Pakiet: rsem (1.3.3+dfsg-1)

[ Pakiet źródłowy: rsem  ]

RNA-Seq by Expectation-Maximization

RSEM is a software package for estimating gene and isoform expression levels from RNA-Seq data. The RSEM package provides an user-friendly interface, supports threads for parallel computation of the EM algorithm, single-end and paired-end read data, quality scores, variable-length reads and RSPD estimation. In addition, it provides posterior mean and 95% credibility interval estimates for expression levels. For visualization, It can generate BAM and Wiggle files in both transcript-coordinate and genomic-coordinate. Genomic-coordinate files can be visualized by both UCSC Genome browser and Broad Institute’s Integrative Genomics Viewer (IGV). Transcript-coordinate files can be visualized by IGV. RSEM also has its own scripts to generate transcript read depth plots in pdf format. The unique feature of RSEM is, the read depth plots can be stacked, with read depth contributed to unique reads shown in black and contributed to multi-reads shown in red. In addition, models learned from data can also be visualized. Last but not least, RSEM contains a simulator.

Inne pakiety związane z rsem

• dep: bowtie

  Ultrafast memory-efficient short read aligner

  lub bowtie2

  ultrafast memory-efficient short read aligner

• dep: libc6 (>= 2.15)

  Biblioteka GNU C: biblioteki współdzielone
  również pakiet wirtualny udostępniany przez libc6-udeb

• dep: libgcc-s1 (>= 3.0)

  Biblioteka wspomagająca GCC

• dep: libhts3 (>= 1.10)

  C library for high-throughput sequencing data formats

• dep: libstdc++6 (>= 9)

  Standardowa biblioteka GNU C++, wersja 3

• dep: perl

  praktyczny język ekstrakcji i raportowania Larry'ego Walla

• dep: python3

  interactive high-level object-oriented language (default python3 version)

• dep: r-base-core

  GNU R core of statistical computation and graphics system

• sug: hisat2

  graph-based alignment of short nucleotide reads to many genomes

• sug: r-bioc-ebseq

  R package for RNA-Seq Differential Expression Analysis

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