five

Seq-Scope analysis of human acne

收藏
NIAID Data Ecosystem2026-03-13 收录
下载链接:
https://www.ncbi.nlm.nih.gov/sra/SRP343259
下载链接
链接失效反馈
官方服务:
资源简介:
Skin samples were analyzed through Seq-Scope. Overall design: A 6 mm punch skin biopsy was frozen in OCT medium and stored at -80°C until sectioning. The current study utilized Seq-Scope[HISEQ], which is similar to the previously described version of Seq-Scope [MISEQ] (PMID: 34115981), but utilized the HISEQ2500 flow cells for Seq-Scope array generation, instead of the MISEQ flow cells. All the procedures are extensively described in the former paper, and current study was performed almost identically; however, following things were different between the two studies: (1) To perform the 1st-Seq process, HISEQ2500 sequencing was performed with 100 pM of HDMI32-oligo library, and generated 1.1 million clusters/mm^2 fully sequenced pixel density (PF clusters). (2) HISEQ2500 tiles have a rectangular shape and are arranged to form a minimally interrupted large imaging area. Therefore, images from individual tiles were assembled to present a larger image that can be aligned with the hematoxylin and eosin histology results. (3) To accommodate the larger imaging area, volume of the solutions was proportionally increased during the experiment. (4) During the secondary strand synthesis, we used an updated Randomer sequence (5'-TCAGACGTGTGCTCTTCCGATCTNNNNNNNNB-3'). Compared to the original Randomer (5'-TCAGACGTGTGCTCTTCCGATCTNNNNNNNNN-3'), the updated Randomer sequence does not anneal to the poly-A region, enabling more efficient transcriptome alignment. (5) To further substantiate our former results from scRNA-seq and spatial-seq, we focused on one acne sample, which presented an ideal spatial orientation that reveals the relationship between diverse inflammatory populations (including TREM2 macrophages) and hair follicle pathology. Other experimental details and analysis methods are as described in the previous study.
创建时间:
2022-07-24
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作