Man page - rsem-generate-ngvector(1)

Packages contains this manual

Package:  rsem
apt-get install rsem

Manuals in package:
• rsem-gff3-to-gtf(1)
• rsem-run-ebseq(1)
• rsem-calculate-expression(1)
• convert-sam-for-rsem(1)
• rsem-simulate-reads(1)
• rsem-control-fdr(1)
• rsem-plot-transcript-wiggles(1)
• rsem-bam2wig(1)
• rsem-prepare-reference(1)
• rsem-generate-ngvector(1)
Documentations in package:
• rsem

Manual

RSEM-GENERATE-NGVECTOR

NAME
SYNOPSIS
ARGUMENTS
OPTIONS
DESCRIPTION
OUTPUT
EXAMPLES

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NAME

rsem-generate-ngvector - Create Ng vector for EBSeq based only on transcript sequences.

SYNOPSIS

rsem-generate-ngvector [options] input_fasta_file output_name

ARGUMENTS

input_fasta_file

The fasta file containing all reference transcripts. The transcripts must be in the same order as those in expression value files. Thus, ’reference_name.transcripts.fa’ generated by ’rsem-prepare-reference’ should be used.

output_name

The name of all output files. The Ng vector will be stored as ’output_name.ngvec’.

OPTIONS

-k <int>

k mer length. See description section. (Default: 25)

-h/--help

Show help information.

DESCRIPTION

This program generates the Ng vector required by EBSeq for isoform level differential expression analysis based on reference sequences only. EBSeq can take variance due to read mapping ambiguity into consideration by grouping isoforms with parent gene’s number of isoforms. However, for de novo assembled transcriptome, it is hard to obtain an accurate gene-isoform relationship. Instead, this program groups isoforms by using measures on read mappaing ambiguity directly. First, it calculates the ’unmappability’ of each transcript. The ’unmappability’ of a transcript is the ratio between the number of k mers with at least one perfect match to other transcripts and the total number of k mers of this transcript, where k is a parameter. Then, Ng vector is generated by applying Kmeans algorithm to the ’unmappability’ values with number of clusters set as 3. ’rsem-generate-ngvector’ will make sure the mean ’unmappability’ scores for clusters are in ascending order. All transcripts whose lengths are less than k are assigned to cluster 3.

If your reference is a de novo assembled transcript set, you should run ’rsem-generate-ngvector’ first. Then load the resulting ’output_name.ngvec’ into R. For example, you can use

NgVec <- scan(file="output_name.ngvec", what=0, sep="\n")

. After that, replace ’IsoNgTrun’ with ’NgVec’ in the second line of section 3.2.5 (Page 10) of EBSeq’s vignette:

IsoEBres=EBTest(Data=IsoMat, NgVector=NgVec, ...)

This program only needs to run once per RSEM reference.

OUTPUT

output_name.ump

’unmappability’ scores for each transcript. This file contains two columns. The first column is transcript name and the second column is ’unmappability’ score.

output_name.ngvec

Ng vector generated by this program.

EXAMPLES

Suppose the reference sequences file is ’/ref/mouse_125/mouse_125.transcripts.fa’ and we set the output_name as ’mouse_125’:

rsem-generate-ngvector /ref/mouse_125/mouse_125.transcripts.fa mouse_125

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