EVzoom | Visually explore covariation in protein families | Genomics library

I'm using the software plink2 (https://www.cog-genomics.org/plink/2.0/) and I'm trying to iterate over 3 variables.

This software admits an input file with .ped extention file and an exclude file with .txt extention which contains a list of names to be excluded from the input file.

The idea is to iterate over the input files and then over exclude files to generate single outputfiles.

1. Input files: Highland.ped - Midland.ped - Lowland.ped
2. Exclude-map files: HighlandMidland.txt - HighlandLowland.txt - MidlandLowland.txt
3. Output files: HighlandMidland - HighlandLowland - MidlandHighland - MidlandLowland - LowlandHighland - LowlandMidland

The general code is:

From this example string:

I am making a code which takes in jumble word and returns a unjumbled word , the data.json contains a list and here take a word one-by-one and check if it contains all the characters of the word and later checking if the length is same , but the problem is when i enter a word as helol then the l is checked twice and giving me some other outputs including the main one(hello). i know why does it happen but i cant get a fix to it

I am trying to use plink1.9 to split multiallelic into biallelic. The input is that

I have a FASTA file that has about 300000 sequences but some of the sequences are like these

For example, I have two strings:

I am currently trying to run genomic analyses pipelines using Hail(library for genomics analyses written in python and Scala). Recently, Apache Spark 3 was released and it supported GPU usage.

I tried spark-rapids library start an on-premise slurm cluster with gpu nodes. I was able to initialise the cluster. However, when I tried running hail tasks, the executors keep getting killed.

On querying in Hail forum, I got the response that

That’s a GPU code generator for Spark-SQL, and Hail doesn’t use any Spark-SQL interfaces, only the RDD interfaces.

So, does Spark3 not support GPU usage for RDD interfaces?

I have 1500 files with the same format (the .scount file format from PLINK2 https://www.cog-genomics.org/plink/2.0/formats#scount), an example is below:

I have been implementing a suite of RecordBatchReaders for a genomics toolset. The standard unit of work is a RecordBatch. I ended up implementing a lot of my own compression and IO tools instead of using the existing utilities in the arrow cpp platform because I was confused about them. Are there any clear examples of using the existing compression and file IO utilities to simply get a file stream that inflates standard zlib data? Also, an object diagram for the cpp platform would be helpful in ramping up.