<![CDATA[BOL: Modular, efficient and constant-memory single-cell RNA-seq preprocessing]]> https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing? https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing Mon, 05 Apr 2021 11:19:43 -0500 https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing <![CDATA[Modular, efficient and constant-memory single-cell RNA-seq preprocessing]]> With kallisto | bustools you can

  • Generate a cell x gene or cell x transcript equivalence class count matrix
  • Perform RNA velocity and single-nuclei RNA-seq analsis
  • Quantify data from numerous technologies such as 10x, inDrops, and Dropseq.
  • Customize workflows for new technologies and protocols.
  • Process feature barcoding data such as CITE-seq, REAP-seq, MULTI-seq, Clicktags, and Perturb-seq.
  • Obtain QC reports from single-cell RNA-seq data

The kallisto | bustools workflow is described in:

Páll Melsted*, A. Sina Booeshaghi*, Lauren Liu, Fan Gao, Lambda Lu, Kyung Hoi (Joseph) Min, Eduardo da Veiga Beltrame, Kristján Eldjárn Hjörleifsson, Jase Gehring & Lior Pachter† Modular and efficient pre-processing of single-cell RNA-seq, Nature Biotechnology (2021).

 

Documentation and tutorials for the kallisto bustools workflow are available at http://pachterlab.github.io/kallistobustools. 

https://www.nature.com/articles/s41587-021-00870-2

Address of the bookmark: https://pachterlab.github.io/kallistobustools/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing#item-annotation-3966 Mon, 05 Apr 2021 12:07:00 -0500 https://bioinformaticsonline.com/bookmarks/view/43025/modular-efficient-and-constant-memory-single-cell-rna-seq-preprocessing#item-annotation-3966 <![CDATA[Comment by Neel]]> scRNA-seq_intro

https://pachterlab.github.io/kallistobustools/tutorials/scRNA-seq_intro/python/scRNA-seq_intro/

]]> Neel