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29
datasets available to search
ShareScore release 0.9.0
Dataset results
29 results for “perturb-seq”
VeloCycle-estimated cell cycle phases of single cells from a genome-scale perturb-seq performed in K562
<p>Continuous cell cycle phase position between 0 and 2π estimated by <em>VeloCycle </em>(Lederer et al., <em>Nature Methods</em> 2024) for single cells of the perturb-seq performed in the K562 CML cell line by Replogle et al., Cell 2022. </p> <p>Underlies the cell cycle imbalances inferred in Pulver & Forey et al., 2024.</p> <p>Method manuscript exerpt:</p> <p>"For analysis on the genome-wide perturb-seq dataset of K562 cells (Replogle <em>et al.</em>, 2022), a transfer learning approach was applied. Condition-independent estimation of the periodic Fourier series components would be especially challenging on Perturb-seq knockdown conditions containing either (1) very few cells or (2) cells belonging to just one phase of the cell cycle. To infer accurate cell cycle phases for these cells, we first performed manifold-learning for 5,000 training steps to estimate the gene harmonic coefficients (ν0, ν1sin, ν1cos) on a larger set of non-targeting control (NT) K562 cells (75,328 cells), which are more evenly distributed throughout the various phases of the cell cycle. Next, we ran manifold-learning again for 5,000 training steps, but on the entire perturb-seq dataset of 1,971,608 cells and 4,127 gene knockdown conditions (with at least 75 cells per condition). This time, we conditioned <em>VeloCycle</em> on the gene harmonic coefficients learned in the first step. This allowed cells belonging to each stratified gene knockdown condition to be assigned to a position on the cell cycle manifold, while restricting those assignments such that they were based on gene expression patterns earned on a larger and more informative dataset (allowing for batch effect expression differences)."</p>
Multiplexed single-cell characterization of alternative polyadenylation regulators (HEK293FT & K562 Perturb-seq data)
<p>This site provides access to datasets from the CPA-Perturb-seq <a href="https://www.biorxiv.org/content/10.1101/2023.02.09.527751v1">manuscript</a> Kowalski*, Wessels*, Linder* et al., including processed Perturb-seq datasets from HEK293FT and K562. We release these data as Seurat objects, where each object contains single-cell quantifications of gene expression (RNA assay), and in addition, quantifications of polyA site usage (polyA site assay). To explore these data, please install the <a href="https://github.com/satijalab/PASTA">PASTA</a> (PolyA Site analysis using relative Transcript Abundance) package, which provides infrastructure and analytical tools to explore alternative polyadenylation at single-cell resolution. For each dataset, we also include a fragment file which enables visualization of read coverage plots across groups of cells. </p> <p>The files include:</p> <p>1. CPA_K562.Rds : Seurat object containing the K562 CPA-Perturb-seq dataset </p> <p>2. CPA_K562_fragments.tsv.gz : Fragment file for the K562 dataset </p> <p>3. CPA_K562_fragments.tsv.gz.tbi : Fragment file index for the K562 dataset </p> <p> </p> <p>R code below:</p> <pre><code>library(PASTA) k562 <- readRDS("CPA_K562.Rds") # Add fragments for plotting Fragments(k562) <- CreateFragmentObject(path = "download/CPA_K562_blocks.tsv.gz", cells = Cells(k562)) # visualize polyA site usage PolyACoveragePlot(k562, region ="chr7-26212195-26213351")</code></pre>
Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq
GEO Series GSE213957. Mus musculus; Homo sapiens. 55 samples. Type: Expression profiling by high throughput sequencing.
Perturb-Seq using T2D islets
GEO Series GSE137766. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
Massively parallel phenotyping of coding variants in cancer with Perturb-seq
GEO Series GSE161824. Homo sapiens. 64 samples. Type: Expression profiling by high throughput sequencing.
CRISPR activation and interference screens decode stimulation responses in primary human T cells [CRISPRa Perturb-seq]
GEO Series GSE190604. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing; Other.
Genome-scale CRISPRi Perturb-seq on both unstimulated and stimulated Jurkat cells reveals regulators of human T-cell signaling
GEO Series GSE249595. Homo sapiens. 16 samples. Type: Other.
Comparison of dual sgRNA library versus Dolcetto by Perturb-seq
GEO Series GSE205310. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
Perturb-seq (CRISPR-based screens with single-cell RNA-sequencing readouts) screens Endoc-betaH1 cell line targeting 61 T2D coding variants genes and 40 RQC function genes.
GEO Series GSE273677. Homo sapiens. 9 samples. Type: Other.
Method of moments approach for generalized differential gene expression analysis (Perturb-seq)
GEO Series GSE274751. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes
GEO Series GSE157977. Mus musculus. 38 samples. Type: Expression profiling by high throughput sequencing; Other.
Compressed Perturb-seq: highly efficient screens for regulatory circuits using random composite perturbations
GEO Series GSE221321. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seq
GEO Series GSE303901. Homo sapiens. 29 samples. Type: Expression profiling by high throughput sequencing.
Perturb-seq: Dissecting molecular circuits with scalable single cell RNA profiling of pooled genetic screens
GEO Series GSE90063. Homo sapiens; Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
MethNet: a robust approach to identify regulatory hubs and their distal targets in cancer [Perturb-seq]
GEO Series GSE236304. Homo sapiens. 3 samples. Type: Other.
CRISPRai Perturb-seq [Series 1]
GEO Series GSE220974. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Massively parallel in vivo Perturb-seq reveals cell type-specific transcriptional networks in cortical development
GEO Series GSE249416. Mus musculus. 14 samples. Type: Expression profiling by high throughput sequencing.
Perturb-seq experiment on patient-derived cancer-associated fibroblast in vitro cell line models from pancreatic ductal adenocarcinoma
GEO Series GSE306853. Homo sapiens. 70 samples. Type: Expression profiling by high throughput sequencing.
Systematic functional interrogation of SARS-CoV-2 host factors using Perturb-seq
GEO Series GSE208240. Homo sapiens; Severe acute respiratory syndrome coronavirus 2; synthetic construct. 2 samples. Type: Other.
In vivo Perturb-Seq in the mouse brain
GEO Series GSE274058. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
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