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Transcriptome profiling of human lung cancer cell lines.

GSE64098 Homo sapiens (human) RNA-seq (gene expression) 40 samples Submitted 2015/03/13 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 40 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Lung cancerThis series is part of our curated briefing on it.
Samples
40 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Purpose: The aim of this study is to compare different RNA extraction methods using a mixture design that allows the relative changes of the majority of genes profiled to be estimated. A number of samples were degraded to allow us to compare methods for dealing with more variable samples. Methods - Cell Culture: Lung adenocarcinoma cell lines NCI-H1975 and HCC827 from a range of passages (2-4) were grown on 3 separate occasions in RPMI media (Gibco) supplemented with Glutamax and 10% fetal calf serum to a 70% confluence.
Read the full summary ↓
To replicate common experimental conditions cell lines were treated with 0.01% Dimethyl sulfoxide (Sigma), which is commonly used as a vehicle in drug treatment experiments. After 6 hours of treatment, cells were collected, snap-frozen on dry ice and stored at -80 degrees C until required. Methods - RNA preparation: Total RNA was extracted from between half a million and million cells using Total RNA Purification Kit (Norgen Biotek) with on-column DNAse treatment accorting to the kit instructions. RNA concentration for each pair of samples to be mixed was equalised to ~100 ng/μl using Qubit RNA BR Assay Kit (Life Technologies). Replicates were pooled in known proportions to obtain mixtures ranging from pure NCI-H1975 (100:0) to pure HCC827 (0:100) and intermediate mixtures ranging from 75:25 to 50:50 to 25:75 NCI-H1975:HCC827. All mixtures corresponding to the second replicate were split into two equal aliquots. One aliquot was left intact (we refer to this as the 'good' replicate), while the second aliquot was degraded to produce known outlier samples by incubation at 37 degrees C for 7 days in a thermal cycler with a heated lid. 10 μl from each replicated mixture (both good and degraded) were used for Next Generation Sequencing library preparation using two kits: Illumina TruSeq Total Stranded RNA with Ribozero (TotalRNA) and Illumina TruSeq RNA v2 (mRNA) according to the manufacturer's instructions. Completed libraries were sequenced on HiSeq 2500 with TruSeq SBS Kit v4- HS reagents (Illumina) as 100 bp single-end reads at the Australian Genome Research Facility (AGRF), Melbourne. Approximately 30 million 100 bp single-end reads were obtained for each sample. Reads were aligned to the human reference genome hg19 and mapped to known genomic features at the gene level using the Rsubread package (version 1.16.1) (Liao et al. 2013). Single reads were then summarized into gene-level counts using FeatureCounts (Liao et al. 2014).
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE64098_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA270114 and SRA study SRP051083. Searching any of these in the dataset finder brings you back here.

Samples in this study

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