: <a href="https://oshlacklab.com/paed-cf-cite-seq/">https://oshlacklab.com/paed-cf-cite-seq/</a> and described in the pre-print titled: "Multimodal single cell analysis of the paediatric lower airway reveals novel immune cell phenotypes in early life health and disease". Instructions for how to incorporate the raw data into the analysis can be found at: <a href="https://oshlacklab.com/paed-cf-cite-seq/gettingStarted.html">https://oshlacklab.com/paed-cf-cite-seq/gettingStarted.html</a> and the complete analysis code and additional data files can be cloned/downloaded from: <a href="https://github.com/Oshlack/paed-cf-cite-seq">https://github.com/Oshlack/paed-cf-cite-seq</a>.

opencc-by-4.0May 2021View details →

Deep cross-omics cycle attention model for joint analysis of single-cell multi-omics data

We proposed DCCA for accurately dissecting the cellular heterogeneity on joint-profiling multi-omics data from the same individual cell by transferring representation between each other.

Single-cell datasets for NK cell

The NK cell mass cytometry dataset total collects 20 patients with 29 features. The attribute is divided into stimulated and unstimulated data. By dealing with data pre-processing in NK cell dataset, the raw data in each feature for every patient were transformed using an arcsinh normalization, which is f(x) = arcsinh(x/5).

single cell dataset for covid

The dataset is covid with data preprocessing. The covid dataset contains 65 million cells from 49 patients, out of which there were six healthy subjects, 23 mild cases of COVID, and 20 severe conditions under ICU care. For data pre-processing in the covid dataset, we collected the data for each experimental condition and removed unnamed proteins (columns with blank titles). We selected the remaining protein features and the entire cell population in the dataset. However, some genes are expressed as negative values in raw data; hence, we set every negative number to 0. Finally, the ward cases and ICU cases total contain 43 patients with 23 features.

Single-cell datasets for preeclampsia

The dataset is preeclampsia with data preprocessing.

opencc-by-4.0Jul 2022View details →

SIRV: Spatial inference of RNA velocity at the single-cell resolution

Spatial transcriptomics and scRNA-seq datasets used for integration and prediction of un/spliced expression for spatially measured genes using SIRV, used to infer the RNA velocity in the spatial context

dryad36/100

Single-cell expression and TCR data from CD19-specific CAR T cells in a phase I/II clinical trial

By leveraging single-cell transcriptome and T cell receptor (TCR) sequencing, we aimed to track the transcriptional signatures of CAR T cell clonotypes throughout the course of treatment and furthermore identify molecular patterns leading to potent CAR T cell cytotoxicity. The data presented in this study encompass blood and bone marrow samples from patients ≤ 21 years of age with relapsed or refractory B-cell acute lymphoblastic leukemia (B-ALL) participating in the SJCAR19 phase I/II clinical trial (<a href="https://clinicaltrials.gov/ct2/show/NCT03573700">NCT03573700</a>). In brief, patients enrolled in the clinical trial received either 1 x 10^6 (dose level 1) or 3 x 10^6 (dose level 2) per kilogram of body weight following successful generation of autologous CAR T cell products and lymphodepleting chemotherapy. Peripheral blood was drawn from each participant every week until week 4 post-infusion, at week 6 or 8, and month 3 or 6 if feasible. At week 4 post-infusion, blood marrow was also collected from participants. Total T cells (CD3+) were sorted from each post-infusion sample, as well as the pre-infusion CAR T cell products, and processed through 10x Genomics' single-cell gene expression and V(D)J sequencing platform using the standard protocol. We identified a unique and unexpected transcriptional signature in a subset of pre-infusion CAR T cells that shared TCRs with post-infusion cytotoxic effector CAR T cells. Functional validation of cells with even a subset of these pre-effector markers demonstrated their immediate cytotoxic potential and resistance to exhaustion.

opencc-zeroJul 2022View details →

Script and single cell RNA sequencing datasets of Biomphalaria glabrata hemocyte

The results of the gene and cell barcode counts (feature-barcode matrices) are available in the file "filtered_feature_bc_matrix_Naive". These data have been processed by cellRanger v3.1.0 and can be used with the script "scRNAseq_Biomphalaria_naive" which gathers all the analyses done for publication.

Supplementary Data for "The shaky foundations of simulating single-cell RNA sequencing data"

Supplementary Data for "The shaky foundations of simulating single-cell RNA sequencing data" See description.txt, Supplementary Text, Methods and https://github.com/HelenaLC/simulation-comparison for further description of the files available here.

Sequence tracks of Ago2 Neural stem cells and differentiated neurons from single-cells- Related to Fig. 5

Single neural stem cells were isolated from the Hippocampus of newborn mice generated from a hybrid cross. Some of these cells were differentiated In vitro and either the NSC or differentiated neurons were lysed and underwent a reverse transcription. The newly formed cDNA was used as a template to amplify expressed Ago2 transcript which was then sent off for Sanger sequencing. A SNP located within the exon was used to determine whether the transcript from that cell was generated from the maternal or paternal allele.

Variable allelic expression of imprinted genes at the Peg13, Trappc9, Ago2 cluster in single neural cells

Fig 1 5' RACE - Sequence tracks and analysis of alternative Trappc9 transcriptional start sites Fig 2 and suppl fig 3- Brain and Kidney tissue or Neural stem cells isolated from the Hippocampus region of newborn mice generated from a C57BL/6 (female) and a Cast/EiJ (male) cross (and its reciprocal cross) was used to determine allelic bias expression. A SNP located within an exon of Peg13, Trappc9, Ago2, Chrac1 and Kcnk9 was identified and amplified via pyrosequencing PCR with the percentage of SNP identification used to determine allele expression percentages. Additionally, Pyrorun sequences of reverse transcribed RNA from Trappc9 expression in different tissues. A hybrid cross between C57BL/6 and JF1 mouse was used to generate hybrid pups that were used to determine allele specificity of Trappc9 expression in Kidney and brain tissues. Figs 3, 4 & 5- Single neural stem cells were isolated from the Hippocampus of newborn mice generated from a hybrid cross. Some of these cells were differentiated In vitro and either the NSC or differentiated neurons were lysed and underwent a reverse transcription. The newly formed cDNA was used as a template to amplify expressed Peg13, Trappc9 or Ago2 transcripts which was then sent for Sanger sequencing. A SNP located within the exon was used to determine whether the transcript from that cell was generated from the maternal or paternal allele. Fig 6- Brain-specific regulatory elements were cloned into a pGL [Luc] vector containing a Trappc9 promoter. These newly generated plasmids were then transfected into either primary neuron or fibroblast cultures alongside a Renilla vector for normalization using Lipofectamine as a transfection reagent. After 48 hours the cells were lysed and analyzed using a Glomax illuminator to determine their impact on Luciferase expression compared to that of the pGL vector containing just the Trappc9 promoter. Additionally, Plasmid vectors that were used for transfection of primary neurons to determine the impact of brain-specific regulatory elements on transcription. Plasmids can be visualized using the free software pdraw.32 downloaded from http://acaclone.com/download/install.htm Suppl fig 2- Single Neural stem cells and in vitro differentiated neurons isolated from Mouse Hippocampus tissue underwent reverse transcription and a qPCR reaction intended to amplify cDNA of genes associated with specific neural cell types as a method of detecting cell fate and whether this had an impact on allele-specific expression and differential methylation. Suppl fig 4 & 5- DNA isolated from Neural stem cells was bisulfite converted for downstream identification of methyl group presence. CpG islands located at or near the promoters of the Peg13, Trappc9, Ago2, Chrac1 and Kcnk9 genes were amplified and cloned into a TOPO vector. The cloned segments were Sanger sequenced and compared to the original non-bisulfite converted sequence using the Quantification for methylation analysis (QUMA) tool to determine which CG dinucleotides were methylated and which weren't. Pyroruns determining methylation frequency at the CpG islands of these genes can be found in a separate upload on Zenodo.

opencc-zeroSep 2022View details →

dryad36/100

Integrated plasma proteomic and single-cell immune signaling network signatures demarcate mild, moderate, and severe COVID-19

The biological determinants underlying the range of COVID-19 clinical manifestations are not fully understood. Here, over 1400 plasma proteins and 2600 single-cell immune features comprising cell phenotype, endogenous signaling activity, and signaling responses to inflammatory ligands are cross-sectionally assessed in peripheral blood from 97 patients with mild, moderate, and severe COVID-19 and 40 uninfected patients. Using an integrated computational approach to analyze the combined plasma and single-cell proteomic data, we identify and independently validate a multivariate model classifying COVID-19 severity (multi-class AUCtraining = 0.799, p-value = 4.2e-6; multi-class AUCvalidation = 0.773, p-value = 7.7e-6). Examination of informative model features reveals novel biological signatures of COVID-19 severity, including the dysregulation of JAK/STAT, MAPK/mTOR, and NF-κB immune signaling networks in addition to recapitulating known hallmarks of COVID-19. These results provide a set of early determinants of COVID-19 severity that may point to therapeutic targets for prevention and/or treatment of COVID-19 progression.

opencc-by-4.0Sep 2022View details →

Long-term testing of alkaline electrolyser single cell using Raney Ni electrodes

Chronopotentiometry and polarization curves of alkaline electrolyser single cell using Raney Ni electrodes.

opencc-by-4.0Mar 2022View details →

Single cell whole genome sequencing from Funnell, O'Flanagan, Williams et al

This repository provides the processed data necessary to reproduce the results from: "Single cell genomic variation induced by mutational processes in cancer Funnell, O’Flanagan, Williams et al" This includes the following: <ul> <li>Single cell whole genome sequencing <ul> <li>Allele specific copy number profiles</li> <li>SNV counts per cell</li> <li>Structural variant counts per cell</li> <li>QC metrics</li> <li>clone assignments</li> <li>phylogenetic trees computed with sitka</li> <li>benchmarking results vs other methods</li> </ul> </li> <li>bulk whole genome sequencing <ul> <li>copy number profiles</li> <li>SNVs</li> </ul> </li> <li>10X single cell RNA sequencing <ul> <li>count matrices</li> <li>seurat Rdata objects</li> </ul> </li> <li>analysis tables <ul> <li>downstream processed results used to generate figures</li> </ul> </li> <li>oxford nanopore <ul> <li>phasing results</li> </ul> </li> </ul>   For further information please feel free to get in touch with Marc Williams (william1 [at] mskcc.org)

Single-cell transcriptome analysis of the in vivo response to viral infection in the cave nectar bat Eonycteris spelaea

Bats are reservoir hosts of many zoonotic viruses with pandemic potential in humans. Here, we utilized single-cell transcriptome sequencing (scRNA-seq) to provide detailed comparative analyses of the immune repertoire and the transcriptional responses in the bat lungs upon in vivo infection with a double-stranded RNA virus, Pteropine orthoreovirus PRV3M. Neutrophils were observed to have basally high IDO1 expression, uniquely amongst mammals currently profiled by scRNA-seq. NK/T cells were the most abundant immune cell type in lung tissue, and included three distinct CD8 + effector T cell populations delineated by the differential expression of KLRB1, GFRA2 and DPP4. We identified NK/T clusters which up-regulated genes involved in T-cell activation and effector function early after viral infection. Alveolar macrophages and classical monocytes were key drivers of antiviral interferon signaling. Infection also resulted in the expansion of a CSF1R + population expressing collagen-like genes, which became the predominant myeloid cell type after infection. This work uncovers novel features relevant to viral disease tolerance in bats, lays a foundation for future in vivo and in vitro experimental investigations, and serves as a key resource for comparative immunology studies across bats and other mammals.   This upload is the transcriptome fasta file used for alignment for the dataset.

opencc-by-4.0Sep 2022View details →

Exploring cell diversity and fidelity in crustacean limb regeneration using single-nucleus RNA sequencing

R objects containing datasets generated by snRNA-seq on Parhyale hawaiensis limbs. These datasets have been generated during my Phd thesis.

opencc-by-4.0Oct 2022View details →

[3/3] Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation

Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation

opencc-by-4.0Oct 2022View details →

[2/3] Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation

Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation

opencc-by-4.0Oct 2022View details →

[1/3] Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation

Patch clamp of a Purkinje cell in a simulated cerebellar cortex model during single impulse stimulation