Posts Tagged ‘rnaseq’

Assembly-based inference of B-cell receptor repertoires from short read RNA sequencing data with V’DJer | Bioinformatics | Oxford Academic

September 30, 2017

Assembly-based inference of Bcell receptor repertoires from..RNAseq w/
V’DJer Less diversity assoc w/ long survival

paper on geuvadis rna-seq variant calling

February 11, 2017

Calling genotypes from public RNA-sequencing data enables
identification of genetic variants that affect gene-expression levels

Patrick Deelen†,
Daria V Zhernakova†,
Mark de Haan,
Marijke van der Sijde,
Marc Jan Bonder,
Juha Karjalainen,
K Joeri van der Velde,
Kristin M Abbott,
Jingyuan Fu,
Cisca Wijmenga,
Richard J Sinke,
Morris A Swertz† and
Lude Franke†

Genotypes from…#RNAseq…enables identification of…variants, related to ASE & eQTLs Validation w/ #Geuvadis

What Dead Pigs Can’t Teach Us About ‘C.S.I.’

July 24, 2016

What Dead Pigs Can’t Teach Us About @CSI_CBS Wonder what this tells us about RIN? #RNAseq

Single-Cell RNA-Seq Reveals Dynamic, Random Monoallelic Gene Expression in Mammalian Cells | Science

January 13, 2016

#SingleCell #RNASeq Reveals Dynamic, Random Monoallelic Gene Expression, occurring in ~20% of genes in mice cells

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells : Nature Biotechnology : Nature Publishing Group

November 14, 2015

Heterogeneity in #singlecell RNAseq…hidden subpopulations by @OliverStegle lab scLVM corrects for cell cycle phase

Buettner, Florian, Kedar N. Natarajan, F. Paolo Casale, Valentina
Proserpio, Antonio Scialdone, Fabian J. Theis, Sarah A. Teichmann,
John C. Marioni, and Oliver Stegle. "Computational analysis of
cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals
hidden subpopulations of cells." Nature biotechnology 33, no. 2
(2015): 155-160.

The landscape of long noncoding RNAs in the human transcriptome : Nature Genetics : Nature Publishing Group

January 28, 2015

Landscape of lncRNAs in the human #transcriptome 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

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium : Nature Biotechnology : Nature Publishing Group

October 13, 2014

Comprehensive assessment of #RNAseq… by #SEQC Spikeins as negative controls, so all diff expression results in FPs.

Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study : Nature Biotechnology : Nature Publishing Group

October 10, 2014

Multiplatform assessment of #transcriptome profiling [w.] RNAseq Nice plots showing great effect of poly-A selection

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

August 30, 2014

#Singlecell #RNAseq highlights intratumoral heterogeneity Subtype classifiers variably expressed across indiv. cells

Patel AP(1), Tirosh I(2), Trombetta JJ(2), Shalek AK(2), Gillespie SM(3),
Wakimoto H(4), Cahill DP(4), Nahed BV(4), Curry WT(4), Martuza RL(4), Louis
DN(5), Rozenblatt-Rosen O(2), Suvà ML(6), Regev A(7), Bernstein BE(8).

Published Online June 12 2014
Science 20 June 2014:
Vol. 344 no. 6190 pp. 1396-1401
DOI: 10.1126/science.1254257

Pacbio MCF-7 transscriptome dataset

July 30, 2014