User: Chirag Parsania
Chirag Parsania • 990
- Reputation:
- 990
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- Location:
- University of Macau
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- Google Scholar Page
- Last seen:
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- Joined:
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Posts by Chirag Parsania
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... I wonder what organisms will be covered in the project ? As of now I can see Canis familiaris, Danio rerio ,Drosophila, Human and Mouse for RNAseq data. Should I expect any update in the organism list in the future ? ...
written 20 hours ago by
Chirag Parsania • 990
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... easiest way is to calculate the stndard deviation for each gene across the samples in each cluster. Once you get SD value, rank each cluster by SD from high to low and then select top genes from each cluster. This will give you highly variable genes across the samples within each cluster and probabl ...
written 21 hours ago by
Chirag Parsania • 990
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... Here is the dplyr way. Make sure that you provide column names as given in `t1` and `t2`
library(tidyverse)
t1 <- tibble(X1 = c("a;b","c","d;e"))
t2 <- tibble(Y1 =letters[1:5] , Y2 = c("uuu","vvv","xxx","yyy","zzz") ,Y3 =c("uu","vv","xx","yy","zz"))
...
written 21 hours ago by
Chirag Parsania • 990
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... Hi Prakash, as of now I don't have any systematic way to do that. But I use crude way to decide number of K. For example, I check visually (using heatmap or lineplot shown above) if observations in particular cluster behaves similarly. If not, I keep on changing K value till I get convincing cluster ...
written 1 day ago by
Chirag Parsania • 990
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... Hi, First you can find the top genes which are highly variable across the conditions. One way to do this is calculate the standard deviation (SD) across the sample for each gene and then arrange from high to low using SD values. You can choose top 10% or 20% of the genes and later parform k-means on ...
written 1 day ago by
Chirag Parsania • 990
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... Hi, here is the solution using dplyr. In the script below, you need to set the path of tab delim .txt file at `file_path` variable. In the given files, columns should be variables and rows should be observations (E.g. genes). Each column and row must have unique identity given as first row and firs ...
written 1 day ago by
Chirag Parsania • 990
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... First you have to convert accession to NCBI tax id then you can get full lineage using following R function
#' Title
#'
#' @param ncbi_tax_ids : a vector of NCBI tax_ids
#' @param ncbi_tax_dir : directory having ncbi tax files
#'
#' @return : a tibble having tax_id plus al ...
written 10 weeks ago by
Chirag Parsania • 990
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... Hi Guangchuang,
Thanks for your reply. I didn't realise that `root` belongs `ape`. Anyway, I checked the documentation of `ape::root.` Infect after the [critical review][1] rerooting function of `ape` have been updated.
[1]: https://academic.oup.com/mbe/article/34/6/1535/3077051 ...
written 3 months ago by
Chirag Parsania • 990
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... Hi thanks for reply. I am trying to compare species tree vs gene tree. However, I have 100s of horizontally transferred (HT) genes an therefore it is not practical to make pair of species tree and gene tree for each of them and then compare with gene tree. To address this, I designed alternate anal ...
written 3 months ago by
Chirag Parsania • 990
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... Hi,
I am quite new to phylogenetic analysis. Please bare with me if question does not make sense.
I am using IQtree to analyse some horizontally transferred genes. I have successfully generated phylogenetic tree using IQtree. I have few questions related to interpretation of the trees given by ...
written 3 months ago by
Chirag Parsania • 990
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