Access modalities in h5 files to extract expression and atac data from 10xh5
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Cynthia • 0
@5413a489
Last seen 11 months ago
United States

Hi everybody

When following the vignette tutorial (https://stuartlab.org/signac/articles/pbmc_multiomic.html) to implement a pipeline to analyze rna-seq and atac data. I want to know how and where the data are stored in the hdf5 object. This basically is related with the cell features called modalities, and aren't not explained in the tutorial. Here, I share a simple explanation that help you to know what metadata you have available to extract.

The h5ad files are composed of a cell by feature, such as genes expression and peaks & other metadata. So, a way to extract expression data or other related, is as described below:

First load the hdf5 file

    sc_hippo <- Read10X_h5("/folder/file_name_hdf5_file.h5"). #set your file name

In this MTX each row represents a peak, predicted to represent a region of open chromatin.

Next read the modalities available in the object

    str(sc_hippo)

Output example:

$ Gene Expression:Formal class 'dgCMatrix' [package "Matrix"] with 6 slots

.. ..@ i : int [1:8851990] 60 70 73 80 82 84 86 94 104 106 ...

.. ..@ p : int [1:2365] 0 2972 7234 9033 12814 18212 21573 22506 24986 28028 ...

$ Peaks :Formal class 'dgCMatrix' [package "Matrix"] with 6 slots

.. ..@ i : int [1:27141995] 113 356 364 415 424 535 555 629 640 787 ...

.. ..@ p : int [1:2365] 0 925 8634 14758 28329 48650 62511 74887 77451 87482 ...

The available modalities here are Gene Expression and Peaks, this modalities are detonated with the $ sign.

By last, you can reading a specific modality

    rna_counts <- sc_hippo$`Gene Expression`

CSC

rna-seq Read10X_h5 atac modalities • 662 views
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@james-w-macdonald-5106
Last seen 1 hour ago
United States

This support site is intended to help people with questions about Bioconductor packages, and Signac is not a Bioconductor package. You could ask somebody from the Sajita lab directly (presumably they have some sort of support available), or perhaps you could try on biostars.org.

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