count-normalize 0.1.1

K-mer Counts Merging and Normalization**

merge_normalized_isoform_count_TPM.py and merge_normalize_isoform_count_v1.py

This script is designed to further process the output of a previous k-mer counting script. Its purpose is to merge the k-mer count data into the original k-mer CSV files and to normalize these counts to account for differences in the total number of k-mers and read counts. This is a necessary step in many bioinformatics workflows, particularly those involving comparative genomics or quantitative assessment of sequence representation.

Features
Merges k-mer count data with the original k-mer list CSV files.
Normalizes k-mer frequencies using the total k-mer counts and read lengths.
Supports input from gzipped FASTQ files for read count determination.
Efficiently calculates normalization factors and processes large datasets.

Example usage: This script accepts command-line arguments to specify the input and output directories, the FASTQ file path, the read length, and the k-mer size. Here's how to run the script: For TPM

python ./scripts/merge_normalized_isoform_count_TPM.py --directory ./data/input --output_directory ./data/output --read_length 150 --k 50

For RPKM

python ./scripts/merge_merge_normalize_isoform_count_v1.py --directory ./data/input --output_directory ./data/output --read_length 150 --k 50

Command-Line Arguments --directory: The directory containing the *_kmers.csv and corresponding *_kmer_counts.csv files (required). This directory is same as the output directory from the last script (kmer_counting_loop.py). --output_directory: The directory where the merged and normalized CSV files will be saved (required). The output directory should be to a new directory for further GaussF workflow. --fastq: The path to the gzipped FASTQ file for which k-mer counts were computed (required). --read_length: The length of the reads in the FASTQ sequences, necessary for normalization (default is 150). --k: The length of the k-mers used during the counting process (default is 50). Output