bioinformatics

I am working on a python project where I study RNA structure evolution (represented as a string for example: "(((...)))" where the parenthesis represent basepairs). The point being is that I have an ideal structure and a population that evolves towards the ideal structure. I have implemented everything however I would like to add a feature where I can get the "number of buckets" ie the k most representative structures in the population at each generation. I was thinking of using the k-means algorithm but I am not sure how to use it with strings. I found scipy.cluster.vq but I don't know how to

I have a command I want to run on all of the files of a folder, and the command's syntax looks like this: tophat -o <output_file> <input_file> What I would like to do is a script that loops over all the files in an arbitrary folder and also uses the input file names to create similar, but different, output file names. The file names looks like this: input name desired output name path/to/sample1.fastq path/to/sample1.bam path/to/sample2.fastq path/to/sample2.bam Getting the input to work seems simple enough: for f in *.fastq do tophat -o <output_file> $f done I tried using output=${f,.fastq,

This is my first post and I have to admit, I am terrible at programming. I am that guy in the class that works his tail off, but can never seem to grasp programming as well as the rest of my classmates. So please be nice, I will try to explain my problem below. I have the following code (comments removed), but when I run it I get a warning similar to the one listed below. Also, when I run the program, the first user inputted value is allowed, but then all of the sudden, it jumps to the end of the program, not allowing me to input the values for the other variables (e.g. the variable "beta"). I

I have a dataframe df1: df1 <- read.table(text=" Chr06 79641 Chr06 82862 Chr06 387314 Chr06 656098 Chr06 678491 Chr06 1018696", header=FALSE, stringsAsFactors=FALSE) I would like to check if each row in df1 is contained in a range in df2. the column2 in df2 is the start of a range, and column3 is the end of a range. no overlapping between ranges (between rows). The data in df2 are sorted by Column1 and column2. I wrote a loop for this but I am not happy to it because It runs so long time if I have a few thousands rows in df1. I would like to find a more efficient way to do this job (better no

I have an input_file.fa file like this ( FASTA format): > header1 description data data data >header2 description more data data data I want to read in the file one chunk at a time, so that each chunk contains one header and the corresponding data, e.g. block 1: > header1 description data data data Of course I could just read in the file like this and split: with open("1.fa") as f: for block in f.read().split(">"): pass But I want to avoid the reading the whole file into memory , because the files are often large. I can read in the file line by line of course: with open("input_file.fa") as f:

I just picked up Pandas to do with some data analysis work in my biology research. Turns out one of the proteins I'm analyzing is called 'NA'. I have a matrix with pairwise 'HA, M1, M2, NA, NP...' on the column headers, and the same as "row headers" (for the biologists who might read this, I'm working with influenza). When I import the data into Pandas directly from a CSV file, it reads the "row headers" as 'HA, M1, M2...' and then NA gets read as NaN. Is there any way to stop this? The column headers are fine - 'HA, M1, M2, NA, NP etc...' Turn off NaN detection this way: pd.read_csv(filename,