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Papers: 10.1186/s12859-021-04057-z

https://doi.org/10.1186/s12859-021-04057-z

Y-LineageTracker: a high-throughput analysis framework for Y-chromosomal next-generation sequencing data

Cited by: 21
Author(s): Hao Chen, Yan Lu, Dongsheng Lu, Shuhua Xu
Published: over 4 years ago

Software Mentions 13

cran: fasta
Fast Adaptive Shrinkage/Thresholding Algorithm
Papers that mentioned: 848
Very Likely Science (60)
pypi: ete3
A Python Environment for (phylogenetic) Tree Exploration
Papers that mentioned: 28
Very Likely Science (100)
pypi: fasta
The fasta python package enables you to deal with biological sequence files easily.
Papers that mentioned: 848
Very Likely Science (80)
pypi: hg
Frequent itemsets -- paired counts fp-tree
Papers that mentioned: 4
Very Likely Science (65)
pypi: LineageTracker
Papers that mentioned: 5
Unlikely Science (0)
pypi: matplotlib
Python plotting package
Papers that mentioned: 1,045
Very Likely Science (100)
pypi: networkx
Python package for creating and manipulating graphs and networks
Papers that mentioned: 110
Very Likely Science (100)
pypi: numpy
Fundamental package for array computing in Python
Papers that mentioned: 832
Very Likely Science (100)
pypi: pandas
Powerful data structures for data analysis, time series, and statistics
Papers that mentioned: 640
Very Likely Science (100)
pypi: pysam
Package for reading, manipulating, and writing genomic data
Papers that mentioned: 130
Very Likely Science (100)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)
pypi: scipy
Fundamental algorithms for scientific computing in Python
Papers that mentioned: 1,071
Very Likely Science (100)
pypi: Y-LineageTracker
Y-LineageTracker: A framework to fully analyze human Y-chromosome sequencing data
Papers that mentioned: 1
Very Likely Science (65)