454测序系统软件手册：数据格式与操作指南

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454 manual 是一份针对454测序系统的详细文档，专为生命科学研究设计，而非用于诊断程序。这份文档涵盖了GS Junior、GS FLX+、GS FLX+/XLR70 和 GS FLX/XLR70 等不同仪器的软件操作指南，重点阐述了2.6版本的软件系统，包括数据获取、处理和分析流程。在概述部分（1.1），文档介绍了454测序系统的整体架构，强调了数据采集的过程，即从实验样本到生成原始数据的步骤。数据处理（1.2）提供了两种选项：对于GS FLX+系统，用户可以利用其内置的处理能力；而对于GS Junior系统，则需要通过GS Run Processor进行后续步骤。数据输出和文件夹结构（1.3）详述了运行结果的组织方式，如运行文件夹（包含原始测序数据）、数据处理文件夹（存储经过初步处理的数据）以及数据分析应用产生的结果。 2. 数据文件和格式部分（2.1和2.2）至关重要，它指导用户如何准备和管理输入数据。目录命名规范（2.1）确保了文件的一致性和可识别性，这对于有效组织和追踪大量数据至关重要。对于输入文件，包括FASTA和FASTQ格式，有具体的要求（2.2.1和2.2.2）。FASTA文件格式通常用于存储DNA或蛋白质序列信息，而FASTQ则包含了质量信息，是测序数据的标准输出格式。在实际操作中，用户需要遵循这些指导，理解不同仪器的特性，正确配置文件格式，以便从454测序系统中获得高质量的科研数据。此外，安全措施（如系统保护）和获取帮助（如联系客户服务）也在这份手册中有所提及，确保用户在使用过程中能够得到适当的支持。这份454 Sequencing System Software Manual 提供了深入的技术细节，不仅包括软件的安装和配置，还涵盖了从数据获取到分析的整个工作流程，对从事454测序研究的专业人员来说，是一份不可或缺的参考资料。

454 Sequencing System Software Manual

General Overview and Data File Formats

454 Sequencing System Software Manual, May 2011 9

 With the GS Junior System, all data acquisition and data processing can be handled by the

Attendant PC, as part of the sequencing Run.

 With the GS FLX+ System, the computationally-intensive image and signal processing may be

configured to take place on an external DataRig.

The data analysis phase offers a choice of several downstream analysis paths to generate the desired final output: a

consensus sequence of the DNA sample generated by the assembly of reads into contigs and scaffolds (GS De Novo

Assembler); a consensus sequence along with a list of high-confidence differences obtained by mapping the reads to

a known reference sequence (GS Reference Mapper); or the identification and quantitation of sequence variants by

the ultra deep sequencing of amplicons (GS Amplicon Variant Analyzer). All data analysis outputs also include base-

per-base quality scores (Phred-equivalent) and other specific metric files.

The data analysis steps are as follows:

1. The GS De Novo Assembler application generates a consensus sequence of the whole DNA sample, by assembling the

reads into contigs (de novo shotgun assembly). An option allows the use of one or more sequencing Runs performed

on a Paired End library (any type, or even a combination of Paired End library types) prepared from the same DNA

sample, to be analyzed together with Shotgun sequencing Run(s) and help order and orient the resulting contigs into

scaffolds. (Paired End reads do not necessarily need to be analyzed together with Shotgun reads.)

2. The GS Reference Mapper application generates the consensus DNA sequence by mapping, or aligning, the reads to a

reference sequence; as well as a list of high-confidence differences (individual bases or blocks of bases that differ

between the consensus DNA sequence of the sample and the reference sequence). Robust cDNA analysis is also

available.

3. The GS Amplicon Variant Analyzer application compares reads from an Amplicon library to corresponding reference

sequences, and allows the user to detect, identify and quantitate the prevalence of sequence variants.

The data analysis applications use the fully processed and “trimmed” read basecalls of a sequencing Run, or of a pool

of Runs, to produce initial alignments to the reference sequence (or read-to-read overlaps for the GS De Novo

Assembler). They then use a combination of nucleotide and flowgram information for consensus-calling of the

contigs and determination of quality values for the contig sequences. Contig consensus-calling is carried out in

“flowspace” (i.e. it operates directly on the processed signals measured from the wells), followed by basecalling to

produce a consensus sequence for the sample. Table 2 lists the specific outputs of the 3 data analysis applications as

well as the individual functions carried out by each one.

The final output of the 454 Sequencing System thus varies depending on what kind of analysis is performed:

Assembly, Mapping or Amplicon Variant Analysis (or no analysis of any kind). In all cases, however, the output

DNA sequence is supplied as a set of FASTA files, with associated “Quality Scores” and other Run and data metrics

files useful for troubleshooting and determining the overall quality of the sequencing Run. ACE-formatted files are

also produced by each of the data analysis applications to allow users to view alignment results using third-party

software tools.

454 Sequencing System Software Manual

General Overview and Data File Formats

454 Sequencing System Software Manual, May 2011 10

Application

Input

Output

Main processing steps

GS De Novo

Assembler

SFF files, from

one or multiple

sequencing

Runs,

containing read

flowgrams and

basecalls, and

per-base

quality scores

Sample

consensus

sequence,

assembled de

novo (and

scaffold

information,

with Paired End

option)

Identify pairwise overlaps between reads, in nucleotide space

Construct multiple alignments of reads that tile together (i.e.

form contigs), based on the pairwise overlaps

Generate consensus basecalls of the contigs by averaging the

processed flow signals for each nucleotide flow included in the

alignment, in flowspace

Output the contig consensus sequences and corresponding

quality scores, along with an ACE file of the multiple alignments

and assembly metrics files

Additional steps with Paired End option:

Identify pairwise overlaps between Paired End tags and the

shotgun contigs

Organize the contigs into scaffolds (order, orientation, and

approximate distance)

Output the scaffolded consensus sequences and

corresponding quality scores, along with an AGP file of the

scaffolds and specific metrics Tables

GS Reference

Mapper

Sample

consensus

sequence,

mapped to a

reference

sequence; and

list of

differences

For each read, search for alignment(s) to the reference

sequence, in nucleotide space

Construct contigs and compute a consensus basecall sequence

from the signals of the aligned reads (flowspace)

Identify the positions where the consensus or subsets of the

reads that comprise it differ from the reference sequence (or

reads from one another); these are the “putative differences”

Evaluate the putative differences to identify high-confidence

differences

Output contig consensus sequence(s) and corresponding

quality scores, an ACE file of the multiple alignments of the

reads and contigs to the reference, the list of identified

differences, and mapping metrics files

GS Amplicon

Variant

Analyzer

Identity and

quantitation of

sequence

variants

Trim reads (remove primer sequences)

Assign reads to “Samples” (demultiplex data sets)

Align Sample reads to their reference sequences

Quantitate variant frequency for each Sample

Table 2: The 3 applications of the data analysis phase of the 454 Sequencing System, with their inputs, outputs, and main

processing steps. Note that all data analysis applications use as input the reads and flowgrams output in SFF format by the

data processing (GS Run Processor application). For a full description of the various data analysis applications, see Parts C

and D in this manual.

The software package described in this manual also includes a variety of applications that are used primarily

or exclusively off-instrument (on a DataRig or GS Junior Attendant PC). The GS Reporter and the GS Run

Browser applications are used to view and troubleshoot the results of a completed sequencing Run; the GS

Support Tool is used to package sequencing Run data to send to Roche Customer Support for further help

and troubleshooting; and the SFF Tools are a set of commands used to create, manipulate and access

sequencing trace data from SFF files. However, these applications and commands are not required steps of

data processing and analysis.

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