refine.bio
  • Search
      • Normalized Compendia
      • RNA-seq Sample Compendia
  • Docs
  • About
  • My Dataset
github link
Showing
of 252 results
Sort by

Filters

Technology

Platform

accession-icon SRP067124
Comparative analysis of single-cell RNA sequencing methods
  • organism-icon Mus musculus
  • sample-icon 743 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500, Illumina HiSeq 2000, Illumina HiSeq 1500

Description

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to address biological and medical questions. However, systematic comparisons of the performance of diverse scRNA-seq protocols are lacking. We generated data from 583 mouse embryonic stem cells to evaluate six prominent scRNA-seq methods: CEL-seq2, Drop-seq, MARS-seq, SCRB-seq, Smart-seq and Smart-seq2. While Smart-seq2 detected the most genes per cell and across cells, CEL-seq2, Drop-seq, MARS-seq and SCRB-seq quantified mRNA levels with less amplification noise due to the use of unique molecular identifiers (UMIs). Power simulations at different sequencing depths showed that Drop-seq is more cost-efficient for transcriptome quantification of large numbers of cells, while MARS-seq, SCRB-seq and Smart-seq2 are more efficient when analyzing fewer cells. Our quantitative comparison offers the basis for an informed choice among six prominent scRNA-seq methods and provides a framework for benchmarking further improvements of scRNA-seq protocols. Overall design: J1 mESC in two replicates per library preparation method.

Publication Title

A systematic evaluation of single cell RNA-seq analysis pipelines.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon SRP108854
zUMIs: a fast and flexible pipeline for RNA sequencing data with UMIs
  • organism-icon Homo sapiens
  • sample-icon 81 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

Background Single-cell RNA-sequencing (scRNA-seq) experiments typically analyze hundreds or thousands of cells after amplification of the cDNA. The high throughput is made possible by the early introduction of sample-specific bar codes (BCs), and the amplification bias is alleviated by unique molecular identifiers (UMIs). Thus, the ideal analysis pipeline for scRNA-seq data needs to efficiently tabulate reads according to both BC and UMI. Findings zUMIs is a pipeline that can handle both known and random BCs and also efficiently collapse UMIs, either just for exon mapping reads or for both exon and intron mapping reads. If BC annotation is missing, zUMIs can accurately detect intact cells from the distribution of sequencing reads. Another unique feature of zUMIs is the adaptive downsampling function that facilitates dealing with hugely varying library sizes but also allows the user to evaluate whether the library has been sequenced to saturation. To illustrate the utility of zUMIs, we analyzed a single-nucleus RNA-seq dataset and show that more than 35% of all reads map to introns. Also, we show that these intronic reads are informative about expression levels, significantly increasing the number of detected genes and improving the cluster resolution. Conclusions zUMIs flexibility makes if possible to accommodate data generated with any of the major scRNA-seq protocols that use BCs and UMIs and is the most feature-rich, fast, and user-friendly pipeline to process such scRNA-seq data. Overall design: HEK293T cells were sequenced using the mcSCRB-seq protocol (Bagnoli et al., 2017)

Publication Title

zUMIs - A fast and flexible pipeline to process RNA sequencing data with UMIs.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon SRP067154
Sequencing Universal Human Reference RNA by Smart-seq and early barcoding library preparation methods
  • organism-icon Homo sapiens
  • sample-icon 11 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq1500

Description

Many library preparation methods are available for gene expression quantification. Here, we sequenced and analysed Universal Human Reference RNA (UHRR) prepared using Smart-Seq2, TruSeq (public data) and a protocol using unique molecular identifiers (UMIs) that all include the ERCC spike-in mRNAs to investigate the effects of amplification bias on expression quantification. Overall design: UHRR 10 and 12 replicates for Smart-seq2 and UMI-seq library preparation methods, respectively.

Publication Title

The impact of amplification on differential expression analyses by RNA-seq.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE3963
Differential expression: associative and nonassociative learning
  • organism-icon Mus musculus
  • sample-icon 48 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

Hippocamus and amygdala expression was examined in nave, conditioned stimulus exposed, and fear conditioned mice 30 minutes after behavioral manipulation

Publication Title

Differential transcriptional response to nonassociative and associative components of classical fear conditioning in the amygdala and hippocampus.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon E-AFMX-1
Transcription profiling of human, chimp and mouse brain
  • organism-icon Macaca mulatta, Mus caroli, Mus musculus, Pan troglodytes, Pongo pygmaeus, Homo sapiens, Mus spretus
  • sample-icon 13 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2), Affymetrix Human Genome U95 Version 2 Array (hgu95av2)

Description

Microarray technologies allow the identification of large numbers of expression differences within and between species. Although environmental and physiological stimuli are clearly responsible for changes in the expression levels of many genes, it is not known whether the majority of changes of gene expression fixed during evolution between species and between various tissues within a species are caused by Darwinian selection or by stochastic processes. We find the following: (1) expression differences between species accumulate approximately linearly with time; (2) gene expression variation among individuals within a species correlates positively with expression divergence between species; (3) rates of expression divergence between species do not differ significantly between intact genes and expressed pseudogenes; (4) expression differences between brain regions within a species have accumulated approximately linearly with time since these regions emerged during evolution. These results suggest that the majority of expression differences observed between species are selectively neutral or nearly neutral and likely to be of little or no functional significance. Therefore, the identification of gene expression differences between species fixed by selection should be based on null hypotheses assuming functional neutrality. Furthermore, it may be possible to apply a molecular clock based on expression differences to infer the evolutionary history of tissues.

Publication Title

A neutral model of transcriptome evolution.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon SRP044274
Dual regulation of Fbw7 function and oncogenic transformation by Usp28
  • organism-icon Mus musculus
  • sample-icon 17 Downloadable Samples
  • Technology Badge IconIllumina Genome Analyzer IIx

Description

Fbw7, the substrate recognition subunit of SCF(Fbw7) ubiquitin ligase, mediates turnover of multiple proto-oncoproteins and promotes its own degradation. Fbw7-mediated substrate degradation is antagonized by the Usp28 deubiquitinase. We now show, using knockout mice, that Usp28 preferentially deubiquitinates and stabilizes Fbw7. Monoallelic deletion of Usp28 maintains stable Fbw7 but destabilizes Fbw7 substrates. In contrast, complete knockout of Usp28 promotes Pin1-dependent autocatalytic turnover of Fbw7, accumulation of Fbw7 substrates and oncogenic transformation. Overexpression of Usp28 stabilizes both Fbw7 and its substrates and similarly enhances transformation. We propose that dual regulation of Fbw7 activity by Usp28 maintains physiological levels of Fbw7 substrates, and that both loss and overexpression of Usp28 in human cancer promote Fbw7 substrate accumulation. Overall design: RNAseq experiments of E13.5 murine embryonic fibroblasts (MEFs) derived from animals in which Usp28 was either deleted (-/-), wildtype (+/+) or heterozygous (+/-). In a first set of experiments immortalized MEFs of all three genotypes were analysed in biological triplicates. In a second set of experiments immortalized and Ras transformed MEFs of all three genotypes and MEFs which overexpress USP28 (+/+/+) where sequenced in duplicates.

Publication Title

Dual regulation of Fbw7 function and oncogenic transformation by Usp28.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP067175
Transposon mutagenesis reveals fludarabine-resistance mechanisms in chronic lymphocytic leukemia
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIon Torrent Proton

Description

Purpose:To identify resistance mechanisms for the chemotherapeutic drug fludarabine in chronic lymphocytic leukemia (CLL), as innate and acquired resistance to fludarabine-based chemotherapy represents a major challenge for long-term disease control. Methods: We employed piggyBac transposon-mediated mutagenesis, combined with next-generation sequencing, to identify genes that confer resistance to fludarabine in a human CLL cell line. Results: RNA-seq profiling of fludarabine-resistant cells suggested deregulated MAPK signaling as involved in mediating drug resistance in CLL. Overall design: To address if the fludarabine-resistant HG3 cells were transcriptionally different at a global level compared to their parental cells, we performed RNA-sequencing of three pairs of HG3 pools

Publication Title

Transposon Mutagenesis Reveals Fludarabine Resistance Mechanisms in Chronic Lymphocytic Leukemia.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon SRP018815
RNA helicase A is necessary for KIF1Bß tumor suppression in neuroblastoma
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

During development neuronal progenitors compete for growth factors such as nerve growth factor NGF and require the prolyl hydroxylase EglN3 and the kinesin KIF1Bß for developmental apoptosis. Inherited KIF1Bß loss-of-function mutations in neuroblastomas and pheochromocytomas implicate KIF1Bß as a 1p36.2 tumor suppressor, however the mechanism of tumor suppression is unknown. We found that KIF1Bß interacts with the RNA helicase A (DHX9) resulting in DHX9 nuclear accumulation to regulate apoptosis. KIF1Bß-dependent DHX9 nuclear localization leads to transcription of the apoptotic target XIAP-associated factor 1. DHX9 is induced when NGF is limiting and required for apoptosis in cells deprived of NGF. Overall design: NB1 cells were transduced to incorporate shRNA against DHX9 or a scrambled control, and transfected with a KIF1Bß expression vector or control, then transfected cells were isolated and lysed after 48h.

Publication Title

RNA helicase A is a downstream mediator of KIF1Bβ tumor-suppressor function in neuroblastoma.

Sample Metadata Fields

Cell line, Subject

View Samples
accession-icon SRP092280
Transcriptome analysis of tumor-specific CD8 T cells in murine solid tumors
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

RNAseq analysis of CD8 T cells becoming dysfunctional in progressing tumors. The overall goal of this study was to elucidate the molecular program that mediates functional unresponsiveness in tumor-specific CD8 T cells. In comparison, we also investigated CD8 T cells differentiating to functional effector and memory T cells during an acute listeria infection. Overall design: T cells were sorted by flow cytometry and RNA-seq was performed.

Publication Title

Chromatin states define tumour-specific T cell dysfunction and reprogramming.

Sample Metadata Fields

Disease, Disease stage, Cell line, Subject

View Samples
accession-icon SRP094710
Cystathionine-ß-Synthase Promotes Colon Carcinogenesis
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 1500

Description

Purpose: The goal of this study is to investigate the role of CBS enzyme in colorectal carcinogenesis Methods: RNA-Seq transcriptome analysis of CBS-overexpression in NCM356 cels compared to control vector cells Overall design: RNA-seq transcriptome profiling of NCM356-CBS overexpressing cells vs. vector cells

Publication Title

Upregulation of Cystathionine-β-Synthase in Colonic Epithelia Reprograms Metabolism and Promotes Carcinogenesis.

Sample Metadata Fields

Subject

View Samples
...

refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

Powered by Alex's Lemonade Stand Foundation

Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

BSD 3-Clause LicensePrivacyTerms of UseContact