Find research datasets worth reusing

single-cell RNAseq data (data set 12) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset12) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor10 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 16) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset16) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from CD4 T-cells in PACA samples downloaded from the GEO website (GSE156728).  see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 11) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset11) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor9 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 14) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset14) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor12 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 9) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset9) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor7 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 8) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset8) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor6 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 7) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset7) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor5 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 19) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset19) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from Liver cancer set 2 samples downloaded from the GEO website (GSE125449).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

Discretized bulk data by the discretization step of rFASTCORMICS used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

Bulk data RNAseq data were downloaded from GEO, GTEX, and other sources (see below) and discretized by the discretization step of rFASTCORMICS (Pacheco et al, 2019) used in the optimization step in scFASTCORMICS: CRC bulk RNAseq data were obtained from Lee et al(2020)  CRC control (NM) was downloaded from GSE81861  (GTEX, Healthy colon from) Pancreatic  Human islet bulk RNAseq data was downloaded from EBI Expression Atlas (Pancreatic islet cells) Immune cells in pancreatic carcinoma bulk data were obtained from GEO (GSE156278) liver and breast cancer bulk RNAseq data were obtained from the TCGA (GSE62944)   rFASTCORMICS and tutorial on rFASTCORMICS can be found: https://github.com/sysbiolux

single-cell RNAseq data (data set 5) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset5) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor3 downloaded from the GEO website (GSE114297).  see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 15) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset15) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from CD8 T-cells in PACA samples downloaded from the GEO website (GSE156728).  see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 4) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset4) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor2 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 3) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset3) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from normal Pancreas donor1 downloaded from the GEO website (GSE114297).  see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.  <pre>  </pre>

opencc-zeroApr 2023View details →

dryad36/100

RNAseq transcriptome of draining lymph node (LN) and tumor of MC38 murine tumors treated with cryoablation and chitosan/IL-12

Focal ablation technologies are routinely used in the clinical management of inoperable solid tumors but often result in incomplete ablations leading to high recurrence rates. Adjuvant therapies capable of safely eliminating residual tumor cells are therefore of great clinical interest. Interleukin 12 (IL-12) is a potent antitumor cytokine that can be localized intratumorally through coformulation with viscous biopolymers including chitosan (CS) solutions. The objective of this research was to determine if localized immunotherapy with CS/IL-12 could prevent tumor recurrence after cryoablation (CA). Tumor recurrence, overall survival, and protective immunity were assessed. Systemic immunity was evaluated in spontaneously metastatic and bilateral tumor models. Temporal bulk RNA sequencing was performed on tumor and draining lymph node samples. In multiple murine tumor models, the addition of CS/IL-12 to CA reduced recurrence rates by 30–55%. Altogether, this cryo-immunotherapy induced complete durable regression of large tumors in 80–100% of treated animals. Mice treated with CA plus adjuvant CS/IL-12 were partially or completely protected from tumor rechallenge. Systemically, CS/IL-12 prevented lung metastases when delivered as a neoadjuvant to CA. However, CA plus CS/IL-12 had minimal antitumor activity against established, untreated abscopal tumors. Adjuvant anti-PD-1 therapy delayed the growth of abscopal tumors. Transcriptome analyses revealed early immunological changes in the dLN, followed by a significant increase in gene expression associated with immune suppression and regulation. Cryo-immunotherapy with localized CS/IL-12 reduces recurrences and enhances the elimination of large primary tumors. This focal combination therapy also induces significant systemic antitumor immunity although further studies are necessary.

HAPSTR1 localizes HUWE1 to the nucleus to limit stress signaling pathways_CAL27_RNAseq_siHUWE1

RNA-seq data from CAL27 cells 3 days after transfection with one of three siRNAs (1, 155 or 969) targeting human HUWE1. si155 corresponds to sequence #2, and si969 corresponds to sequence #3 in Monda et al. Cell Reports. 2023. Each transfection was performed in triplicate and analyzed with paired-end reads. See DOI:10.5281/zenodo.7839090 for the CAL27 siControl dataset. See DOI:10.5281/zenodo.7839102 for the CAL27 siHAPSTR1 dataset.

HAPSTR1 localizes HUWE1 to the nucleus to limit stress signaling pathways_CAL27_RNAseq_Control

RNA-seq data from CAL27 cells 3 days after transfection with one of three control non-targeting siRNAs. The transfection was performed in triplicate and analyzed with paired-end reads. See DOI: 10.5281/zenodo.7839102 for the CAL27 siHAPSTR1 dataset. See DOI: 10.5281/zenodo.7839096 for the CAL27 siHUWE1 dataset.

HAPSTR1 localizes HUWE1 to the nucleus to limit stress signaling pathways_CAL27_RNAseq_siHAPSTR1

RNA-seq data from CAL27 cells transfected with one of three siRNAs targeting human HAPSTR1. Each transfection was performed in triplicate and analyzed with paired-end reads. See DOI:10.5281/zenodo.7839090 for the CAL27 siControl dataset. See DOI: 10.5281/zenodo.7839096 for the CAL27 siHUWE1 dataset.

Training Data for "Metatranscriptomics analysis using microbiome RNASeq data"

Microbiomes play a critical role in host health, disease, and the environment.. Functional microbiome analysis which estimates the functional groups expressed by microbial community enables researchers to look beyond taxonomic composition and correlation with the condition under study. Using microbial community RNA-Seq data and subsequent metatranscriptomics workflows to elucidate the functional complement of the microbiome is gaining interest in the field. This tutorial from Galaxy training network will introduce researchers to the basic concepts of metatranscriptomics data analysis. It takes in paired-end datasets of raw shotgun sequences (in FastQ format) as an input and: <ol> <li>preprocess</li> <li>extract and analyze the community structure (taxonomic information)</li> <li>extract and analyze the community functions (functional information)</li> <li>combine taxonomic and functional information to offer insights into taxonomic contribution to a function or functions expressed by a particular taxonomy.</li> </ol> The dataset used in the tutorial comes from a time-serie analysis of a microbial community inside a bioreactor (Kunath et al, ISME, 2018). Only the data for one time point (1st) and a biological replicate (A) is analyzed here, after having been trimmed out the original file for the purpose of saving time and resources.

RNAseq of E. coli

RNAseq subset.

RNAseq analysis of Elafibranor and S217879 effects on human PCLS with MAFLD

Oxidative stress triggers nonalcoohlic steatohepatitis (NASH) and liver fibrosis. Nuclear-erythroid-2-Related Factor 2 (NRF2) is the master regulation of the anti-oxidant response. In this study, we tested the therapeutic potential of a new NRF2 activator (S217879) in Precision Cut Liver Slices (PCLS) derived from the liver of patients with metabolic associated fatty liver disease (MAFLD), and compared its effects to those of the well-known PPARa/d agonist, Elafibranor.