Papers: 10.1093/bioinformatics/btu638

https://doi.org/10.1093/bioinformatics/btu638

HTSeq—a Python framework to work with high-throughput sequencing data

Cited by: 14,991
Author(s): Simon Anders, Paul Theodor Pyl, Wolfgang Huber
Published: almost 12 years ago

Software Mentions 7

bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distribution
Papers that mentioned: 9,583
Very Likely Science (100)
bioconductor: edgeR
Empirical Analysis of Digital Gene Expression Data in R
Papers that mentioned: 6,568
Very Likely Science (100)
bioconductor: GenomicRanges
Representation and manipulation of genomic intervals
Papers that mentioned: 323
Very Likely Science (90)
bioconductor: Rsamtools
Binary alignment (BAM), FASTA, variant call (BCF), and tabix file import
Papers that mentioned: 138
Very Likely Science (90)
cran: SAM
Sparse Additive Modelling
Papers that mentioned: 4,566
Very Likely Science (85)
pypi: Cython
The Cython compiler for writing C extensions in the Python language.
Papers that mentioned: 118
Very Likely Science (100)
pypi: HTSeq
A framework to process and analyze data from high-throughput sequencing (HTS) assays
Papers that mentioned: 3,071
Very Likely Science (65)