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A new approach overcomes the hurdles of identifying large, complex structural variants in cancer genomes by directly comparing tumor and normal genome sequencing reads.
CRISPR-Cas9 can be used to edit both single and multiple genes in postmitotic neurons in adult mice enabling rapid assessment of gene functions in the brain.
Efforts to improve the efficiency of photosynthesis in crop plants will benefit from a resource of transcriptomic and metabolomic data on maize and rice.
An elegant mathematical model supported by experiments in Escherichia coli demonstrates how clustering enzymes can efficiently channel intermediates from one enzyme to the next, facilitating rational engineering of metabolism.
Coupling limited proteolysis and a proteomics workflow enables measurement of both subtle and wholesale protein conformational changes in a eukaryotic proteome.
Analysis of the genome editing activity of more than 1800 sgRNAs in mouse and human cells yields rules to facilitate design of highly active RNA guides for Cas-9 genome editing.
For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA- depletion enables effective analysis of degraded RNA samples.
The Sequencing Quality Control (SEQC) consortium shows that junction discovery and differential gene expression profiling with RNA-seq can be robust but transcript-level and absolute measurements remain challenging.
A comparison of RNA-seq and microarray data from samples treated with diverse drugs highlights a dependency of cross-platform concordance on treatment effect.
Remove unwanted variation (RUV) is a new statistical method for RNA-seq data normalization that uses control genes or samples to improve differential expression analysis.