ddseq单细胞转录组数据上游处理(2)-云平台illumina

云平台illumina能一家独大吗

先浏览:ddseq单细胞转录组数据上游处理(一)
因为要处理illumina的单细胞转录组数据,所以看了看其云平台:https://basespace.illumina.com/apps
琳琅满目,简单截图如下:



简单注册就可以拿到 250个积分,可以新建project来上传自己的fastq测序数据,选择对应的app来处理自己的就是咯。

You have 250 promotional iCredits remaining for use toward app fees and compute time (does not apply to storage fees).
云平台介绍写的很嚣张:https://www.illumina.com/destination/dragen.html 使用的是AWS,用户界面交互友好,是骡子是马,拉出来溜溜咯。

上传的fastq文件的文件名还有要求

包含5个部分:

  • SampleName—The sample name provided in the sample sheet. If a sample name is not provided, the file name includes the sample ID, which is a required field in the sample sheet and must be unique.
  • S1—The sample number based on the order that samples are listed in the sample sheet starting with 1. In this example, S1 indicates that this sample is the first sample listed in the sample sheet.
  • L001—The lane number.
  • R1—The read. In this example, R1 means Read 1. For a paired-end run, there is at least one file with R2 in the file name for Read 2. When generated, index reads are I1 or I2.
  • 001—The last segment is always 001.
    还可以上传很多其它类型的文件:Upload FASTQ, VCF, or Manifest Files,上传取决于自己的网速,我这边10分钟可以上传3G的文件:

    公共数据中心

    看了看数据蛮多的,可以拿来练手哦; https://basespace.illumina.com/datacentral

    这些数据可以直接导入illumina自己的APP,必然的,反正都是他们的AWS上面。

    新建project

    只有新建了 https://basespace.illumina.com/projects/ 才能在上面上传自己的fastq测序数据,然后选择流程。
    比如我选择:https://basespace.illumina.com/apps/5084079/SureCell-RNA-Single-Cell?preferredversion

    这里面还附带了两个测试数据,可以直接浏览他们的分析结果:

  • Analysis: SureCell RNA Single-Cell v1.1 - K562 Combined Samples 1-4
    示例数据出报告如下;

    中间分析结果文件如下;

    如果是自己上传的数据需要自己选择APP来处理,需要排队和消耗自己的积分。

 

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