Expression QTL (eQTL) Resources on FunGen-AD Resources

Knight ADRC brain gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

Knight ADRC brain gene expression QTL#

Contact#

Chunming Liu

Links to QTL analysis notebooks#

See notebooks in:

https://github.com/cumc/xqtl-analysis/tree/main/analysis/Wang_Columbia/KnightADRC/eQTL

The notebooks in this folder contain the commands and data wrangling codes for analysis of the expression data in KnightADRC. (data wrangling exist because not all data are processed using the xqtl-pipeline from the beginning and need to be reformatted to fit one intermediate step of the pipeline).

Association data preprocessing#

Knight_data_RNASeq.ipynb shows the commands used for phenotype calling.

MAGENTA African American Blood Gene Expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

MAGENTA African American Blood Gene Expression QTL#

Multi-Ancestry Genomics, Epigenomics, and Transcriptomics of Alzheimer’s (MAGENTA) Project: Participants include 465 individuals (AA – 113 with AD, 118 cognitively intact controls; NHW – 116 with AD, 118 controls) ascertained by the John P. Hussman Institute for Human Genomics (HIHG) at the University of Miami Miller School of Medicine (Miami, FL), North Carolina A&T State University (Greensboro, NC), and Case Western Reserve University (Cleveland, OH). Participants were ascertained as part of the ADSP Follow-up Study and included both cases (>65 years of age of onset) and controls (>65 years of age at age of exam). All participants were adjudicated by a clinical panel with expertise in AD related disorders and classified as AD according to standard criteria developed by the National Institute of Aging and the Alzheimer’s Association.

MAGENTA Non-Hispanic White Blood Gene Expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

MAGENTA Non-Hispanic White Blood Gene Expression QTL#

MetaBrain Brain Gene Expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

MetaBrain Brain Gene Expression QTL#

MetaBrain multi-region bulk RNA-seq gene expression data used for validation of eQTL signals in the FunGen-xQTL flagship study.

Contact#

FunGen-xQTL Analysis Team

Study Overview#

Study name: MetaBrain brain expression eQTL
Study Description: Large-scale brain eQTL meta-analysis across five brain regions used as a validation and replication resource. All five MetaBrain contexts were used to replicate xQTL signals identified in the ROSMAP, MSBB, and MiGA cohorts.
Brain regions: Cerebellum, Cortex, Basal ganglia, Spinal cord, Hippocampus
Reference: Schipper et al. 2021, Nature Neuroscience. doi:10.1038/s41593-021-00976-7

Analysis Details#

MetaBrain summary statistics were obtained from the MetaBrain resource and used as an independent eQTL replication dataset in the FunGen-xQTL flagship analysis. Fine-mapping and colocalization were performed in parallel with the primary FunGen-xQTL datasets.

MiGA multi-brain region gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

MiGA multi-brain region gene expression QTL#

A genetic and transcriptomic resource comprised of 255 primary human microglia samples isolated ex vivo from four different brain regions of 100 human subjects with neurodegenerative, neurological, or neuropsychiatric disorders, as well as unaffected controls.

Microglia Genomic Atlas from the Netherlands Brain Bank (NBB) and the Neuropathology Brain Bank and Research CoRE at Mount Sinai Hospital. The permission to collect human brain material was obtained from the Ethical Committee of the VU University Medical Center, Amsterdam, The Netherlands, and the Mount Sinai Institutional Review Board. For the Netherlands Brain bank, informed consent for autopsy, the use of brain tissue and accompanied clinical information for research purposes was obtained per donor ante-mortem.

MSBB brain gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

MSBB brain gene expression QTL#

Contact#

Minghui Wang

Links to QTL analysis notebooks#

See notebooks in:

https://github.com/cumc/xqtl-analysis/tree/main/analysis/Wang_Columbia/MSBB/eQTL

The notebooks in this folder contain the commands and data wrangling codes for analysis of the expression data in MSBB. (data wrangling exist because not all data are processed using the xqtl-pipeline from the beginning and need to be reformatted to fit one intermediate step of the pipeline).

Association data preprocessing#

Genotype data preprocessing#

Principal component analysis for eQTL mapping#

Phenotype data preprocessing#

Covariate data preprocessing#

Association scan using TensorQTL and summary statistics standardization#

TensorQTL.ipynb provides the pipeline to generate TensorQTL cis association results for all QTLs.
MSBB_eQTL provides information about the input files for TensorQTL cis association in the base_params variable in [generate_command_1].

Path(s) to cis-QTL association testing#

output of TensorQTL.ipynb

ROSMAP AC gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

ROSMAP AC gene expression QTL#

Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) AC gene expression.

Please refer to this document for an overview of the ROSMAP project.

Contact#

Frank Grenn

Data Descriptions#

Verifying current avaliable location for the dataset now

Samples were extracted using Qiagen’s miRNeasy mini kit (cat. no. 217004) and the RNase free DNase Set (cat. no. 79254), and quantified by Nanodrop and quality was evaluated by Agilent Bioanalyzer.

ROSMAP DLPFC gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

ROSMAP DLPFC gene expression QTL#

Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) DLPFC gene expression.

Please refer to this document for an overview of the ROSMAP project.

Contact#

Shrishtee Kandoi; Frank Grenn

Contact Email : ; hs3163@cumc.columbia.edu; hs3393@cumc.columbia.edu; jt3386@cumc.columbia.edu
Contact Affiliation : Boston University; Columbia University
Contact Role : Shrishtee Kandoi and Hao Sun performed QTL analysis; Haochen Sun performed fine-mapping, and Jiajun Tao performed replication

Study Overview#

Study name : ROSMAP DLPFC eQTL
Study Description : Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) eQTL analysis summary statistics using the FGC xQTL pipeline.

Samples’ phenotype information (sex, age, race etc.) can be found in ROSMAP metadata, see “Other information” section in this document

ROSMAP PCC Expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

ROSMAP PCC Expression QTL#

Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) PCC alternative splicing.

Please refer to this document for an overview of the ROSMAP project.

Contact#

Frank Grenn

Study Overview#

In progress

Sample information: ####/####_sample_attributes.csv.
Lab protocol: ####/####_lab_protocol.csv.
Computational protocol: ####/####_computational_protocol.csv.
QTL summary statistics output: ####/####.qtl_results.csv.
Fine-mapping results individual level data model: ####/####.susie.csv.
Fine-mapping results summary statistics model: ####/####.susie_rss.csv.
Colocalization with AD GWAS: ####/####.susie_coloc.csv.

Analysis Status#

TransQTL association: Need to be performed.

ROSMAP RNA-seq microglia gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

ROSMAP RNA-seq microglia gene expression QTL#

Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) microglia data-set.

Please refer to this document for an overview of the ROSMAP project.

Contact#

Travyse Edwards

Data descriptions#

The ROSMAP monocyte data were downloaded from syn2580853 on Janunary xx, 2023.

Path on CU cluster /..

I didn’t do cis assocaition for microglia seperately?

Path(s) to fine-mapping with SuSiE RSS model#

Fine-mapping model objects (SuSiE-RSS, .rds) are available in the finemapping models folder (syn69670592).

ROSMAP RNA-seq monocyte QTL

Mon, 01 Jan 0001 00:00:00 +0000

ROSMAP RNA-seq monocyte QTL#

Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) monocyte data-set.

Please refer to this document for an overview of the ROSMAP project.

Contact#

Travyse Edwards

Data descriptions#

The ROSMAP monocyte data on MSSM were downloaded from syn22024496 on July 11th, 2022. (path on MSSM to be added)

Path on MSSM cluster /sc/arion/projects/load/data-ext/ROSMAP/raw/rnaseq_monocytes_syn23650893/Gene_Expression-RNA-seq-monocyte
Path on S3 Bucket s3://statfungen/ftp_fgc_xqtl/eQTL/ROSMAP/monocyte/analysis_ready/phenotype_preprocessing/monocyte_sample_fastq.final.rnaseqc.low_expression_filtered.outlier_removed.tmm.expression.bed.gz

Preview Monocyte Gene Expression Data#

Over all 615 samples in the dataset, 302 samples have diagnosis meta data, 1 sample missing associated sex meta data.

ROSMAP snRNA-seq pseudo-bulk gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

ROSMAP snRNA-seq pseudo-bulk gene expression QTL#

Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP) snRNA-seq from different cells in Dorsolateral Prefrontal Cortex (DLPFC).

Please refer to this document for an overview of the ROSMAP project.

Contact#

Hao Sun (eQTL), Masashi Fujita (eQTL), Haochen Sun (fine-mapping), Jiajun Tao (replication)

Study Overview#

Sample information: ROSMAP/ROSMAP_Pseudo_Bulk_sample_attributes.csv.
Lab protocol: ROSMAP/ROSMAP_Pseudo_Bulk_lab_protocol.csv.
Computational protocol: ROSMAP/ROSMAP_Pseudo_Bulk_computational_protocol.csv.
QTL summary statistics output: ####/####.qtl_results.csv.
Fine-mapping results individual level data model: ####/####.susie.csv.
Fine-mapping results summary statistics model: ####/####.susie_rss.csv.

Analysis Status#

TransQTL association: Finished.

STARNET macrophage gene expression QTL

Mon, 01 Jan 0001 00:00:00 +0000

STARNET macrophage gene expression QTL#

STARNET is an RNA expression study of various disease-relevant tissues obtained from living patients with cardiovascular disease (CVD). The inclusion criterion for patients was eligibility for coronary artery by-pass graft (CABG) surgery. Please refer to this document for an overview of the STARNET project.

Contact#

Contact Name: Travyse Edwards
Contact Email: travyse.edwards@icahn.mssm.edu
Contact Affiliation: Icahn School of Medicine at Mount Sinai
Contact Role: Travyse performed QC & QTL analysis

Study Overview#

Study name : STARNET Macrophage eQTL
Study Description : Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) macrophage eQTL analysis summary statistics generated using the FGC xQTL pipeline.

Analysis Details#

Sample Size Tracking Through Analysis Workflow#

Step	Sample Size
Raw Expression Data	480
QC’d Expression Data	479
After overlapping with STARNET genotype data	471

Quality Control and Normalization Details for Phenotype Data#

For quality control performed for the macrophage gene expression dataset, please refer to this markdown document.