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Huber Group - Huber GroupHuber Group

Multi-omics and statistical computing The Huber group aims to understand inter-individual differences by large-scale statistical modelling and integrating multiple levels of genomic and molecular information from individuals with their phenotypic variation in health and disease. Contact Huber Group EMBL Heidelberg, … Continue reading →

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Huber Group - Huber GroupHuber Group | www-huber.embl.de Reviews

https://www-huber.embl.de

Multi-omics and statistical computing The Huber group aims to understand inter-individual differences by large-scale statistical modelling and integrating multiple levels of genomic and molecular information from individuals with their phenotypic variation in health and disease. Contact Huber Group EMBL Heidelberg, &hellip; Continue reading &rarr;

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Counting reads in features with htseq-count — HTSeq 0.6.1p2 documentation

http://www-huber.embl.de/users/anders/HTSeq/doc/count.html

HTSeq 0.6.1p2 documentation. Counting reads in features with. Given a file with aligned sequencing reads and a list of genomic features, a common task is to count how many reads map to each feature. A feature is here an interval (i.e., a range of positions) on a chromosome or a union of such intervals. Special care must be taken to decide how to deal with reads that overlap more than one feature. The. A tour through HTSeq. The three overlap resolution modes of. Work as follows. For each position. Contain...

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DESeq

http://www-huber.embl.de/users/anders/DESeq

DESeq is an R. Package to analyse count data from high-throughput sequencing assays such as RNA-Seq and test for differential expression. The package is available via Bioconductor. And can be conveniently installed as follows:. Start an R session and type. Source("http:/ www.bioconductor.org/biocLite.R") biocLite("DESeq"). The package home page of DESeq is here. For usage instructions, see the package vignette available from the package home page. 2010) R106, doi:10.1186/gb-2010-11-10-r106.

3

HTSeq: Analysing high-throughput sequencing data with Python — HTSeq 0.6.1p2 documentation

http://www-huber.embl.de/users/anders/HTSeq/doc/overview.html

HTSeq 0.6.1p2 documentation. HTSeq: Analysing high-throughput sequencing data with Python. HTSeq is a Python package that provides infrastructure to process data from high-throughput sequencing assays. Please see the chapter. A tour through HTSeq. First for an overview on the kind of analysis you can do with HTSeq and the design of the package, and then look at the reference documentation. Section in the overview below for what is available. For downloads and installation instructions, see. This chapter ...

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Huber Group - Huber GroupHuber Group

Skip to primary content. Multi-omics and statistical computing. The Huber group aims to understand inter-individual differences by large-scale statistical modelling and integrating multiple levels of genomic and molecular information from individuals with their phenotypic variation in health and disease. EMBL Heidelberg, Meyerhofstraße 1, 69117 Heidelberg, Germany. New paper: Single-cell transcriptome analysis reveals coordinated ectopic gene-expression patterns in medullary thymic epithelial cells.

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