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User: MMa

gravatar for MMa
MMa • 240
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240
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3 months ago
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2 years, 4 months ago
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M**@mdanderson.org

Posts by MMa

<prev • 36 results • page 1 of 4 • next >
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Does a no-normal pipeline exist for MuSiC?
... Hi, We have a large set of tumor-only WES data that we want to run `music smg`. However, it's unclear from the documentations on whether: 1. Matched tumor-normal bam files are required for `music smg` *per se*, 1. Running `music bmr calc-bmr` is necessary before running `music smg`, and 1. I can u ...
music written 3 months ago by MMa • 240
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How likely do cDNAs with start-loss variants appear in mRNA-seq?
... I know that many transcripts having frameshift mutations will be degraded by nonsense- or readthrough-mediated degradation, subject to rules that are well-known. How how about start-loss? Most likely they won't be translated if they don't have an alternate start codon, but will they be degraded qui ...
rna-seq written 10 months ago by MMa • 240
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Comment: C: Strategies to call variants from a cancer sample
... Well, the somatic callers I used (MuTect, MuTect2, VarScan, MuSE) do not call somatic reversions, which I hope they could. That aside, using only default parameters and nothing else on a particular pair I'm currently working, MuTect gives less than 2,000 variants and MuSE gives less than 500. I'd b ...
written 10 months ago by MMa • 240
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Comment: C: Strategies to call variants from a cancer sample
... I understand this. The purpose of the variant calling in question, however, is not to study their biological significance. I plan to do some RNA-editing research, so I need to identify DNA-level variations to act blacklist positions. ...
written 10 months ago by MMa • 240
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Comment: C: Strategies to call variants from a cancer sample
... Hi @igor, the intention is to identify all variants regardless of source. ...
written 10 months ago by MMa • 240
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Strategies to call variants from a cancer sample
... Hi all, I am looking to identify DNA-level variations from a matched tumor-normal WES data. Specifically, I just want to know the variations in the tumor sample in relate to the *reference genome*, not the normal sample. I have noticed two possible approaches here: 1. Simply use a germline-varia ...
next-gen snp written 10 months ago by MMa • 240 • updated 10 months ago by d-cameron • 1.9k
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Comment: C: Mapping between genomic coordinates to transcriptomic coordinates
... Eventually I got to try out this one. The important `GenomicFeatures` function here is `mapToTranscripts`: library(GenomicFeatures) library(rtracklayer) gencodeTxDb <- makeTxDbFromGFF (file="gencode.annotation.gtf") gencodeTx <- transcripts (gencodeTxDb) names (gencodeTx) ...
written 11 months ago by MMa • 240
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Answer: A: ssGSEA on RNA-Seq data from TCGA
... I know this is an old thread, but SSGSEA can be calculated using the Bioconductor package GSVA. If you use RPKM, use `ssgsea <- gsva (RPKM, method="ssgsea", kcdf="Gaussian", ...)`; if you use raw counts, use `ssgsea <- gsva (counts, method="ssgsea", kcdf="Poisson", ...)` ...
written 11 months ago by MMa • 240
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Comment: C: How to get sequencing depths from VCF with Rsamtools
... The docs for the current versions of pindel states depth is the same I'd get from `samtools depth`. ...
written 15 months ago by MMa • 240
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How to get sequencing depths from VCF with Rsamtools
... I got from our collaborator some pindel output and the BAM files that is used as pindel input. Unfortunately, they used an older of version of pindel (before approximately 0.2.4u) that doesn't record total depth at breakpoint (i.e. the DP field in VCF). While our collaborator's standard practice is ...
R rsamtools pindel written 15 months ago by MMa • 240 • updated 15 months ago by Pierre Lindenbaum ♦ 113k

Latest awards to MMa

Student 10 months ago, asked a question with at least 3 up-votes. For Adding Coverage Stats into MuTect2 output VCFs
Teacher 14 months ago, created an answer with at least 3 up-votes. For A: Different results with edgeR when adding gene symbols
Teacher 17 months ago, created an answer with at least 3 up-votes. For A: Different results with edgeR when adding gene symbols
Scholar 17 months ago, created an answer that has been accepted. For C: I get the same modules but different number of genes WGCNA
Scholar 17 months ago, created an answer that has been accepted. For C: I get the same modules but different number of genes WGCNA
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