11973 results for "cancer rna-seq"

in 21.52 milliseconds.

• RNA-Seq of chronic lymphocytic leukemia

  398 runs and 184 samples of CLL paired RNA-Seq. Sequences were prepared with the Illumina TruSeq RNA Kit. Paired sequencing was done on Hiseq2000 or Hiseq2500.

  Dataset EGAD00001009637

• NKI-AvL OpACIN RNA-seq of stage III melanoma patients

  The dataset “NKI-AvL OpACIN RNA-seq of stage III melanoma patients" includes 18 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 for 18 stage III melanoma patients.

  Dataset EGAD00001004216

• RNA-seq of Shprintzen-Goldberg syndrome dermal fibroblasts

  RNA-seq of dermal fibroblasts treated ± TGF-β from control and Shprintzen-Goldberg syndrome patients.

  Dataset EGAD00001006801

• JAGuaR outputs from RNA-seq

  JAGuaR outputs from RNA-seq of 35 pancreatic neuroendocrine neoplasms.

  Dataset EGAD00001006990

• McGill EMC Release 4 for assay "RNA-seq"

  McGill EMC Release 4 for assay "RNA-seq": Transcriptome profiling by high-throughput sequencing

  Dataset EGAD00001001290

• Paired-end RNA-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 46 paired-end RNA-seq samples from 3 patients.

  Dataset EGAD00001010290

• Raw sequencing data from chromosome conformation capture, RNA sequencing and chromatin assays in human primary monocytes

  This dataset contains raw sequencing data from eQTL Capture Hi-C, ATAC-seq and RNA-seq experiments in monocytes isolated from 34 healthy male donors, as well as from Hi-C, 4C-seq and CTCF ChIP-seq in subsets of individuals. The data are released as paired-end Illumina FASTQ files. Hi-C and Capture Hi-C used DpnII digestion and Tn5-based low-input library preparation. In Capture Hi-C, this was followed by targeted capture with custom-designed biotinylated RNA probes targeting ~1100 eQTL regions. ATAC-seq was performed on PFA-fixed cells using a digitonin-based protocol. 4C-seq and CTCF ChIP-seq were performed using standard protocols.

  Dataset EGAD50000001116

• Single-cell RNA-seq of immune cells from Melanoma tumors (Li et al, 2018)

  Single-cell RNA-seq profiling of immune cells sorted from human Melanoma tumors (and several matching PBMC samples). Contains de-multiplexed FASTQ files per plate (MARS-seq amplification batch, total 204 samples) and also de-multiplexed FASTQ files of single-cell TCRb-seq.

  Dataset EGAD00001004497

• WES and RNA-seq of triple-negative breast cancers from the MyBrCa cohort

  The dataset contains a genomics characterization of 35 triple-negative Asian breast tumours from the Malaysian Breast Cancer cohort. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a NovaSeq 6000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a NovaSeq 6000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001009311

• single cell RNA-seq data of circulating tumor cells from three small cell lung cancer patients

  This dataset contains raw 10x Genomics single-cell RNA sequencing data from a total of eight runs of circulating tumor cells from three small cell lung cancer patients. Each run represented by four FASTQ files (R1, R2, I1, I2) generated using the Illumina NextSeq 2000 platform. These files include read pairs as well as sample and cellular barcode indices. Circulating tumor cells were enriched from the blood of three SCLC patients using the CTC-iChip followed by magnetic depletion of RBCs. The enriched samples were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system.

  Dataset EGAD50000002035

• Transcriptome of Ewing sarcoma tumors - RNA-seq (ICGC)

  Transcriptome of Ewing sarcoma tumors (ICGC project). Fastq files of 57 RNA-seq are available (2x101bp).

  Dataset EGAD00001004493

• Single Cell RNA-Seq

  Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq. Nine techniques applied to samples from four PDX models: #105, #177, #233, #264

  Dataset EGAD50000000216

• Single nucleus RNA-seq of human epiglottis and subglottis

  This dataset contains single nucleus RNA-seq of human epiglottis and subglottis tissue performed using the 10X platform

  Dataset EGAD50000001279

• Bulk RNA-seq of Human Epiglottis and Subglottis

  This study contains bulk and single nucleus RNA-seq of human epiglottis and subglottis tissue.

  Dataset EGAD50000001278

• Glioblastoma stem cell lines RNA-seq

  RNA-seq data for three Glioblastoma stem cell (GSC) lines exposed to PRMT5 inhibitor and control samples.

  Dataset EGAD00001006095

• Un-mapped RNA-Seq data

  Un-mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma.

  Dataset EGAD00001001940

• Vcf RNA-Seq data

  Variants derived from mapped whole transcriptome RNA-Seq data from 476 human samples of early stage urothelial carcinoma.

  Dataset EGAD00001001941

• RNA-seq data from sorted CML and normal samples

  RNA-seq data from sorted populations from 10 CML samples and 4 normal bone marrow samples.

  Dataset EGAD00001004079

• 7 samples RNA-seq raw data

  Dataset comprising raw paired RNA-seq data in fastq.gz format for 7 samples of rosette forming brain tumors

  Dataset EGAD00001009265

• RNA-seq of UTUC samples

  This dataset includes transcription profiling by RNA-seq of 3 upper urinary tract urothelial tumours (UTUC).

  Dataset EGAD00001008138

• Transcriptomics for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains transcriptomics data processed with the STAR pipeline. Two sequencing kits were employed: Roche KAPA for high-quality RNA samples and Takara SMART-Seq Stranded for samples with limited RNA quantities.

  Dataset EGAD50000002236

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma - RNA-Seq

  This study aims to investigate the dysregulation of RNA translation and identify functional non-canonical open reading frames (ORFs) as potential targets for medulloblastoma treatment. The study involves ribosome profiling and RNAseq of medulloblastoma tissues and cell lines to observe the translation of non-canonical ORFs. Multiple CRISPR-Cas9 screens will be used to identify functional non-canonical ORFs implicated in medulloblastoma cell survival.

  Dataset EGAD00001011192

• Asan Medical Center Data Access Committee

  This DAC is responsible for reviewing and approving data access requests to protect the sensitive information of patients. The dataset includes RNA-seq data from CRLM patients treated with FOLFOX, bevacizumab, and atezolizumab, and supports research in gene expression analysis and therapeutic response. Data access requests require an approved ethical research plan, limited to projects related to cancer biology and therapy development.

  Dac EGAC50000000439

• Pathogenesis and Immunity in Endemic Burkitt Lymphoma

  This genomic landscape of Burkitt lymphoma represents a multimodal sequencing of tumors and control tissues and individuals to better understand the etiology, and molecular pathogenesis of Burkitt lymphoma including the roles of the associated Plasmodium falciparum malaria and EBV infections. Comprehensive sequencing set includes genomic, transcriptomic, and epigenomic datasets in concert with variable clinical phenotypes and outcome information such as anatomical presentation site, in-hospital survival rates, and EBV genome type. This deposit includes additional small RNA-seq data from endemic BL (eBL) tumors and RNA-sequencing data from sorted NK cell subsets from the peripheral blood of eBL patients. The additional small RNA-seq data are from tumor specimens from 17 eBL cases, of the previously deposited polyA RNA-seq data from 28 eBL cases (phs1282.V1). The additional RNAseq data from Fluorescence-activated cell sorting (FACS) of NK cell subsets, isolated from the peripheral blood of 7 eBL cases. The additional RNAseq data are from eBL tumor samples of 5 eBL cases, BL cell lines established from these tumor samples and also NSG mouse tumors created by implanting the established BL cell lines into NSG mice. The dataset also includes RNAseq data of the NSG mouse tumors after treatment with Rituximab (RIT) and Phosphate buffered saline (PBS). The fifth batch of data includes mRNA-seq from different passages of a single eBL cell line that have variable EBV phenotypes (low passage with lytic EBV and high passage with latent EBV). This batch also includes lytic and latent lymphoblastoid cell line (LCL) clones from a single blood donor generated through infection with the strain of EBV isolated from the aforementioned eBL cell line. For initial transcriptome analysis see: Kaymaz et al. "Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-specific Difference." Molecular Cancer Research, 2017, PMID: 28465297. For initial microRNA analysis see: Oduor et al. "Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma." Frontiers in Microbiology 8, 2017, PMID: 28400759. For initial NK subsets RNA expression analysis see: Forconi et al. "A new hope for CD56negCD16pos NK cells as unconventional cytotoxic mediators: an adaptation to chronic diseases." Frontiers in Cellular and Infection Microbiology, 2020, PMID: 32373555.For initial eBL cell line and mouse avatar RNA expression analysis see: Saikumar et al. "Endemic Burkitt lymphoma avatar mouse models for exploring inter-patient tumor variation and testing targeted therapies." Life Science Alliance, 2023, PMID: 36878637. For general overview of cohort study see: Buckle et al. "Factors influencing survival among Kenyan children diagnosed with endemic Burkitt lymphoma between 2003 and 2011: A historical cohort study." Int J Cancer. 15:1231, 2016, PMID: 27136063.

  Study phs001282

• RNA sequencing of tumor samples from patients with Waldenstrom macroglobulinemia

  RNA was extracted from flow-sorted CD19+. RNA-Seq was performed on 32 samples of 30 patients (2 replicates per samples). RNA-Seq libraries were subjected to non-stranded paired-end (2 x 75 bp) sequencing on HiSeq 2500 (Illumina). The files are in FASTQ format.

  Dataset EGAD00001005324

• Complex-I stratification of Parkinson's disease - single nucleus RNAseq

  Single nucleus RNA seq dataset for CI stratification of Parkinson's disease Single nucleus RNA seq dataset of prefrontal cortex tissue from a total of N=18 samples. Tissue samples correspond to patients with idiopathic Parkison's disease (PD) with varying levels of Complex-I activity (N=12) and neurologically healthy controls (N=6). Single nucleus RNA seq was carried out using 10X Genomics Chromium. This dataset corresponds to a subset of the samples sequenced using conventional bulk tissue RNA seq and available within this Study as a separate Dataset.

  Dataset EGAD50000000432

• Single-cell profiling reveals monocyte mitochondrial dysfunction in patients with cirrhosis progressing to acute-on-chronic liver failure

  We performed single-cell RNA-seq and CITE-seq in PBMC samples derived from patients with acutely decompensated cirrhosis at risk of developing ACLF, as well as from Healthy Donors. We identified a population of monocytes associated with disease progression. We also explored the presence of this cell population in blood samples by bulk RNA-sequencing.

  Study EGAS50000001127

• Deciphering RBP - alternative splicing networks in ALS iPSC-MN: NOVA1 gain and loss of function systems

  We produced NOVA1 and EGFP over-expression RNA-seq datasets in three healthy control individuals using lentivirus-mediated gene transfer to model NOVA1 gain of function. Additionally, we produced a NOVA1 loss of function RNA-seq dataset by generating iPSC-MN with NOVA1 knock out produced by CRISPR/Cas9 in the CV-B iPSC line.

  Study EGAS00001005881

• Ongoing Replication Stress Tolerance and Clonal T Cell Responses Distinguish Liver and Lung Recurrence and Patient Outcomes in Pancreatic Ductal Adenocarcinoma

  Patients with metastatic pancreatic ductal adenocarcinoma (PDAC) survive longer when disease spreads to the lung but not to the liver. We generated overlapping, multi-omic datasets to identify molecular and cellular features that distinguish patients whose disease develops liver metastasis (liver cohort) from those whose disease progression results in lung metastasis without liver metastases (lung cohort). Lung cohort patients generally survived longer than liver cohort patients, independent of tumor subtype. We developed a pORG gene signature that distinguishes primary tumors in the liver and lung cohorts. We identified ongoing replication stress (RS) response pathways in high pORG/liver cohort tumors, while low pORG/lung cohort tumors had greater densities of lymphocytes and shared T cell clonal responses. Our study demonstrates that liver-avid PDAC is associated with tolerance to ongoing RS, limited tumor immunity, and less favorable outcomes; whereas low RS, lung-avid/liver-averse tumors are associated with active tumor immunity that may account for favorable outcomes. As expected, we found high frequencies of KRAS, TP53, CDKN2A, and SMAD4 gene alterations in our tumor samples. High pORG activity (GSVA scores) in our primary tumors appear to be positively correlated with alteration frequencies in both TP53 and CDKN2A. We did not see a correlation with alterations in KRAS as almost all the tumor samples have KRAS alterations. From a de-identified dataset of 1,873 patients diagnosed with and/or treated for PDAC at our institution between 2004 and 2020, we identified 422 patients for which we had specimens with sequencing data (N=374) and/or specific evidence of disease metastasis site(s) from the OHSU cancer registry or disease-relevant computed tomography (CT) scans to allow cohort classification. Note that our study includes RNA-Seq, DNA-Seq panel, and TCR-Seq (T-cell Receptor Sequencing) data, but that this dbGaP submission just includes the patients/samples with RNA-Seq and/or DNA-Seq panel data. Therefore, this submission includes 290 samples from 278 patients. TCR sequence data is available on the Adaptive Biotechnologies platform. Clinical course timepoints, patient demographics, stage, grade, nodal involvement, resection margins, and angiolymphatic invasion were provided as deidentified data by the OHSU cancer registry with quality control data verification in a subset by pathologists (BB and TM). We reviewed all available computed tomography (CT) scans for all patients with primary tumor resection dates recorded by the cancer registrar, with tumor samples analyzed by RNA-seq, DNA-seq, or TCR-seq, and/or with additional information indicating metastatic spread (e.g., metastatic samples received for related studies). We abstracted the site of all lesions proven to be metastatic by biopsy and/or that clearly increased in size during progression or decreased in size during treatment as long as a radiologist described the lesion as “likely”, “suspicious for”, “concerning for”, or “favor” metastasis. Clinical imaging was reviewed by a radiologist (AG) to validate patient assignments to the liver, lung, and neither liver nor lung (other recurrence site) cohorts. Time to recurrence was calculated from the earliest of either the recurrence date provided by the OHSU cancer registry, or the date of earliest lesion abstracted from CT reports. The subject attributes reported in this submission were up to date at the time of our data freeze, which occurred July 2021.

  Study phs003597

• H3K27ac/H3K27me3 landscape of medulloblastoma

  We profiled 111 patient medulloblastoma primary tumor samples by bulk RNA-seq (19 samples), 27ac (98 samples) / 27me3 (61 samples) ChIP-Seq, WGS (4 samples) and 27ac hichip (8 samples). Submitted data consists of data generated from previously unpublished tumors as well as complementary data for data sets already published for identical medulloblastoma tumors (ex: 27me3 ChIP-Seq and RNA-Seq data submitted for a tumor with publicly available WGS data). The raw fastqs and hg19 aligned RNA-Seq bams are provided.

  Dataset EGAD00001009709

• Single-cell RNA-seq profiling of patient derived organoids

  The aim of this study was to profile developement of resistance to cancer treatments using organoids. Two patient derived colorectal cancer organoids were profiled using single cell RNAseq after treatment with a combination of different anticancer drugs. The organoids were profiled both after 4 weeks of treatment and after a drug holiday of 2 weeks.

  Study EGAS50000001025

• RNA-seq derived from metastatic Castration-Resistant Prostate Cancer

  Patients with progressive, metastatic castration-resistant prostate cancer (mCRPC) underwent metastatic tumor biopsy. 118 total samples including 14 paired samples (baseline and later progression). Various organ sites including soft tissue & bone were present. Published in DOI: 10.1200/JCO.2017.77.6880 Journal of Clinical Oncology 36, no. 24 (August 20, 2018) 2492-2503.

  Dataset EGAD00001008991

• A phase II trial of the aurora kinase A inhibitor alisertib for patients with castration resistant and neuroendocrine prostate cancer: efficacy and biomarker evaluation

  Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may develop de novo or as a mechanism of treatment resistance. N-myc is capable of driving NEPC progression. Alisertib inhibits the interaction between N-myc and its stabilizing factor Aurora-A, inhibiting N-myc signaling, and suppressing tumor growth. In this single arm, multi-institutional open label phase 2 clinical trial of alisertib, sixty men were treated with alisertib 50mg twice daily for 7 days every 21-days. Eligibility included metastatic prostate cancer and at least one: small cell neuroendocrine morphology; ≥50% neuroendocrine marker expression; new liver metastases without PSA progression; elevated serum neuroendocrine markers. The primary endpoint was six-month radiographic progression free survival. Pre-treatment biopsies were evaluated by whole exome and RNA-seq.

  Study phs001666

• RNA-seq colorectal adenomas NKI-AvL TGO series NGS-ProToCol

  The dataset "RNA-seq colorectal adenomas NKI-AvL TGO series NGS-ProToCol" includes 2 x 30 fastq files from paired-end total RNA sequencing on Illumina HiSeq2500 for 30 snap-frozen colorectal adenomas.

  Dataset EGAD00001004055

• Leiomyosarcoma RNA-Seq

  RNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic12 relapses) and 13 tumors treated with radiation(7 primaries, 6 metastatic relapses). RNA-Seq sequencing was performed using established protocols on Illumina HiSeq 2500

  Dataset EGAD00001006628

• Single RNA-Seq of fCAB treated tRNAs from VDH01

  Single RNA-seq of fCAB treated tRNAs from vdh01 samples (5 replicates). tRNAs were extracted using Mirvana° Invitrogen kit. The samples were prepped with Il TruSeq Small RNA and sequenced on Illumina NextSeq550.

  Dataset EGAD00001008743

• RNA-seq colorectal carcinomas NKI-AvL TGO series NGS-ProToCol

  The dataset "RNA-seq colorectal carcinomas NKI-AvL TGO series NGS-ProToCol" includes 2 x 30 fastq files from paired-end total RNA sequencing on Illumina HiSeq2500 for 30 snap-frozen colorectal carcinomas.

  Dataset EGAD00001004056

• RNA-seq of BCR-ABL1 lymphoblastic leukemia

  This dataset is derived from whole-transcriptome sequencing (RNA-seq) of RNA from 57 BCR-ABL1 lymphoblastic leukemias (53 diagnostic, 4 relapse).

  Dataset EGAD00001010307

• RNA-Seq data of VDH15 cells with and without deletion of NSUN3

  paired RNA-Seq data of VDH15 cells with and without deletion of NSUN3. The 11 samples were sequenced on HiSeq 4000 and prepared with SmarTer low input RNA and Chip NEBNext kit.

  Dataset EGAD00001006560

• DDX50 Cooperates With STAU1 to Effect Stabilization of Pro-Differentiation RNAs

  This study was undertaken to determine the role of DDX50 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. DDX50, which was associated with STAU1, was found to promote epidermal differentiation and transcript stability using the methods of RNA-seq, CLIP-seq and DMS-MaP-seq.

  Study phs003766

• RNA-seq data for Heterogeneity of IKZF1 genomic alterations and risk of relapse in childhood BALL

  RNA-seq data for 14 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000151

• Single-cell RNA-seq of Bone marrow samples

  For two donors, we collected CD34 plus and CD34 minus hematopoietic cells for the single-cell RNA-seq analysis.

  Dataset EGAD50000000514

• RNA-seq data for HCC patients from Y90+Nivolumab trial

  This dataset includes RNA-seq fastq files of pre-treatment and on-treatment samples from 28 patients

  Dataset EGAD00001010132

• RNA-seq data for de-methylation of FOXP3-TSDR study

  22 RNA-seq samples of ex-vivo (TN and Treg), cultured Treg, TET1 and untreated mCherry-MOCK

  Dataset EGAD00001006865

• RNA-Seq Illumina GAII dataset

  RNA-Seq Illumina GAII dataset for the TraIT cell-line use case (added reverse and forward reads).

  Dataset EGAD00001001626

• IMpower133 processed RNA-seq data whole transcriptome

  This dataset contains log2(TPM + 1) for 271 tumor samples profiled by RNA-seq for the entire transcriptome.

  Dataset EGAD00001006927

• Transcriptomic Profiling of an Anti-PD-L1 Treated Cohort of Newly Diagnosed GBM Patients

  Checkpoint inhibitor therapy has limited efficacy in glioblastoma patient outcomes. This study involves RNA sequencing (RNA-seq) of newly diagnosed GBM patients treated with concurrent atezolizumab, radiation therapy, and temozolomide. By analyzing RNA-seq data from 39 tumors, the study aims to explore tumor transcriptomic features, including immune-based transcriptomic programs and immune infiltration, to understand their influence on PD-L1 blockade treatment efficacy and to identify which patients may benefit more from such therapy.

  Study EGAS50000000784

• Human data for chromatin accessibility (ATAC-Seq and scATAC-Seq) and transcriptome (RNA-Seq and scRNA-Seq) in eight B-cell precursors, from HSC to Naive B cells

  We generated paired transcriptomic (RNA-Seq) and chromatin accessibility (ATAC-Seq) profiles from 8 immune cell populations representing the early lymphoid hematopoietic differentiation stages along the B cell lineage: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+. Cell populations were isolated from healthy adult human bone marrow precursors and peripheral blood (n=13) following a predefined sorting strategy. For each donor, a subset of different cell type populations was obtained. Additionally, to explore the continuous dynamic of RNA and ATAC, we generated a single-cell sample of human CD34+ B cell precursors.

  Study EGAS00001007296

• scRNA Seq of MCSP+ melanoma DCC and bulkRNA Seq of MelDCC lines

  Single cell RNA Seq of: 193 MCSP+ DCC isolated from SLNs of melanoma patients, 9 MCSP+ cells isolated from LNs of non-melanoma patients, 14 melanocytes from a healthy donor. Bulk RNA Seq of 10 samples from 4 DCC-PDX-derived cell lines. Sequencing on NovaSeq6000. Fastq files.

  Dataset EGAD00001009662

• Brain Cell Type-Specific Enhancer-Promoter Connectivity Maps and Disease Risk Association

  These studies map the epigenetic landscape of microglia, neurons, astrocytes and oligodendrocytes. The initial study compared acutely isolated microglia to cultured microglia from the same donors, to identify changes that occur when microglia are removed from the brain microenvironment. In collaboration with the Rady Children's Hospital, we obtained brain tissue samples from pediatric patients representing putative normal tissue resected to gain access to brain tumors as well as tissue resected to remove epileptic foci. We assayed microglia isolated from these samples using RNA-seq, ATAC-seq and ChIP-seq for PU.1, H3K4me2, and H3K27ac. For patients from whom a sufficient cell number was obtained, we additionally cultured their microglia for up to 7 days and subjected these to the same suite of assays. In a follow-up study, we obtained brain tissue from a comparable cohort of pediatric epilepsy patients from Rady Children's Hospital. We isolated nuclei from microglia, neurons, astrocytes and oligodendrocytes, and assayed for ATAC-seq, ChIP-seq for H3K4me3, and H3K27ac, and PLAC-seq (Proximity Ligated ChIP-seq). We isolated microglia from human fetal and postnatal sample and assayed for bulk RNA-seq, bulk ATAC-seq, bulk H3K27ac ChIP-seq, single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq. For these studies, human microglia are defined by signature genes/proteins, such as P2RY12, SALL1, and CX3CR1.

  Study phs001373