Datasets for the Carpentry-style RNA-seq lesson

<strong>Lesson files</strong> For all compressed files, go to the Shell and uncompress using `tar -xzvf myarchive.tar.gz`. <strong>1) Bioinformatic files: </strong>bioinformatic_tutorial_files.tar.gz This archive contains the following datasets: FASTQ files from Arabidopsis leaf RNA-seq: Arabidopsis_sample3.fq.gz Arabidopsis_sample1.fq.gz Arabidopsis_sample4.fq.gz Arabidopsis_sample2.fq.gz Arabidopsis thaliana genome assembly and genome annotation: AtChromosome1.fa.gz ath_annotation.gff3.gz The sequence of sequencing adapters in adapters.fasta. <strong>2) Gene counts usable with DESeq2 and R: </strong>tutorial.tar.gz This archive contains the following datasets: <strong>raw_counts.csv</strong>: a dataframe of the sample raw counts. It is a comma-separate values file therefore data are separated by commas ','. <strong>samples_to_conditions.csv</strong>: a dataframe that indicates the correspondence between samples and experimental conditions (e.g. control, treated). <strong>differential_genes.csv: </strong>a dataframe that contains the result of the DESeq2 analysis specifying this contrast in `DESEq2::results()` function: `<code class="language-plaintext">contrast = c("infected", "Pseudomonas_syringae_DC3000", "mock")</code> The<strong> raw_counts.csv </strong>file was obtained by running the `v0.1.1` version of a RNA-Seq bioinformatic pipeline on the mRNA-Seq sequencing files from Vogel et al. (2016): https://www.ebi.ac.uk/ena/data/view/PRJEB13938. Please read the original study (Vogel et al. 2016): https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.14036 ==== <strong>Exercise files</strong> <strong>1) NASA spaceflight</strong> The NASA GeneLab experiment GLDS-38 performed transcriptomics and proteomics of Arabidopsis seedlings in microgravity by sending seedlings to the International Space Station (ISS). The raw counts, scaled counts and sample to conditions files are available in the ZIP archive <strong>2) Deforges 2019 hormone-treatments: </strong>deforges_2019.tar.gz This archive contains: arabidopsis_root_hormones_raw_counts.csv arabidopsis_root_hormones_sample2condition.csv dataset01_IAA_arabidopsis_root_raw_counts.csv dataset02_ABA_arabidopsis_root_raw_counts.csv dataset03_ACC_arabidopsis_root_raw_counts.csv dataset04_MeJA_arabidopsis_root_raw_counts.csv The <em>arabidopsis_root_hormones_raw_counts.csv</em> file contains all gene counts from all hormones. Separate datasets were made for each hormone for convenience.