ARSDA: A New Approach for Storing, Transmitting and Analyzing Transcriptomic Data

G3 : Genes - Genomes - Genetics
Xuhua Xia

Abstract

Two major stumbling blocks exist in high-throughput sequencing (HTS) data analysis. The first is the sheer file size, typically in gigabytes when uncompressed, causing problems in storage, transmission, and analysis. However, these files do not need to be so large, and can be reduced without loss of information. Each HTS file, either in compressed .SRA or plain text .fastq format, contains numerous identical reads stored as separate entries. For example, among 44,603,541 forward reads in the SRR4011234.sra file (from a Bacillus subtilis transcriptomic study) deposited at NCBI's SRA database, one read has 497,027 identical copies. Instead of storing them as separate entries, one can and should store them as a single entry with the SeqID_NumCopy format (which I dub as FASTA+ format). The second is the proper allocation of reads that map equally well to paralogous genes. I illustrate in detail a new method for such allocation. I have developed ARSDA software that implement these new approaches. A number of HTS files for model species are in the process of being processed and deposited at http://coevol.rdc.uottawa.ca to demonstrate that this approach not only saves a huge amount of storage space and transmission bandwidth, but also...Continue Reading

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Datasets Mentioned

BETA
SRR1536586
GSM1465035

Methods Mentioned

BETA
RNA-Seq

Software Mentioned

DAMBE
NET
LFQC
Cufflinks
GZIP
QuickStart
file
Fastq
ARSDA
MAFFT

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