User: sckinta

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sckinta480
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Posts by sckinta

<prev • 59 results • page 1 of 6 • next >
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Comment: C: comparing ATAC-seq/ChIP-seq peaks
... In terms of BAMPE/BEDPE option (which is very smart!), I currently have tagAlign file (basically a bed file). Every two lines present a pair of read mapping. I can convert that to BEDPE by defining the chromosome name, most left and right position of pair reads as fragment coordinate. Is that valid? ...
written 6 weeks ago by sckinta480
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Comment: C: comparing ATAC-seq/ChIP-seq peaks
... I agree with you that libraries are undersequenced. Thus I am thinking to merge reads from all biological replicates together then call peaks. For some cells I have large replicate sizes (which are not shown here). I am worried about read length, since I have experienced read-length-bias on quantit ...
written 6 weeks ago by sckinta480
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Comment: C: comparing ATAC-seq/ChIP-seq peaks
... Thank you for reply. Yes, to do the comparison, I have to merge peaks anyway. For the option 1), since the cells are very different from each other, pooling reads from all samples may cancel out the noise and true signal between samples. So I choose to call peaks at different cell types by pooling r ...
written 6 weeks ago by sckinta480
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comparing ATAC-seq/ChIP-seq peaks
... We want to do a meta-analysis on previously analyzed ATAC-seq data from different cell types. It has been noticed that those ATAC-seq libraries are sequenced at different batches (some libraries are 100bp PE while some are 50 bp PE). The library sizes of dedup read are varied a lot too. cell t ...
chip-seq atac-seq written 6 weeks ago by sckinta480 • updated 6 weeks ago by ATpoint13k
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RNA-seq unbalanced batch effect correction
... Hi i have a set of RNAseq data with unbalanced batch effect (see table below). Batch 1 was made of single indexed kit and sequenced at time 1, while batch 2 was made of dual indexed kit and sequenced independently from batch 1. sample batch groups 1 Naive_Dmt3aKO_rep1 2 Naive_Dmt3aKO ...
R rna-seq edger batch effect written 5 months ago by sckinta480 • updated 5 months ago by Devon Ryan88k
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Comment: C: Batch effects : ComBat or removebatcheffects (limma package) ?
... Thank you for the tips. I have one more detail question though. According to the clustering and heatmap before batch removal, I have notice batch 1 and 3 are clustered within each group, while all batch 2 samples are clustered together regardless group. In reality, all batch are prepared independent ...
written 6 months ago by sckinta480
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Comment: C: Batch effects : ComBat or removebatcheffects (limma package) ?
... Thank your for sharing this. I am trying to explain your idea in R code using edgeR package. Could you check whether it is right? group <- factor(c("mut","mut","mut","wt","wt","wt")) group <- relevel(group,ref="wt") seq_batch <- factor(c(1,2,3,1,2,3)) design <- model.m ...
written 6 months ago by sckinta480
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Comment: C: RNA-seq replicates not clustering
... Well, only three samples, I cannot say correlation. I do observe outliers have relatively more read count. Here are read count per sample Th2KO_ev_rep1 7,616,704 Th2KO_ev_rep2 3,455,495 Th2KO_ev_rep3 2,867,725 Th2KO_mut_rep1 9,538,351 Th2KO_mut_rep2 5,271,933 Th2KO_mut_rep3 ...
written 6 months ago by sckinta480
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Comment: C: RNA-seq replicates not clustering
... It is just a name. I called vsn as vsnCPM. The plots were made from vsn output. VSN is variance stabilizing method, which is what rlog was trying to do. but rlog is less sensitive to sample size ...
written 6 months ago by sckinta480
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Comment: C: RNA-seq replicates not clustering
... I did remove low exp genes before normalization. Actually I tried to PCA top 50% genes, the results are very similar. I have very low depth on samples. After mapping and filtering, I have only 2M ~ 9M (3M on average) reads left per sample. When I was doing the low exp genes, I just made sure top 3 s ...
written 6 months ago by sckinta480

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