4d41f2ce-16c6-4def-b52c-dcfdd459a321 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001010912 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Total RNA extracted from 15 knocking down treated 293T cells using siRNAs targeting transcription splicing factors and sequenced using Illumina Hiseq PE150 platform to generate RNA sequencing with 150bp in read length. Nearly 50 million raw reads were yielded from each sample respectively. We used FastQC to confirm the quality of raw fastq sequencing data, and Ericscript software to detect fusion transcripts.
2018-12-14 | GSE113101 | GEO
Project description:20 random DNA barcodes were designed in silico and transfected into PC3 cells. Barcodes were sequenced using Illumina-Miseq technology to find the sequence and their respective copy numbers. Current file contains the raw data of these DNA barcodes in fastq format
2016-03-31 | GSE67441 | GEO
Project description:The adult healthy human pancreas has been poorly studied given lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors thus avoiding any warm ischemia time. We found that neoplastic lesions occur frequently in healthy organs, in donors as young as in their 3rd decade of life. Using the 10X Genomics Platform, we performed single cell RNA sequencing on 6 donor pancreata, 5 of which we separately sequenced tissue from the pancreas head and tail, for a total of 11 sequencing runs. This is a robust single-cell dataset of healthy, nonpathologic pancreas tissue and includes acinar, ductal, and non-epithelial cells (myeloid cells, fibroblasts, endothelial cells, lymphocytes). We compared this dataset of normal pancreata to single cell sequencing of tumor samples previously published in Steele, et al, Nature Cancer 2020, (raw fastq in dbGap phs002071) realigned to GRCh38 reference genome (CellRanger 6.0). This GEO series contains the raw and filtered feature matrices for the donor pancreata as well as the realigned tumor samples. Supplementary files contain the aggregate feature matrices and the metadata of the donor pancreata samples and the tumor samples.
2023-05-01 | GSE229413 | GEO
Project description:To generate this dataset in RNA-seq, we performed a mixing experiment, in which we mixed mRNAs from three cell lines: lung adenocarcinoma in humans (H1092), cancer-associated fibroblasts (CAFs) and tumor infiltrating lymphocytes (TIL), at different proportions to generate 32 samples, including 9 samples that correspond to three repeats of a pure cell line sample for three cell lines. The RNA amount of each tissue in the mixture samples was calculated on the basis of real RNA concentrations tested in the biologist’s lab. This dataset was generated in house and then used to generate the count table that counts the number of reads mapped to each exon for all the samples. This count data will be pre-processed by total count normalization and genes that contained zero counts are removed.
2018-10-12 | GSE121127 | GEO
Project description:Total RNA extracted from differentiated mesenchymal stem cells at four time points (T1,T2,T3,T4) and sequenced using Illumina Hi-seq 2000 platform to generate RNA sequencing with 101bp in read length. Nearly 50 million raw reads were yielded from each sample respectively. We used FastQC to confirm the quality of raw fastq sequencing data, and SOAPfuse software to detect fusion transcripts.
2016-02-09 | GSE64032 | GEO
Project description:Transcriptomic profile of human adipose tissue progenitor cells was performed as follows. For AmpliSeq transcriptome sequencing library construction, AmpliSeq™ Library PLUS, AmpliSeq Transcriptome Human Gene Expression Panel and AmpliSeq CD indexes SetA kits were purchased from Illumina and sequencing libraries were constructed as described in AmpliSeq for Illumina Transcriptome Human Gene Expression Panel reference guide (Illumina). Equimolar concentrations of libraries were pooled at 4 nM and denatured and diluted as described in Denature and Dilute Libraries Guide (Illumina) and adjusted to final concentration of 1.4 pM. Resulting library was sequenced on NextSeq 500 using NextSeq 500/550 High Output v2 kit with 2 X 151 bp cycle. Generated raw files were converted to FASTQ files and used for data analysis. AmpliSeq transcriptome FASTQ files were analyzed on Array studio V10.0 (Omicsoft, Qiagen). Following raw read QC, first and last 10 bases were trimmed and mapped to reference genome Human.B38. The read count data was generated using GeneModel RefGene20170606. Resulting data was normalized by DESeq package, transformed to log2 value and used for ANOVA analyses.
2023-01-12 | GSE222749 | GEO
Project description:Purpose:To understand the change in transcriptome for the overxepression of ΔCSP in HepG2 cells. Methods:Total RNAs of ΔCSP stable expressing or control HepG2 cells were extracted using TRIzol (Invitrogen), following the manufacturer's instructions. RNA-seq and bioinformatic data analysis were performed by Shanghai Sangon Bio Ltd. Briefly, sequencing libraries were generated using VAHTSTM mRNA-seq V2 Library Prep Kit for Illumina® (Vazyme Biotech, Nanjing, China) following manufacturer's recommendations and were sequenced on HiSeq XTen sequencers (Illumina, San Diego, CA). Raw reads in FASTQ format were subjected to quality control using FastQC. RNA-seq reads were aligned to the reference genome using Bowtie. Uniquely mapped reads were used for further analysis. Gene expression levels are expressed as TPM (Transcripts per million reads) and differences in gene expression were calculated with rSeq. Results:There were 492 genes differentially expressed in ΔCSP-overexpressing HepG2 cells compare to the control group respectively (fold change >2 or < 0.5).
2020-12-31 | GSE129323 | GEO
Project description:Small RNAs (<100 bases in length) were purified from total RNA samples using the miRNeasy kit (Qiagen), and multiplexed miRNA libraries were prepared using a previously described protocol and sequenced on a HiSeq 2000 (Illumina). Image analysis, base calling, demultiplexing and conversion of BCL to FASTQ format were carried out using CASAVA 1.8.2 software (Illumina). Adaptor sequences were removed using mirExpress software. Fastq were 3p-adaptor trimmed. The sequences were then aligned on hg19 (GRCh37) human reference genome with STAR (v.2.5.2a), allowing no mismatch with reference. Reads were counted using HTSeq-count (HTSeq v 0.6.1p1 Python package) using “intersection-strict” mode, to count mature miRNA abundance according to miRbase v.20.
2020-08-12 | E-MTAB-6553 | biostudies-arrayexpress
Project description:For single cell RNA sequencing analysis, whole cell population isolated from two breast cancer bone metastases and associated organoid models were analyzed by 10X genomic single cell RNA platform. Raw BCL files from Novaseq6000 was converted to FASTQ files with cellranger (Version: 3.1.0) mkfastq function. Cellranger count function was then applied for read alignment, barcode and UMI counting using GRCh38 as reference. scCB2 and DoubletFinder were used to predict and remove empty droplets and doublets of single cell data. Cells with number of features less 300 and more than 9000 were further filtered out based on the distribution of number of features. For bulk RNA sequencing, RNA were extracted from FFPE preserved primary tumor and bone metastasis. Library was prepared with TruSeq Stranded mRNA for FFPE kit, and sequenced by NextSeq 500 with high output 150 cycle kit.
2022-02-08 | GSE190772 | GEO