User: inah
inah • 0
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Posts by inah
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... Hi,
I have total RNAseq data and one of my main goals is to map lncRNAs (long noncoding RNAs). I am using STAR for alignment and featureCounts for mapping (counting). For the lncRNAs, I think I need to use the annotation file gencode.v28.long_noncoding_RNAs.gtf.gz. I will pass this annotation fi ...
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... There is still something that must be going wrong with my analysis. I have compared the numbers of protein coding genes present (here meaning present in two samples with counts of at least 5) between mRNA-seq and total RNA-seq data. The mRNA-seg data had library sizes around 24 million, while the to ...
written 17 months ago by
inah • 0
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... Hi,
I have human total RNA-seq data (PE, Next-Seq) from a pilot study with two samples and am getting results from featureCounts that do not make any sense to me. I process the data as follows: (1) I perform adapter trimming using ea-utils mcf and mild quality trimming using btrim. I use STAR for ...
written 17 months ago by
inah • 0
• updated
17 months ago by
Gordon Smyth ♦ 39k
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... Hi,
I have been using featureCounts to obtain both exon- and gene-level read counts (reads were aligned with STAR). For one particular gene (ARID5B, which has 12 exons, 5 unique to one isoform, 2 unique to another isoform and 5 shared), I find that the read count summed over the 12 exons is greate ...
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... Hi,
I want to obtain read counts at the exon level using featureCounts. I run Rsubread and use these options:
annot.ext="/home/inah/RefGTF/GRCh38/annotation/Homo_sapiens.GRCh38.85.gtf",
isGTFAnnotationFile=TRUE,
GTF.featureType="exon", GTF.attrType="exon_id", useMetaFeatures=FALSE
The resulti ...
written 2.4 years ago by
inah • 0
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Popular Question
16 months ago,
created a question with more than 1,000 views.
For read count summed over exons is greater tham the gene-level read count using featureCounts
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