rnaseq_fastq
data type. Expand to view the properties of rnaseq_fastq
datasets:
Properties
Wu, A. C. K., Patel, H., Chia, M., Moretto, F., Frith, D., Snijders, A. P., & van Werven, F. J. (2018). Repression of divergent noncoding transcription by a sequence-specific transcription factor. Molecular Cell, 72(6), 942-954.e7. https://doi.org/10.1016/j.molcel.2018.10.018Additionally, in order to perform alignment, a reference genome FASTA file and gene annotation GTF or GFF file must be provided. Additional reference data, such as a reference transcriptome or additional FASTA could be required depending on your analysis. We’ve used the
rnaseq_reference
data type to allow you to store all reference data together. Expand to view the properties of rnaseq_reference
datasets:
Properties
rnaseq
pipeline, which is included in your Mantle account.
rnaseq_fastq
datasets into an input samplesheet. Additionally, we added a process at the end of the workflow to collect some of the files that the pipeline creates into Mantle datasets, and to register the MultiQC report HTML file as an output of the pipeline on Mantle, which allows it to be displayed on the pipeline run page.
count_matrix
dataset) in the bulk_rnaseq
notebook, which ran in the spatial-transcriptomics-analysis
environment.
matrix
property on the dataset and mark the dataset as an input to the analysis notebook. Then, we used the Scanpy package to perform differential expression analysis.