User: SupBioInformatics
SupBioInformatics • 10
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Posts by SupBioInformatics
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... great! Thanks. I will check this out! ...
written 27 days ago by
SupBioInformatics • 10
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... Hi,
I am learning processing scRNA-seq data. I notice the ambient RNA is important metrics to QC and I found `SoupX` is the tool to detect ambient RNA. However, I realize I only have **raw gene-barcode matrix**, but lacks of **filtered gene-barcode matrix**, which is required for `SoupX` input.
C ...
written 29 days ago by
SupBioInformatics • 10
• updated
28 days ago by
Friederike ♦ 6.7k
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... Hi,
I am doing QC on the single-cell RNAseq data. I have 3 samples: **tumor, normal, adjacent**. All data shows **strong right skewed distribution** of # genes and # of cells or most cells have fewer genes. So right now, I only filtered out **cells > 10 % mitochondrial percent and cell < 200 ...
written 4 weeks ago by
SupBioInformatics • 10
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... Hi,
I tried to use SingleR to identify cell types for clusters. I have the table of results from `FindAllMakers` of `Seurat` package.
I know that I can use:
SingleR(GetAssayData(seurat.object,
assay = assay, slot = "data"), clusters = Idents(seurat.object),
ref = hpc ...
written 7 weeks ago by
SupBioInformatics • 10
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... Hi,
I am still practicing the `Seurat` workflow. I wonder how the pipeline will be the best practice for large datasets. Specifically, I am not sure if I should normalize prior to or after the merging. I list the questions in my mind:
- If I have 6 patients and each patient has two conditions, I w ...
written 9 weeks ago by
SupBioInformatics • 10
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... So my workflow will be
1. QC (filter out bad quality cells) each data (patient1-condition1, patient1-condition2, patient2-condition1 ... patient6-condition2)
2. Normalize each data (`NormalizeData`)
3. Merge (`Merge`, not integrate) all the data (so now only one combined dataset)
4. Scale the d ...
written 9 weeks ago by
SupBioInformatics • 10
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... Thanks for your detailed answer, ATpoint! I will check out the https://osca.bioconductor.org/ today. Really appreciate it!
I was confused when to merge/integrate the datasets is because I found the `Merge` function (https://satijalab.org/seurat/v3.1/merge_vignette.html) on `Seurat`. I think what ` ...
written 9 weeks ago by
SupBioInformatics • 10
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... Hi all,
I have a scRNA-seq dataset, which has 6 patients and each patient has 2 sample types (normal, tumor). So I have **12 folders** and each folder contain its scRNA data: `barcodes.tsv.zip`, `features.tsv.zip`, `matirx.mtx.tsv.zip`. I would like to use this data to practice and learn the `Seura ...
written 9 weeks ago by
SupBioInformatics • 10
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... Hi,
I know there are lots of experts on biostars. I know `ORA` needs to know total numbers of genome and not good for small sample size. `globaltest` uses random effect model and `GSVA` implements non-parametric KS test like GSEA.
I wonder if anyone can explain (simply) the differences among `ORA ...
written 3 months ago by
SupBioInformatics • 10
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... Maybe `Human complexes with their participating protein molecules ` this one? ...
written 4 months ago by
SupBioInformatics • 10
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