In the fast-paced field of single-cell biology, studies that compare methods can help scientists to pick the right technique for their research.
Single-cell biology has exploded over the past decade. Between 2015 and 2021, studies in the PubMed database of biomedical literature using the term ‘single-cell’ more than tripled, driven largely by technological innovations in isolating single cells and their molecular content.
Researchers use these and many other methods to probe individual cells in different ways, from characterizing their gene expression to documenting their epigenetic state, transcription factor activity and cell-to-cell communication.
“Single-cell biology has really been opened up to a much broader audience,” says Samantha Morris, a developmental biologist at Washington University in St. Louis, Missouri.
But even though the proliferation of wet-lab techniques and analytical methods has expanded access to single-cell studies, it has also muddied the waters for researchers trying to pick the best approach. The online single-cell RNA tools catalogue, scRNA-tools, lists nearly 1,400 software packages that turn single-cell data into scientific insights. How are researchers supposed to choose?
In the fast-paced field of single-cell biology, studies that compare methods can help scientists to pick the right technique for their research.
Single-cell biology has exploded over the past decade. Between 2015 and 2021, studies in the PubMed database of biomedical literature using the term ‘single-cell’ more than tripled, driven largely by technological innovations in isolating single cells and their molecular content.
Researchers use these and many other methods to probe individual cells in different ways, from characterizing their gene expression to documenting their epigenetic state, transcription factor activity and cell-to-cell communication.
But even though the proliferation of wet-lab techniques and analytical methods has expanded access to single-cell studies, it has also muddied the waters for researchers trying to pick the best approach. The online single-cell RNA tools catalogue, scRNA-tools, lists nearly 1,400 software packages that turn single-cell data into scientific insights. How are researchers supposed to choose?
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In the fast-paced field of single-cell biology, studies that compare methods can help scientists to pick the right technique for their research.
Single-cell biology has exploded over the past decade. Between 2015 and 2021, studies in the PubMed database of biomedical literature using the term ‘single-cell’ more than tripled, driven largely by technological innovations in isolating single cells and their molecular content.
Researchers use these and many other methods to probe individual cells in different ways, from characterizing their gene expression to documenting their epigenetic state, transcription factor activity and cell-to-cell communication.
But even though the proliferation of wet-lab techniques and analytical methods has expanded access to single-cell studies, it has also muddied the waters for researchers trying to pick the best approach. The online single-cell RNA tools catalogue, scRNA-tools, lists nearly 1,400 software packages that turn single-cell data into scientific insights. How are researchers supposed to choose?
Related Posts
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Worm’s radical transformation shows metamorphosis can change the functions of cells
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
Atlas of the brain’s striatum could guide researchers to new drug treatments
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Precursor tRNAs sense temperature changes: heat stress-induced capped pre-tRNAs suppress protein synthesis
Ketamine increases neuroplasticity in female mice but not in males
Somatic mutations linked to vascular damage in progeria
Scientists map dormant cancer cells’ hideouts, opening new targets for treatment
Soluble signals released by neighboring cells direct how the human kidney is built
Genetics influence how cancer arises – and how it evolves
RNA-based testing uncovers extraordinary diversity in mutations driving lung cancer
Study offers new insights into why ex-smokers remain at elevated risk of lung disease
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