Moderator: igor

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igor7.1k
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Posts by igor

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Answer: A: Interpretation of TCGA clinical data
... I personally find that Xena is the easiest way to download TCGA-related data. All the datasets are aggregated in a basic table format with consistent sample names. For example, the Pan-Cancer data is here: https://xenabrowser.net/datapages/?cohort=TCGA%20Pan-Cancer%20(PANCAN)&removeHub=https%3 ...
written 2 days ago by igor7.1k
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Comment: C: RNA-strandness of single cell library prep methods
... If you are not sure, you can process RNA-seq data using both stand options. Based on the results, it should be obvious which is the correct strand (if stranded, usually over 90% of the reads are on one strand). See also this previous discussion: https://www.biostars.org/p/301252/ ...
written 5 days ago by igor7.1k
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Comment: C: GATK: -nct and -nt
... Looks like this was cross-posted here: https://gatkforums.broadinstitute.org/gatk/discussion/9283/understanding-nct-and-nt Where it was specified: > -nt / --num_threads controls the number of data threads sent to the processor > > -nct / --num_cpu_threads_per_data_thread controls the numbe ...
written 10 days ago by igor7.1k
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Comment: C: Why is my features different between featurecounts and cuffnorm?
... Yes, but many people run it even if they are not interested in them. For example, the original poster expects the output to match the original GFF file (known genes only). ...
written 13 days ago by igor7.1k
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Answer: A: Why is my features different between featurecounts and cuffnorm?
... In general, some of the tools you are using such as Tophat and Cufflinks have been replaced by newer alternatives. I would suggest you look into some previous discussions here, such as: - https://www.biostars.org/p/279420/ - https://www.biostars.org/p/351785/ Additionally: > The job is a who ...
written 16 days ago by igor7.1k
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Comment: C: Analyzing digital gene expression data (DGE) from drop-seq pipeline with Seurat.
... If you are not sure what a function does, you can check by putting a `?` in front of it. For example, `?system.file`. That will tell you that `system.file` takes "character vectors, specifying subdirectory and file(s) within some package". In the example, they are using `pbmc_raw.txt` from the Seura ...
written 18 days ago by igor7.1k
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Answer: A: Analyzing digital gene expression data (DGE) from drop-seq pipeline with Seurat.
... If you don't have 10x data, then you don't need to use `Read10X()`. This is a function to make reading 10x data easier since it's not stored as a simple CSV/TSV table. There is no need to try to recreate that format. In the same tutorial, you can skip to the next step, which is `CreateSeuratObject() ...
written 18 days ago by igor7.1k
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Comment: C: Detecting copy number alterations based on RNA-seq data
... Yet another option is [CaSpER][1]: > CaSpER is an algorithm for identification, visualization and > integrative analysis of CNV events in multiscale resolution using > single-cell or bulk RNA sequencing data. [1]: https://github.com/akdess/CaSpER ...
written 19 days ago by igor7.1k
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Comment: C: scRNA-seq, SEURAT, NormalizeData, ScaleData, PCA, CCA ...
... I guess I (and the Seurat tutorial) did not explicitly mention the primary objective. Yes, the scaling adjusts the range of expression values across all the genes, which will likely impact the downstream analysis far more than any additional regression. When I originally wrote the answer, I was thin ...
written 28 days ago by igor7.1k
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Comment: C: scRNA-seq, SEURAT, NormalizeData, ScaleData, PCA, CCA ...
... You go from raw to normalized to scaled. ...
written 29 days ago by igor7.1k

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Scholar 13 days ago, created an answer that has been accepted. For A: Pre-processing MiSeq Paired End data
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Teacher 28 days ago, created an answer with at least 3 up-votes. For A: GL000201,GL000202... etc What are these?
Scholar 28 days ago, created an answer that has been accepted. For A: Pre-processing MiSeq Paired End data
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