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scRNA workflow #969
scRNA workflow #969
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topics/transcriptomics/tutorials/scrna_preprocessing/tutorial.md
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# Analysis Strategy | ||
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Most scRNA sequencing techniques use pooled-sequencing approaches to generate a higher throughput of data by performing amplification and sequencing upon multiple cells in the same "pool". From a bioinformatics standpoint, this means that the output FASTQ data from the sequencer is batch-specific and contains all the sequences from multiple cells. |
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What are multiple cells? Just many of the same type and not a single or different cell types together?
What is a batch? What means batch-specific?
Write FASTQ not in capitals
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I agree with @erxleben that batch should be explained a little bit
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Sorry 😟
topics/transcriptomics/tutorials/scrna_preprocessing/tutorial.md
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tutorial_name: scrna | ||
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<style> |
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Can you remove the styling here?
We try to keep only Markdown here. If you need some special formatting, we should see how we can handle it more generally.
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Hi @mtekman, we changed the way we add metadata in this repository, and I've updated your PR accordingly, the metadata is now added at the top of the |
There is https://en.wikipedia.org/wiki/Bulked_segregant_analysis
for example, but never mind: bulk is probably just fine :)
…On 01.02.19 11:25, Mehmet Tekman wrote:
***@***.**** commented on this pull request.
------------------------------------------------------------------------
In topics/transcriptomics/tutorials/scrna_preprocessing/tutorial.md
<#969 (comment)>:
> + text-align: center;
+ border-right: 1px solid #ddd;
+ border-left: 1px solid #ddd;
+}
+
+</style>
+
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+# Introduction
+{:.no_toc}
+
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+## Why do Single Cell sequencing?
+{:.no_toc}
+
+Single-cell RNA (scRNA) sequencing is the technological successor to classical bulk RNA-seq, where samples are no longer defined at the tissue level but at the individual cell level. Under bulk RNA-seq the expression of genes in a sample would yield the average expression of all the constituent cells in that sample, irregardless of the distinct expressions profiles given by subpopulations of cells. The advent of scRNA sequencing has provided the means to explore samples at the individual cell level, enabling a greater understanding of the development and function of such samples by the characteristics of their constituent cells. Consider the heterogenity of cells sampled from bone marrow, where hematopoietic stem cells can give rise to many different cell types within the same tissue:
It's bulk, the second one sounds strange to me
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finished the barcodes section
<!-- Questions for team | ||
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* Does it make sense to split out the Understanding Barcodes section into its own tutorial | ||
* Does it make sense to split out the Understanding Plates and Batches into its own tutorial |
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Yes and yes to the above, but maybe into only one additional tutorials (plates, batches and barcodes)?
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Agreed, already I can see how entangled these topics are.
> 1. Create a new history and rename it (*e.g.* scRNA-seq single batch tutorial) | ||
> 1. Import the following files from [`Zenodo`](https://zenodo.org/record/2554612) or from the data library (ask your instructor) | ||
> ``` | ||
> https://zenodo.org/record/2554612/files/SRR5683689_1.fastq.gz?download=1 |
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Why do the files used here have to be different from the ones used in the barcode section?
Would simplify the logic substantially if there was only one input dataset.
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The whole barcoding example was based on a dataset I previously used, but later dropped due to it being low quality. I saw two options:
- Rewrite this entire section taking into account the new data
- Split this off into it's own hands-on tutorial because it relies only on two files
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part 1 done
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Co-Authored-By: mtekman <mtekman89@gmail.com>
Co-Authored-By: mtekman <mtekman89@gmail.com>
Co-Authored-By: mtekman <mtekman89@gmail.com>
Co-Authored-By: mtekman <mtekman89@gmail.com>
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Co-Authored-By: mtekman <mtekman89@gmail.com>
Co-Authored-By: mtekman <mtekman89@gmail.com>
thank you so much for the review @wm75 |
Clean version