Posts Tagged ‘dw’

Nature 03142018 Single cell rnaseq of development of human brain Pfc

Sunday, March 18th, 2018

https://www.nature.com/articles/nature25980

A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex

Suijuan Zhong
, Shu Zhang
[…]
Xiaoqun Wang
Nature
doi:10.1038/nature25980

New GWAS SCZ loci (nature genetics 2018)

Tuesday, March 6th, 2018

Common #schizophrenia alleles are enriched in mutation-intolerant genes & in regions under strong background selection
https://www.nature.com/articles/s41588-018-0059-2 50 novel SCZ loci & 145 loci in total, from #GWAS – associated w/ 33 candidate causal genes

QT:{{”
We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci.
“}}

Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection
Nature Genetics (2018)
doi:10.1038/s41588-018-0059-2

A survey of human brain transcriptome diversity at the single cell level

Wednesday, June 28th, 2017

Brain #transcriptome diversity at the single cell level
http://www.PNAS.org/content/112/23/7285 Has useful gene-exp. profiles of specific neural cell types

has profiles for 185 biomarker genes for 6 cell types

R package: variancePartition

Sunday, November 13th, 2016

https://bioconductor.org/packages/release/bioc/html/variancePartition.html

new tool in psychencode meeting

Authorship solution

Thursday, July 28th, 2016

A solution to a perennial problem: Co-first “author ordering determined by coin flip” – eg
http://onlinelibrary.wiley.com/wol1/doi/10.1002/anie.201604431/full & https://arxiv.org/pdf/1412.6980v8.pdf

similar
https://arxiv.org/pdf/1412.6980v8.pdf
∗Equal contribution. Author ordering determined by coin flip over a Google Hangout.

Similarity network fusion for aggregating data types on a genomic scale : Nature Methods : Nature Publishing Group

Tuesday, February 9th, 2016

Similarity #network fusion for aggregating data types
http://www.nature.com/nmeth/journal/v11/n3/full/nmeth.2810.html Combines mRNA, miRNA & gene fusions to classify cancer subtypes http://compbio.cs.toronto.edu/SNF/SNF

Single-cell ChIP-seq

Friday, October 23rd, 2015

#Singlecell ChIPseq reveals…subpopulations defined by chromatin statehttp://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3383.html Sparse data: on order of 1K uniq. reads/cell

http://www.nature.com/nbt/journal/vaop/ncurrent/full/nbt.3383.html

Lessons from modENCODE

Saturday, July 11th, 2015

http://www.annualreviews.org/doi/abs/10.1146/annurev-genom-090413-025448

Publication delays at PLOS and 3,475 other journals

Monday, July 6th, 2015

#Publication delays at PLOS & 3,475 other[s] by @dhimmel http://blog.dhimmel.com/plos-and-publishing-delays Perhaps journals should provide on-time stats as airlines do

Similarity network fusion for aggregating data types on a genomic scale : Nature Methods : Nature Publishing Group

Monday, June 1st, 2015

Similarity #network fusion for aggregating data types http://www.nature.com/nmeth/journal/v11/n3/full/nmeth.2810.html Combines mRNA, miRNA & gene fusions to classify cancer subtypes
http://compbio.cs.toronto.edu/SNF/SNF