scRNA-Seq-TCC-prep
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Code outdated
Hi,
I am willing to try your code for a 10x scRNA-Seq analysis. However, in the latest V2 chemistry, they changed the design of barcodes, R1 and R2 reads. In simple, R1 is 26 bp long, including the cell barcodes and UMI, while R2 is 98 bp long, which is the length of the transcripts. The independent I7 index is saved in an I1.fastq file. So your jupyterhub notebook is almost useless without substantial changes. Not sure whether you will be actively developing this code or not, but just in case you are, please check 10x for their latest development.
Best, Ying
I indeed noticed the same issue as @yingzhang121. My guess is that the fastq files you processed were generated with cellranger demux
, while 10X genomics now recommends the use of cellranger mkfastq
(https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/mkfastq)
I am curious to know whether updating this pipeline is in your plans. That would be really useful!
We have changed the script to be compatible with chemistry version 2. Now, we are investigating whether the thresholding strategy and the error correction of the barcodes is broadly applicable. So, some more time needed before we could eventually submit an update of the scripts.
Great! Keep us updated!
We have written a perl wrapper and adapted the python scripts from pachterlab to work with Chromium 10X chemistry v1 and v2. All is available on our github https://github.com/vibbits/sc_read_kallisto_wrapper. The thresholding strategy is finally taken over from CellRanger's thresholding strategy. Future work: we could look into the potentially faster code from the other fork and adapt it to work with chem v1 and chem v2, too.
Thanks Alex for letting us know... And for the work! Just out of curiosity: is that some work you're doing in collaboration with the Pachter lab, or independently on your side?
We picked up the scripts from their github (so we are very greatful that they are open source). Based on these scripts, we are developing pipelines (usually for pipeline tools, we use GenePattern but it can also be run in command line or transferred to Galaxy) to be run in our training courses. Single cell transcriptomics analysis will be one of our courses next year.