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
Posts Tagged ‘transcriptome’
A survey of human brain transcriptome diversity at the single cell level
June 27, 2017Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors : Nature Genetics : Nature Research
May 6, 2017http://www.nature.com/ng/journal/v49/n5/full/ng.3818.html
Ref component analysis..of transcriptomes, by @Robson_Paul &co http://www.Nature.com/ng/journal/v49/n5/full/ng.3818.html Clustering similarity of samples to tissue references
Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins : Nature Genetics : Nature Publishing Group
March 3, 2016Gene-gene & gene-env interactions…by #transcriptome…in twins by @dermitzakis lab
http://www.nature.com/ng/journal/v47/n1/full/ng.3162.html Nice model for ASE HT @cjieming
Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins
Alfonso Buil, Andrew Anand Brown, Tuuli Lappalainen, Ana Viñuela, Matthew N Davies, Hou-Feng Zheng, J Brent Richards, Daniel Glass, Kerrin S Small, Richard Durbin, Timothy D Spector & Emmanouil T Dermitzakis
seasonal effects on gene expression
August 9, 2015Widespread [25% genes] seasonal…expression reveals [circ]annual differences in…immunity, relevant for vaccination http://www.nature.com/ncomms/2015/150512/ncomms8000/full/ncomms8000.html
In addition to circadian rhythms, batch effects, now consider seasonal effects on gene expression
Single cell Genome + Transcriptome Sequencing
July 28, 2015G&T-seq: parallel…#singlecell genomes & transcriptomes by @CGATist
lab & others http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.3370.html low cov. matched data on 130+ cells
https://twitter.com/CGATist/status/604271101678587904
G&T-seq: parallel sequencing of single-cell genomes and transcriptomes
Iain C Macaulay,
Wilfried Haerty,
Parveen Kumar,
Yang I Li,
Tim Xiaoming Hu,
Mabel J Teng,
Mubeen Goolam,
Nathalie Saurat,
Paul Coupland,
Lesley M Shirley,
Miriam Smith,
Niels Van der Aa,
Ruby Banerjee,
Peter D Ellis,
Michael A Quail,
Harold P Swerdlow,
Magdalena Zernicka-Goetz,
Frederick J Livesey,
Chris P Ponting
& Thierry Voet
Nature Methods 12, 519–522 (2015) doi:10.1038/nmeth.3370Received 18 November 2014 Accepted 27 March 2015 Published online 27 April 2015
Identification of Asthma Phenotypes Using Cluster Analysis in the Severe Asthma Research Program (ATS Journals)
May 30, 2015Identification of #Asthma Phenotypes Using Cluster Analysis
http://www.atsjournals.org/doi/abs/10.1164/rccm.200906-0896OC#.VWk-gFxViko 5 canonical groups based on lung function, meds usage, &c
Canonical clustering of asthmatic patients into different groups
Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma (ATS Journals)
May 30, 2015Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma http://www.atsjournals.org/doi/abs/10.1164/rccm.201408-1440OC Consistent blood expression patterns
Noninvasive Analysis of the Sputum Transcriptome Discriminates
Clinical Phenotypes of Asthma (ATS Journals)
Yan, X., Chu, J.-H., Gomez, J., Koenigs, M., Holm, C., He, X., Perez,
M. F., Zhao, H., Mane, S., Martinez, F. D., Ober, C., Nicolae, D. L.,
Barnes, K. C., London, S. J., Gilliland, F., Weiss, S. T., Raby, B.
A., Cohn, L., and Chupp, G. L. “Non-Invasive Analysis of the Sputum
Transcriptome Discriminates Clinical Phenotypes of Asthma” American
Journal of Respiratory and Critical Care Medicine (2015):
doi:10.1164/rccm.201408-1440OC,
QT:{{"
Conclusions: There are common patterns of gene expression in the
sputum and blood of children and adults that are associated with near
fatal, severe and milder asthma.
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The landscape of long noncoding RNAs in the human transcriptome : Nature Genetics : Nature Publishing Group
January 28, 2015Landscape of lncRNAs in the human #transcriptome
http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3192.html Derived from RNAseq read assembly; not much overlap w/ @GencodeGenes
Matthew K Iyer,
Yashar S Niknafs,
Rohit Malik,
Udit Singhal,
Anirban Sahu,
Yasuyuki Hosono,
Terrence R Barrette,
John R Prensner,
Joseph R Evans,
Shuang Zhao,
Anton Poliakov,
Xuhong Cao,
Saravana M Dhanasekaran,
Yi-Mi Wu,
Dan R Robinson,
David G Beer,
Felix Y Feng,
Hariharan K Iyer
& Arul M Chinnaiyan
Nature Genetics (2015) doi:10.1038/ng.3192Received 20 June 2014 Accepted 18 December 2014
Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study : Nature Biotechnology : Nature Publishing Group
October 10, 2014Multiplatform assessment of #transcriptome profiling [w.] RNAseq http://www.nature.com/nbt/journal/v32/n9/full/nbt.2972.html Nice plots showing great effect of poly-A selection
Blood transciptome paper
September 28, 2014Splicing changes along the blood lineage, good ex. of the
state-of-the-art in human transcriptomics
http://www.sciencemag.org/content/345/6204/1251033.abstract
Science 26 September 2014:
Vol. 345 no. 6204
DOI: 10.1126/science.1251033
Transcriptional diversity during lineage commitment of human blood progenitors
Chen et al.
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