3 results match your criteria: "France. daniel.gautheret@universite-paris-saclay.fr.[Affiliation]"

Article Synopsis
  • K-mer indexing is an effective technique for searching RNA sequences in RNA-seq libraries but hasn't allowed for direct quantification of RNA until now.
  • The study demonstrates that arbitrary RNA sequences can be quantified quickly and accurately by breaking them down into k-mers, achieving precision similar to traditional methods.
  • Using an extensive RNA-seq sample collection from the Cancer Cell Line Encyclopedia, the researchers showcase how k-mer indexing can uncover non-reference sequences and variant RNAs related to specific genetic changes.
View Article and Find Full Text PDF

2-kupl: mapping-free variant detection from DNA-seq data of matched samples.

BMC Bioinformatics

June 2021

Institute of Integrative Cell Biology (I2BC), Université Paris-Saclay, CNRS, CEA, 1 avenue de la Terrasse, 91190, Gif-sur-Yvette, France.

Background: The detection of genome variants, including point mutations, indels and structural variants, is a fundamental and challenging computational problem. We address here the problem of variant detection between two deep-sequencing (DNA-seq) samples, such as two human samples from an individual patient, or two samples from distinct bacterial strains. The preferred strategy in such a case is to align each sample to a common reference genome, collect all variants and compare these variants between samples.

View Article and Find Full Text PDF

Reference-free transcriptome signatures for prostate cancer prognosis.

BMC Cancer

April 2021

Institute for Integrative Biology of the Cell, UMR 9198, CEA, CNRS, Université Paris-Saclay, Gif-Sur-Yvette, France.

Background: RNA-seq data are increasingly used to derive prognostic signatures for cancer outcome prediction. A limitation of current predictors is their reliance on reference gene annotations, which amounts to ignoring large numbers of non-canonical RNAs produced in disease tissues. A recently introduced kind of transcriptome classifier operates entirely in a reference-free manner, relying on k-mers extracted from patient RNA-seq data.

View Article and Find Full Text PDF