Upload Data to the Server
- If you have irregular data (without barcode information, such as demultiplexed (seperate files for each sample) fastq from company or downloaded from NCBI), please Modify Irregular Data first, and then reorganize them for uploading. If you have regular data and barcode information, skip this step.
- Please name the fastq files as XX_R1.fastq, XX_R1_001.fastq, XX_R1.fq or XX_R1_001.fq.
- You can either upload Fastq files with barcode file seperated or not. For example:
XX_R1_001.fastq(.gz), XX_R2_001.fastq(.gz) and barcode read XX_I1_001.fastq(.gz)
- Each sequencing run should include fastq (2 or 3) files and a map file (named as XX_map.txt, see example. No - or _ in the map, use . instead.)
- It is highly suggested to Validate Map Files before uploading them, you know, to save a lot of time.
- The files of each sequencing run should be put in a folder named as XXdataset_XX (such as dataset_1. Don't compress it).
- One or more XXdataset_XX folders should be put in a NEW folder such as input_data, and then compressed the new folder to .zip (e.g. input_data.zip, using 7z in Windows, "ditto -ck --keepParent xx xx.zip" or GUI zipper in Mac OS) and uploaded it below (don't rename it after compression).
Your Email: We will send the Job ID to this Email
Job Name: Only letters, numbers and -.
Data to Upload: Please read the instruction carefully. Maximum File Size 60 Gb
Here are some example data: barcode_outside_data
Need to extract barcode file?
(If you only have R1 and R2 files, select Yes.)
(If you already have barcode fastq file (e.g. XX_I1.fastq), select either Reverse or Forward.)
Is the barcode in map file and fastq file reverse complementary:
(If you only have two fastq files, select No.)
(Quality check by FastQC)
Trainset for RDP Classifier:
Ambiguous Base Cutoff: (Number of N per sequence, 0-10)
Barcode Mismatch: (Barcode mismatch allowed, 0-5)
Minimum Length: (Minimum length after read merge, >100)
Maximum Length: (Maximum length after read merge, 100-1000)
Overlap Length Cutoff: (Minimum overlap in read merge, >5)
P value of Read Merge: (P value cutoff in read merge, should be one of 0.05, 0.01, 0.001 and 0.0001)
Resampling Depth: (Make it "auto" if you don't know the depth)
CPU Usage: (2-10 CPUs)