joachimwolff / scHiCExplorer

Single-cell Hi-C data analysis toolbox
https://schicexplorer.readthedocs.io/
MIT License
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In readthedocs, there are some false command, and what is the forward and reverse barcode? #15

Open khsjh opened 1 year ago

khsjh commented 1 year ago

While running scHiCExplorer with tutorial, I have some questions about scHiCExplorer tools such as Demultiplex and BuildMatrix. (The tutorial means Analysis of single-cell Hi-C data index)

At first, in case of hicBuildMatrix, three arguments should be used, restrictionSequence, restrictionCutFile and danglingSequence

But in the tutorial, there are no required options in example command. So I tried that command including these options and it work well. (When I used this command without three required options, some error message were occurred) Is that right the example command is false? also some command is skipped the space between option and argument, such as -n1 -P1-I ... Creation of Hi-C interaction matrices index is the example.

And what is the forward barcode and reverse barcode? I think the one is barcode sequence and the other is the i5 sequence. Is that right?

joachimwolff commented 6 days ago

Hi,

Even though it has been a while since you opened the issue, I would still like to reply. It may help.

Concerning hicBuildMatrix: I think the issue arises because we made the input on HiCExplorer more stringent, but did not update this in scHiCExplorer documentation/tutorials. So yes, you have to give restrictionSequence, restrictionCutFIle and the danglingSequence to build the matrix.

Forward and reverse barcode: Hi-C data is sequenced paired-end, but the forward and reverse strand are mapped individually as single-end. In the data used in the tutorial, the original authors provide the data in the fastq files as follows: 1. line is the forward read, second line the barcode for the forward read, third line the bar code for the reverse read and fourth line the reverse read.

That we have forward and reverse barcodes is provided in the README of the Nagano et al 2017 study: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE94489 / https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE94489&format=file&file=GSE94489%5FREADME%2Etxt

I hope this clarifies your questions.

Thanks and best,

Joachim