Sentences with phrase «cell sequence data»

Co-first author Alice Eunjung Lee, PhD, from the lab of Peter Park, PhD, at the Center for Biomedical Informatics at Harvard Medical School, developed the study's retrotransposon analysis tool, which detects somatic retrotransposon mutations in single - cell sequencing data.

Not exact matches

Hindson adds that even seemingly simple issues, such as how the cells are isolated and stored before sequencing, can have a major impact on the quality of the data.

Some also offer the technique as a service, taking customers» vials of cells and returning complete single - cell RNA sequence data.

The new platform processes hundreds to tens of thousands of cells per day, providing scalable, sensitive, single - cell sequencing with simple yet powerful data analysis.

He also recommends performing standard bulk - cell sequencing on a portion of the sample, to provide a basis for comparison with the single - cell DNA data.

By comparing proteomic and RNA - sequencing data from people on different exercise programs, the researchers found evidence that exercise encourages the cell to make more RNA copies of genes coding for mitochondrial proteins and proteins responsible for muscle growth.

Not only has the parasitic micro jellyfish evolved a stripped - down body plan of just a few cells, but via data generated at the KU Medical Center's Genome Sequencing Facility researchers also found the myxozoan genome was drastically simplified.

Single cell RNA sequencing can define cell types by revealing differences in the proteins produced by individual cells, however analysing the data remains challenging.

Reported in Nature Methods today, the new open source computer tool called Single Cell Consensus Clustering (SC3) was shown to be more accurate and robust than existing methods of analysing single - cell RNA sequence data, and is freely available for researchers to Cell Consensus Clustering (SC3) was shown to be more accurate and robust than existing methods of analysing single - cell RNA sequence data, and is freely available for researchers to cell RNA sequence data, and is freely available for researchers to use.

The SC3 tool was then used to analyse single - cell RNA - sequence data from two patients diagnosed with myeloproliferative neoplasm (MPN) blood cancers.

Dr Vladimir Yu Kiselev, first author from the Sanger Institute, said «We created the new SC3 tool to analyse complex single - cell RNA - sequence data, and showed that it is more robust and accurate than existing methods at grouping cells.

Dr Martin Hemberg, lead author on the paper from the Wellcome Trust Sanger Institute, said: «It has been difficult to fully exploit single - cell RNA - sequence data due to the current lack of computational methods for analysing them.

The first study to sequence and analyze the entire genome of a HeLa cell line, along with access to its sequence data, has been published Aug. 7 in its final version, by G3: Genes Genomes Genetics, an open - access, scientific journal of the Genetics Society of America.

The new controlled access policy for full genome sequence data from HeLa cells will give the Lacks family the ability to have a role in work being done with the HeLa genome sequences and track any resulting discoveries.

Under the policy, biomedical researchers who agree to abide by terms set forth in the HeLa Genome Data Use Agreement will be able to apply to NIH for access to the full genome sequence data from HeLa ceData Use Agreement will be able to apply to NIH for access to the full genome sequence data from HeLa cedata from HeLa cells.

Researchers working with stem cells should follow the example of their colleagues in genetic sequencing and clinical research, setting up global networks for sharing data, materials, and intellectual property, according to a report released today in Washington, D.C..

HM - SNS allows researchers to sequence the genomes of single tumor cells and study multiple cells simultaneously, both lowering the cost and boosting data analysis for such studies.

In addition, NIH - funded researchers who generate full genome sequence data from HeLa cells will be expected to deposit their data into a single database for future sharing through this process.

Using an unsupervised learning algorithm, the team was able to convert the T - cell receptor sequencing data into numeric distances based on similarities in the receptor sequences and cluster them by functional specificity.

The Johns Hopkins team tested ImmunoMap's ability to correlate immune responses on receptor sequencing data from T - cells in the tumors of 34 patients with cancer enrolled in a nationwide clinical trial of the immunotherapy drug nivolumab.

«With our sequencing and transcriptional data, we can figure out which of these cell lines most closely match the human tumors.

The convergence of several factors explains the trend: cheaper genetic sequencing technologies, the discovery of new oncogenes (genes that can cause a normal cell to become cancerous), a new generation of computers and bioinformatics that can analyze vast amounts of data, and a multibillion - dollar effort by researchers inside and outside the pharma industry to develop targeted drugs and companion diagnostics for cancer.

The team then performed comprehensive RNA sequencing on the blood samples followed by computational data analyses to determine what genes and cells were activated and driving these allergic reactions.

To see if any of these lay in genetic sequences on which the p53 protein acts, the investigators used data from several lines of healthy and cancerous cells subjected to various p53 - activating treatments.

The scientists used diffusion maps — a basic way to order snapshots of single cells along their developmental journey — but they plan to study developmental trajectories using a new algorithm called Wishbone, which uses single - cell RNA sequencing and mass cytometry data to specifically model branching steps during cell differentiation (Nat Biotechnol, 34:637 - 45, 2016).

The technique is an economical method that sequences a cell's complete set of transcripts and obtains live imaging data for each individual cell.

Once the cells were color - coded, Cembrowski could work with the Quantitative Genomics team to get sequencing data and he found that the green and magenta cells» gene expression was strikingly different.

We developed SomaticSniper to detect somatic mutations in whole - genome sequencing data while allowing for tumor contamination of normal cells that occurs in some types of leukemia.

Most data types for the Human Cell Atlas will require some processing to support the majority of downstream use cases (e.g. alignment and demultiplexing for single - cell RNA sequencing, detection and segmentation for image - based transcriptomiCell Atlas will require some processing to support the majority of downstream use cases (e.g. alignment and demultiplexing for single - cell RNA sequencing, detection and segmentation for image - based transcriptomicell RNA sequencing, detection and segmentation for image - based transcriptomics).

First, the researchers analyze sequence data from an individual's tumor and identify four to 10 genes altered in the cells.

By integrating the sequence data and the associated metadata, we have established laboratory and bioinformatics - based methods that enable us to investigate scientific questions including: the tropism of ZIKV for dendritic cells and the antiviral response of the cells during infection (Bowen et al. 2017); investigating the phylogenetic diversity of strains obtained by Biodefense and Emerging Infections (BEI) Resources and distributed to virologists (manuscript in preparation); the genetic determinants of ZIKV host adaptation in C6 / 36 mosquito vs. Vero cells; and the diversity of ZIKV circulating in limited geographic regions, including Barbados, Colombia, and the state of Chiapas, Mexico.

«These extensions complement the MIxS suite of metadata standards by defining the key data elements pertinent for describing the sampling and sequencing of single - cell genomes and genomes from metagenomes,» said GSC President and study co-author Lynn Schriml of the Institute of Genome Sciences at University of Maryland School of Medicine.

In the case of sequence data, metadata can encompass what organism or cell was sequenced, where it came from, what it was doing, quality metrics, and a spectrum of other characteristics that add value to the sequence data by providing context for it and enabling greater biological understanding of the significance of the sequence.

Using high - throughput DNA sequencing techniques, the research team looked at these functional elements in more than 1,000 data sets produced from over 100 mouse cell types and tissues.

Cas - Analyzer is an instant assessment tool for high - throughput sequencing data for genome edited cells.

Sequence data from the SMRT cells were assembled with HGAP17 (version 2.3.0), assuming an assembly size of 30 Mb.

To help tease out cancer's inherited components, the new study adds analysis of the sequencing data from the patients» normal cells that contain the «germline» information.

A novel study from researchers at Karolinska Institutet shows that by using so called random sequence labels, working as barcodes for tracing genetically altered cells, during CRISPR / Cas9 gene knock - outs it is possible to generate more comprehensive data from a smaller number of cells.

Along with the sequences, we collected data on environmental parameters in the samples (chlorophyll a, bacterial production, salinity, nutrients, bacterial cell numbers, and particulate organic carbon and nitrogen).

Cell biology has continued to expand ever since, extending its impact on clinical medicine and pharmacology while drawing on new technologies in bioengineering, high - resolution imaging, massive data handling, and genomic sequencing.

Researchers from the global Human Cell Atlas (HCA) Consortium have sequenced 250 000 cells involved in early human development and preliminary data analysis is now underway.

The Georgetown team's preliminary data demonstrates that they collected sequenced DNA over 68,000 base pairs long from 10,000 year - old microbial samples, meaning that the DNA came from viable cells.

Chip - seq and RNA sequencing data of KMT2D - mutated T - lymphoma cells treated with chidamide and / or decitabine.

Alexander van Oudenaarden is one of the pioneers of single cell RNA - sequencing and his lab has developed several bio-informatics tools to analyze these data in detail.

The recent developments in high throughput single - cell RNA sequencing technology (scRNA - seq) have enabled the generation of vast amounts of transcriptomic data at cellular resolution.

Unique research resources include synthetic compounds, model organisms, cell lines, viruses, cell products, and cloned DNA, as well as DNA sequences, mapping information, crystallographic coordinates, and spectroscopic data.

However, normalization is typically performed using methods developed for bulk RNA sequencing or even microarray data, and the suitability of these methods for single - cell transcriptomics has not been assessed.

Whole genome sequence data of the mutants with altered cell shape, directed mutants, wild type stocks and isolated helical and rod - shaped «wild type» C. jejuni, identified a number of different mutations in pgp1 and pgp2, which result in a change in helical to rod bacterial cell shape.

The Bioinformatics group uses computational methods to analyse genome sequences, amino acid sequences, and gene expression data, both to identify new genes of interest and to determine their structure, function and role in the cell.

Specifically, we have generated clusters of transcripts that behave the same way under the entire spectrum of the sixty - seven experimental conditions; we have assembled genes in groups according to their time of expression during successive days of ES cell differentiation; we have included expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in «Expression Waves» and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic resources.