Moderator: Charles Warden
Charles Warden ♦ 4.8k
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I am a Bioinformatics Specialist at City of Hope, where I work in the Integrative Genomics Core doing microarray and high-throughput sequencing analysis.
Posts by Charles Warden
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... Lowering the delta-beta cutoff will only help if the methylated thresholds are also changed. You could try setting both methyl.cutoff and unmethyl.cutoff equal to 0.3, or disable the use of methylated thresholds by setting unmethyl.cutoff=1 and methyl.cutoff=0.
Yes - in terms of posting etiquette, ...
written 15 days ago by
Charles Warden ♦ 4.8k
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... In most cases, it is difficult to confidently resolve classifications for 16S data at the species or sub-species level. So, if you were specifically interested in types of *Staphylococcus aureus*, it might be best to use a different marker (which you could define from comparing whole genome sequenc ...
written 25 days ago by
Charles Warden ♦ 4.8k
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... While I haven't directly used assemblage, I've done some testing with [MAKER][1], where I tended to get better results if I used protein / EST sequences (or an RNA-Seq *de novo* assembly) rather than starting with *de novo* gene predictions. Since it looks like assemblage is a modification of the M ...
written 6 weeks ago by
Charles Warden ♦ 4.8k
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... The R code that you are supposed to run is within the Word / PDF files, which call the other files under "R Tutorials"
At the beginning of the extracted R code, you'll need to define `dat0` as the beta matrix (such as `dat0 = read.table("probe_beta.txt",head=T, sep="\t")`)
Also, at least with the ...
written 7 weeks ago by
Charles Warden ♦ 4.8k
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Comment:
C: differential exon usage
... [DEXSeq][1] uses a specialized scripts (**dexseq_prepare_annotation.py** and **dexseq_count.py**) to run HTSeq for exon counts. The manual mentions that you can use other read counting programs, but I would typically use those specifically designed for DEXSeq (using a GTF annotation file).
Juncti ...
written 7 weeks ago by
Charles Warden ♦ 4.8k
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Answer:
A: differential exon usage
... If you are looking at differential exon usage (for patient characteristics, tumor-normal, etc.), DEXSeq is a popular option.
I happen to like [JunctionSeq][1] (which is based upon DEXSeq), which also includes splice sites (known junctions, and novel junctions between known exons) and an overall p-v ...
written 7 weeks ago by
Charles Warden ♦ 4.8k
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... Depends upon the library size - I believe the default setting is 3 cycles, and using 5 or 10 cycles is a little better if defining CCS reads. However, I typically don't see CCS reads greater than a few kb in length.
For genome assemblies, especially if you have 10+ kb segments of repetitive elemen ...
written 7 weeks ago by
Charles Warden ♦ 4.8k
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... The probe name indicates the methylation context, which can be either CpG or CpH (or a SNP probe with an rsID).
For example, ch.9.7776528F has hg19 coordinate chr9:7786528. The probe is for a CpH on the forward strand, so that position is a "C" and the next nucleotide is an "A" (H=A, C, or T).
In ...
written 3 months ago by
Charles Warden ♦ 4.8k
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... I would say it is OK to use CCS reads, where it might be a good idea to impose 5x or 10x cutoffs (the default is 3x).
I'm not as certain about error-corrected subreads if the library size is too large to define CCS reads. I guess it should be OK, but I can't really provide you with evidence from 1 ...
written 3 months ago by
Charles Warden ♦ 4.8k
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... If you are trying to find deferentially expressed regions that don't necessarily match annotated regions, I would recommend [derfinder][1]. It's pretty quick (at least compared to trying to perform a novel assembly with cufflinks), although I typically would at least start by focusing on annotatio ...
written 4 months ago by
Charles Warden ♦ 4.8k
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