Question about the cQTL analysis in Wang et al 2018

I am writing with a question about the cQTL analysis in Wang et al 2018. Were the 292 individuals analyzed in this analysis all of European ancestry? If not, what were the sample sizes for European vs non-European ancestry, and how did you control for ancestry in your analysis?

I apologize for writing with such a detailed question, but I could not find the answer in the main text or supplement of the paper, or on the synapse website. (Context: I am interested in cross-population genetic analyses of psychiatric disease and wondering if PyschENCODE cQTL data is relevant.)

In calculating the cQTLs, we used 173 Caucasians and 119 non-Caucasians. With respect to controlling for ancestry — we used the top three genotype principal components as covariates to control for ancestral group.

Inquiry regarding PsychENCODE Datasets

We are trying to replicate some results using the bulk RNA-seq datasets available from the PsychENCODE consortium. We currently have access to the transcript RSEM count data from reads aligned to hg19. We were wondering if the same data was available for reads aligned to hg38 and if so, how we could access that data?

Sorry, we currently don’t have the transcript RSEM count data from reads aligned to hg38.

Question regarding RNA-seq data uploaded to “Synapse”

I was referred to you by Micheal Gandal for a question I have regarding you RNA-seq data from the fascinating shared article "Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder"

I know you’ve uploaded the TPM data to to PsychEncode website – could you tell me if the data this file is normalized DER-02_PEC_Gene_expression_matrix_TPM

We didn’t run any quantile normalization on this file.

MS data in the Psychencode datasets

I recently met you at LMB where you gave a wonderful talk on PsychENCODE data analysis.

You mentioned that there were MS datasets in the PsychENCODE. I am unable to find it. Is it possible for you to point me to that or point me to someone who may know about this? Is it possible for you to point out the MS data in the PschENCODE datasets?

Could you please explain a little more about what dataset you need?

I am looking for Mass Spec data sets in PsychEncode. Mark mentioned that MS analysis were done for some samples. I wonder whether you could help me in identifying them?

I just checked with our DCC team and currently we don’t have any Mass Spec data available for public sharing.

What is dcc team? I was given to believe from the publications that this data was available along with others for analysis. i would not have asked otherwise. is there a way i can reach out to any group among your dcc team that has this data to see whether i can formally collaborate with them? Can you kindly let me know who may be the best person to ask for the details of the group that may have the MS datasets? I am looking for MS data (even if it is published) from any of the samples that were used in the Psychencode project.
I am willing to collaborate and share authorships with the scientists who generated these datasets?
Would it be possible for you to point out to any one whom you may know who may have this dataset (published or unpublished)?

I have contacted the group that is generating the Mass Spec data. Are you specifically interested in proteomics related to donors with neuropsychiatric disorders? We (Sage Bionetworks) also function as the data coordination center for the NIA funded Accelerating Medicines Partnership – Alzheimer’s Disease (AMP-AD). There are a variety of studies in AMP-AD with Mass Spec proteomics on post mortem brain tissue, that also have other genomic data such as WGS and RNAseq. Included in that is the Religious Orders Study and Memory and Aging project (ROS/MAP) from the Rush Alzheimer’s Disease Center. See here for information on the cohorts. There will be TMT labeled MS on ~400 ROS/MAP donors released this fall.

Thank you for getting in touch with me. Thank you for your pointer. Indeed, we will be interested in the Alzheimer’s samples (all the three WGS, RNAseq and Proteomics).
I will write a separate note to you on this.
At the moment, we are looking for MS samples from donors with neuropsychiatric disorders.

Actually, my lab is doing something very similar as well, validating novel ORFs identified from our third generation sequencing, and riboseq data.
If you use other approaches that we did not use yet, or with some special goals more than just validating ORFs in brain, I will be happy to collaborate.
I have two students/collaborators on this.

Is it possible for me to make a quick call?

…(resolved via phone call on Jul 9, 2019)…

Question about deconvolution analysis in PsychENCODE paper

I have a question about the deconvolution method used in the flagship PsychENCODE paper Comprehensive functional genomic resource and integrative model for the human brain. I would like to perform a similar analysis on my own bulk samples using the single cell expression profiles used in the paper, however it is unclear how these profiles are formed.

Specifically, supplementary file DER-23 lists the cell type fractions for 24 cell types. These coefficients presumably came from solving the following:

B = C * W

Where B is the marker gene by samples matrix, C is the marker gene by cell type matrix, and W is the appropriate weights matrix. How do I go about obtaining or reproducing the 24 cell type profiles? From what I can tell, these profiles were not released along with the other supplemental data sets.

If you could please answer my question or forward this email on the appropriate author(s), I would appreciate it.

Sorry for the late reply. I think the profiles you want are on

Requesting information about cQTL and fQTL data from PsychENCODE

I am writing in regards to the datasets posted on PsychENCODE website. I noticed that full summary statistics for QTL maps are posted for eQTLs and isoQTLs, but cQTLS and fQTLs only have top SNP information. Is there a chance you could upload full summary stats for cQTLs and fQTLs as well?

We calculated cQTLs and fQTLs differently from eQTLs and isoQTLs. So we only have top SNP information for cQTLs and fQTLs.

Inquiry regarding PsychENCODE eQTL resource


Was the eQTLs calculated on 1,886 unique individuals?

No, the eQTLs were calculated on 1387 filtered adult samples with matching gene expression and genotypes.

In Fig S34, it mentions only 1,432 individuals have genotyped. How was the genotype information determined for the remaining 454 individuals?

We didn’t have genotype information determined for the remaining 454 individuals. So we didn’t include these 454 individuals in any QTL analysis.

The # of samples with genotypes enumerated in Table S1 and Table S11 do not appear to match. For example, Table S1 reports 450 GTEx samples (97 DFC), but Table S11 reports 25 GTEx genotypes from the pre-frontal cortex. There might be some subtlety between these two tables I have missed, could you please clarify how to properly interpret these tables?

The Genotypes column in Table S11 only includes the filtered high genotyping quality samples (for example, genotype imputation accuracy score R2>0.3) which have matched RNA-seq data.