17417 results for "fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins They are definitely a top seller..rG5l"

in 26.56 milliseconds.

• Single Cell Genome Sequence for DLP+ library A95632C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 6 on DLP+ library A95632C

  Dataset EGAD00001009322

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Single Cell Genome Sequence for DLP+ library A95635A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 116.126 on DLP+ library A95635A

  Dataset EGAD00001009324

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• Single Cell Genome Sequence for DLP+ library A95652A

  Single Cell Genome Sequence for immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 on DLP+ library A95652A

  Dataset EGAD00001009326

• Single Cell Genome Sequence for DLP+ library A95652B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A95652B

  Dataset EGAD00001009327

• 10x Genomics Single Cell Gene Expression for TOV2295(R)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line TOV2295(R)

  Dataset EGAD00001009158

• 10x Genomics Single Cell Gene Expression for SA1035X7XB03502

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 7

  Dataset EGAD00001009151

• 10x Genomics Single Cell Gene Expression for SA535X4XB02498

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009152

• 10x Genomics Single Cell Gene Expression for SA1035X5XB03021

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 5

  Dataset EGAD00001009153

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03216

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009154

• 10x Genomics Single Cell Gene Expression for SA535X5XB02891

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009155

• 10x Genomics Single Cell Gene Expression for SA535X5XB02895

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 5

  Dataset EGAD00001009156

• 10x Genomics Single Cell Gene Expression for SA535X9XB03617

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 9

  Dataset EGAD00001009157

• 10x Genomics Single Cell Gene Expression for SA604X9XB02425

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA604 passage 9

  Dataset EGAD00001009159

• 10x Genomics Single Cell Gene Expression for SA610X3XB03802

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA610 passage 3

  Dataset EGAD00001009160

• Genomic characterization of a patient with AGS and CdLS transcriptomic comparison of his monocytes against healthy and disease control samples

  In this study, we describe an extreme genetic phenotype of two simultaneous genetic lesions, leading to broad alterations in immunophenotype and transcriptome. Whole Exome Sequencing and RNA-Sequencing of CD14+ monocytes was performed on the case patient, and RNA-sequencing was also performed on disease (Systemic Lupus Erythematosus) and healthy controls.

  Study EGAS00001007829

• EM-seq data from plasma cfDNA samples of ALS patients, control and C9-carriers

  This dataset contains targeted EM-seq data from 61 plasma cfDNA samples spanning 20 sporadic ALS, 10 C9orf72-ALS, 10 asymptomatic C9orf72 expansion carriers, and 21 non-disease controls. Libraries were prepared with the NEBNext Enzymatic Methyl-seq (EM-seq) kit, captured using the Twist Human Methylome Panel (3.98 M CpGs; 123 Mb), and sequenced on Illumina NovaSeq 6000 (150 bp paired-end; ~45× on-target depth) with unmethylated lambda DNA spike-in and a 20% PhiX balance library. The dataset includes per-sample gzipped FASTQ files (R1/R2) and minimal metadata.

  Dataset EGAD50000001808

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [scRNAseq]

  This dataset contains single-cell RNA, individually reference-aligned data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as the traditional community of Yoboi Village (in Lake Sentani) and Sereh Village (individuals from highland Papua residing near Lake Sentani) in Papua. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002385

• Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia [TCR]

  This dataset contains single-cell TCR, individually reference-aligned data from 203 individuals representing four Indonesian populations: the general urban population of Denpasar and the traditional community of Pedawa Village in Bali, as well as the traditional community of Yoboi Village (in Lake Sentani) and Sereh Village (individuals from highland Papua residing near Lake Sentani) in Papua. The dataset was produced as part of the Immune Cell Atlas of Environmental and Ancestral Diversity in Indonesia, a study aimed at characterizing how genetic background and environmental context shape immune cell states across diverse Indonesian communities.

  Dataset EGAD50000002383

• Bulk RNA-sequencing datasets from Caco-2 cells under normal or inflamed conditions treated with 4HTBZ or vehicle.

  This dataset contains 4 bulk RNA sequencing files (.fastq.gz) and a metadata file (.csv) from Caco-2/TC7 intestinal epithelial cells under normal or inflamed conditions, followed by treatment with 4HTBZ or vehicle. The cDNA libraries were prepared with the QuantSeq 3′ mRNA-Seq Kit (Lexogen, Inc.) and sequenced on an Illumina HiSeq4000 system. The metadata file provides sample information (experimental condition and code identifier). Raw sequencing reads were quality-checked with FastQC, trimmed with Trimmomatic, and aligned to the human reference genome (GRCh38) using HISAT2.

  Dataset EGAD50000001759

• PRO-SPeCT: PROstate cancer heterogeneity deconvolution through Single cell Profiling of Chromatin accessibility and Transcriptomic output

  38 prostate cancer specimens derived from five human patients with ISUP ≥ 3 pathology who underwent radical prostatectomy and pelvic lymph node dissection at surgery as part of the International Cancer Genome Consortium (ICGC) late-onset cohort. Using single-cell multiome (expression and chromatin accessibility from RNA and ATAC, respectively) sequencing assay, we characterized 282,956 nuclei/cells, with a median of 6 primary tumor foci from the prostate gland and 3 locoregional lymph node metastases across all patients.

  Dataset EGAD50000000745

• Precursor lesions, clonal architecture and relapse in Wilms nephroblastoma

  Targeted resequencing at high depth (21 genes, 9 chromosomal regions): at least 4 FFPE samples per case and matched germline DNA: * 100 cases with detailed outcome data, including 15 cases with tumour relapse (515 samples) * 40 cases with matched pre-chemotherapy biopsies (240 samples) * 50 nephrogenic rests matched to above cases (50 samples) We expect a proportion (possibly 10%) of cases to be mutationally silent on the above studies, and propose to subsequently carry out integrated whole-genome, methylome and transcriptome studies on matched frozen tissue from these cases

  Dataset EGAD00001003217

• RNA-seq of iPSC-derived hepatocyte-like cells

  We performed RNA-seq on polyA-enriched mRNA isolated from the original liver biopsy tissue (Liver tissue), primary liver cells (PLC), hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs), and iPSCs. RNA libraries were prepared using the Illumina TruSeq Stranded mRNA Sample Preparation protocol (ref. RS-122-2101, Illumina, San Diego CA, US) and sequenced using the Illumina HiSeq2500 platform following the manufacturer’s protocol. Samples were sequenced in paired-end mode to a length of 2x76 base pairs. Images from the instrument were processed using the manufacturer’s software to generate FASTQ sequence files.

  Dataset EGAD00001003770

• Congenital mesoblastic nephroma and infantile fibrosarcoma

  The genetic basis of many rare childhood cancers remains unknown. These include a spectrum of infant soft tissue tumors without canonical gene fusions, encompassing congenital mesoblastic nephroma (CMN) of the kidney and infantile fibrosarcoma (IFS). Here, we integrated whole genome and transcriptome sequencing and identified diagnostic markers and novel therapeutic strategies.

  Dataset EGAD00001003884