Tag: plotMA

Cut AND Run , DiffBind Parameters

Forum:CHIPSEQ : Cut AND Run , DiffBind Parameters 0 Hello I have been using DiffBind to perform differential enrichment analysis on my ChIP-seq Cut and Run dataset where I have 2 sample groups, Control and YY1_overexpression, with 4 replicates in each sample group. (Peak Calling was done through SEACR) 8…

Continue Reading Cut AND Run , DiffBind Parameters

Comparing 3 Data Sets using DeSeq and Heatmaps

Hi all, I am new to bioinformatics analysis, so I’d appreciate if someone could check my code for the goal I am trying to achieve. I have 3 samples – Wild Type (WT) FoxP3-TCF-HEB (I have 3 replicates of this) TCFKO I have defined these in the sample information csv…

Continue Reading Comparing 3 Data Sets using DeSeq and Heatmaps

DESeq2 Normalization with 4 Groups

Hello All! I am running DESeq2 on my RNA Seq dataset. I have four groups in my treatment with 8 replicates and about 14,500 rows (genes) after using keep (removing low copy numbers) and removing NA. I also used level so that my Control is the reference. So I have…

Continue Reading DESeq2 Normalization with 4 Groups

Will DESeq2 be appropriate tool for analysis?

Will DESeq2 be appropriate tool for analysis? 0 @959b4cc0 Last seen 12 hours ago Sweden Hello! We are looking at extra cellular RNA which has been collected from cell culture media. We used UMIs to tag and sequence nucleotides which were present in the media, processed them with nf-core RNA-seq…

Continue Reading Will DESeq2 be appropriate tool for analysis?

low counts too many genes

DESEq2 results : low counts too many genes 1 My deseq2 results shows as follows : out of 55357 with nonzero total read count adjusted p-value < 0.1 LFC > 0 (up) : 0, 0% LFC < 0 (down) : 12, 0.022% outliers [1] : 0, 0% low counts [2]…

Continue Reading low counts too many genes

Solved In the pre-recorded video, your instructor described

Transcribed image text: In the pre-recorded video, your instructor described how DESEq2 log2 fold-change estimates are frequently over-estimated particularly for low expression genes. To obtain better estimates of the log2 fold-change, DESeq2 recommends “shrinking” the raw estimates in your output table above. DESeq2 makes available the lfcShrink function to extract…

Continue Reading Solved In the pre-recorded video, your instructor described

CRISPR-clear imaging of melanin-rich B16-derived solid tumors

B16 melanin(+) tdTomato cell line generation The generation and characterization of a lentivirus encoding tdTomato has been described previously22. The B16-D5-HER2 stable cell line was a generous gift from Louis Weiner (Georgetown University)13,23. Cell lines were cultured in DMEM Dulbecco’s modified Eagle’s medium (DMEM; Sigma) supplemented with 10% (v/v) fetal…

Continue Reading CRISPR-clear imaging of melanin-rich B16-derived solid tumors

Choosing the correct shrinkage type

Hi everyone, First time poster here – tried to look for the answer but I do not seem to find exactly what I am looking for. I have a question re log2FC shrinking as part of my DEse2 pipeline. I cannot understand which type of shrinkage I should be using….

Continue Reading Choosing the correct shrinkage type

R: MA-Plot

R: MA-Plot plotMA {limma} R Documentation MA-Plot Description Creates an MA-plot with color coding for control spots. Usage plotMA(MA, array=1, xlab=”A”, ylab=”M”, main=colnames(MA)[array], xlim=NULL, ylim=NULL, status, values, pch, col, cex, legend=TRUE, zero.weights=FALSE, …) Arguments MA an RGList, MAList or MArrayLM object, or any list with components M containing log-ratios and…

Continue Reading R: MA-Plot

Change log2FoldChange range – plotMA

You can use base R graphics to make these plots. The data is sitting there in columns of the res object, so you can filter it directly, and use boolean vectors to pick out the things you need: # make sure there are no NA values sum(is.na(res$log2FoldChange)) # choose some…

Continue Reading Change log2FoldChange range – plotMA

Diffbind3 dba.plotMA error

Hello, I am analyzing some ATAC-seq from flies using Diffbind3.0.8 and EdgeR. I initially ran dba.analyze() with the default peak size of 401 and was able to graph the results using dba.plotMA and dba.plotVolcano when my contrasts were evaluated using both EdgeR and DESEQ2. After resizing the peaks to 100…

Continue Reading Diffbind3 dba.plotMA error

weird MAplot or volcano plot of DESeq2 diff result

Hi, every one. I find a werid MAplot or volcano plot of DESeq reuslt. I am wondering whether you can give me some advice. This diff result is from two cell type bulk RNA-seq. I use two specific marker to get these two cell type using Flow cytometer. I alreadly…

Continue Reading weird MAplot or volcano plot of DESeq2 diff result