... Have you looked at the pipeline suggested at IEDB: http://tools.iedb.org/main/bcell/modeling-docking/? The **Web servers for modeling 3D structure of antibody-protein complexes** seems to be what you need, or at least can serve as a starting point. ...
... I think the most straightforward way is the Volcano plot. Regarding the multiple testing, you can try to illustrate the fact that there are no significant differences by plotting the distribution of P-values and computing the false discovery rate (e.g. with this [package](https://cran.r-project.org/ ...
... Here you go:
df <- data.frame(cond_1=c('a', 'b', NA),
cond_2=c('a', 'b', 'c'),
cond_3=c('b', 'c', 'd'),
cond_4=c('e', 'f', 'g'))
df <- subset(dcast(melt(df, id.vars = c()), value~variable), !is.n ...
... Here are a couple of reasons:
1. Ask yourself if you want this forum to turn in a sort of stackoverflow. Count the number of downvotes you'll get for this post from SO perspective, assuming this question was already asked and core users are too conservative to change the voting system.
2. We work ...
... This is a productive sequence, just load it to IgBlast and see for yourself:
![enter image description here]
' TRBV14 is productive and in frame with J
I think the situation can probably be explained as follows: the mapping software checks for conserved ``FGXG`` motif of Joining segment to ens ...
... Software for T/B-cell receptor repertoire analysis using non-amplicon samples:
1. [TraCeR](https://github.com/Teichlab/tracer) T-cell receptors, single-cell RNA-Seq
2. [VDjer](https://github.com/mozack/vdjer) B-cell receptors, RNA-Seq
P.S. Check out [T cell fate and clonality inference from sing ...