17261 results for "free coins in fc 26 Visit Buyfc26coins.com for latest FC 26 coins news..xwWa"

in 17.61 milliseconds.

• Ribosomal profiling on Epstein-Barr virus transformed B-lymphoblastoid cell lines

  Epstein-Barr virus-transformed B-lymphoblastoid cell lines from six individuals (HG00114, HG00282, NA12005, NA12044, NA12717 and NA12751) of the GEUVADIS Project were selected for ribosomal profiling. For each EBV-LCL, 20 million cells were treated with 2 μg/ml harringtonine and 100 μg/ml cycloheximide. After lysing cells in lysis buffer supplemented with 100 μg/ml cycloheximide, ribosome complexes were purified by density purification. Small RNA molecules were isolated using the NucleoSpin miRNA Kit (Bioke, Leiden, Netherlands), followed by RNA PAGE gel separation. Universal linkers were added after dephosphorylation. After reverse transcription, the cDNA was circularized and, after ribosomal RNA depletion, barcoded and sequenced on Illumina NextSeq 500.

  Dac EGAC50000000209

• Clonal architectures predict clinical outcome in clear cell renal cell carcinoma

  We analyze the clonal architectures of ccRCC patients from three different populations, including TCGA, Japanese and Chinese patients. We characterize the mutational signatures across different populations and evolution stages. The TCGA and Japanese data sets were downloaded from published studies and we also generated the whole genome sequencing data for more than 40 Chinese patients.

  Study EGAS00001003447

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  ChIP-Seq data for 172 CD14-positive, CD16-negative classical monocyte sample(s). 572 run(s), 345 experiment(s), 340 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002672

• Whole Exome Sequencing data of glioma from the Chinese Glioma Genome Atlas (CGGA) project

  Glioma is the most common and aggressive brain cancer in adults. While primary glioma has been widely studied, molecular characterization of recurrent glioma is still rare. The high-quality sequencing data that we generated provides a useful resource for the community. The CGGA project contains over 2,000 samples from Chinese cohorts. It totally includes the whole-exome sequencing (286), DNA methylation (159), mRNA sequencing (1,018), mRNA microarray (301) and microRNA microarray (198) and matched clinical data. CGGA removes the barriers to researchers, providing rapid and convenient access to high-quality functional genomic data resources for biological research and clinical applications.

  Dataset EGAD00001006445

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (ChIP-Seq for CD4-positive, alpha-beta T cell, on genome GRCh37)

  ChIP-Seq data for 154 CD4-positive, alpha-beta T cell sample(s). 355 run(s), 265 experiment(s), 250 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002673

• Whole Genome Sequences of 18th century African descended individuals from Charleston, South Carolina.

  This study presents Whole Genome Sequencing results from the Anson Street African Burial Ground Project, which is a community-based initiative aimed at understanding the histories of 37 Ancestors in Charleston, South Carolina. Here we report fastq files for all 37 Ancestors. DNA was extracted at the University of Tennessee-Knoxville following Dabney et al. 2013, and dual index libraries prepared using a modified NEBNext Ultra II kit with partial USER enzyme digestion. Libraries were then enriched for human genomic DNA (MyBaits) and sequenced on Illumina Platforms.

  Dataset EGAD00001009643

• COMPARE study: participants typed during UK Biobank version 2 array development phase

  The COMPARE study enrolled 29,066 British blood between donors between February 2016 and March 2017, the study aim is to find the optimum technology for haemoglobin screening (ISRCTN 90871183). All participants were at the time of recruitment active blood donors. The 4,796 participants in this dataset have consented to join the NIHR BioResource. Genotyping data was produced using the Thermo Fisher Scientific Axiom Genotyping platform. The UK Biobank version 2 array design was used, content on this array has been added to allow for accurate DNA based identification of human blood group antigens.

  Dataset EGAD00001005023

• Blueprint: A human variation panel of genetic influences on epigenomes and transcriptomes in three immune cell types, (RNA-Seq for CD14-positive, CD16-negative classical monocyte, on genome GRCh37)

  RNA-Seq data for 197 CD14-positive, CD16-negative classical monocyte sample(s). 197 run(s), 197 experiment(s), 197 analysis(s) on human genome GRCh37. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/blueprint_Epivar/protocols/README_rnaseq_analysis_sanger_20160816

  Dataset EGAD00001002674

• The British Autozygosity Populations BioResource (2018-06-06)

  This data set contains whole exome sequences of individuals with self-stated parental relatedness from the East London Genes & Health cohort. Rare frequency functional variants in these healthy individuals will be studied with respect to the genetic health of the participants and loss-of-function analysis of human genes. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-06-06.

  Dataset EGAD00001004150

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373