Local Run Manager Resequencing Analysis Module Workflow Guide (1000000002705 v00)

Local Run Manager Resequencing Analysis Module Workflow Guide (1000000002705 v00)
Local Run Manager
Resequencing Analysis Module
Workflow Guide
For Research Use Only. Not for use in diagnostic procedures.
Overview
Set Parameters
Analysis Methods
View Analysis Results
Analysis Report
Analysis Output Files
Custom Analysis Settings
Technical Assistance
ILLUMINA PROPRIETARY
Document # 1000000002705 v00
January 2016
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Overview
Overview
Intended for whole-genome sequencing of small genomes, the Local Run Manager
Resequencing analysis module aligns reads against the specified reference, and then
performs variant analysis.
Compatible Library Types
The Resequencing analysis module is compatible with specific library types represented
by library kit categories on the Create Run screen. For a current list of compatible library
kits, see the Local Run Manager support page on the Illumina website.
Input Requirements
In addition to sequencing data files generated during the sequencing run, such as base
call files, the Resequencing analysis module requires a reference genome.
A reference genome provides the chromosome and start coordinate in the alignment
output file. When setting up run and analysis parameters, specify the path to the
reference genome associated with each sample to be sequenced.
About This Guide
This guide provides instructions for setting up run parameters for sequencing and
analysis parameters for the Resequencing analysis module. For information about the
Local Run Manager dashboard and system settings, see the Local Run Manager Software
Guide (document # 1000000002702).
Local Run Manager Resequencing Analysis Module Workflow Guide
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Set Parameters
1
Click Create Run, and select Resequencing.
2
Enter a run name that identifies the run from sequencing through analysis.
Use alphanumeric characters, spaces, underscores, or dashes.
3
[Optional] Enter a run description to help identify the run.
Use alphanumeric characters.
Specify Run Settings
1
From the Library Kit drop-down list, select from the following library kit categories.
Library Kit
Nextera
Nextera XT
Nextera XT V2
Nextera Mate Pair
Read Type
Paired End or
Single Read
Number of Index Reads
Possible number of index reads is none,
1, or 2 reads of 8 cycles each.
Paired End only
TruSeq HT
Paired End or
Single Read
Paired End or
Single Read
Possible number of index reads is none
or 1 read of 6 cycles.
Possible number of index reads is none,
1, or 2 reads of 8 cycles each.
Possible number of index reads is none
or 1 read of 6 cycles.
TruSeq LT
2
Specify the number of index reads.
} 0 for a run with no indexing
} 1 for a single-indexed run
} 2 for a dual-indexed run
3
Specify a read type: Single Read or Paired End, if a change is possible.
4
Enter the number of cycles for the run.
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[Optional] Specify any custom primers to be used for the run.
Specify Module-Specific Settings
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1
Expand the Aligner drop-down list and select an alignment method.
} BWA-MEM—(Default) Optimized for Illumina sequencing data and reads ≥ 70 bp.
} BWA-Backtrack Legacy—Use with legacy data or reads < 70 bp.
2
Expand the Variant Caller drop-down list and select a variant calling method.
} Starling—(Default) Calls SNPs and small indels, and summarizes depth and
probabilities for every site in the genome.
} GATK—Calls raw variants for each sample, analyzes variants against known
variants, and then calculates a false discovery rate for each variant.
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Click the On/Off toggle to enable or disable the following analysis settings.
} Export gVCF—Off by default. When enabled, analysis includes gVCF files that
contain information about all sites within the region of interest.
} Flag PCR Duplicates—On by default. When enabled, PCR duplicates are flagged
in the BAM files and not used for variant calling. PCR duplicates are defined as 2
clusters from a paired-end run where both clusters have the exact same alignment
position for each read.
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Specify Samples for the Run
Specify samples for the run using the following options:
} Enter samples manually—Use the blank table on the Create Run screen.
} Import samples—Navigate to an external file in a comma-separated values (*.csv)
format. A template is available for download on the Create Run screen.
After you have populated the samples table, you can export the sample information to
an external file, and use the file as a reference when preparing libraries or import the file
for another run.
Enter Samples Manually
1
Adjust the samples table to an appropriate number of rows.
} Click the + icon to add a row.
} Use the up/down arrows to add multiple rows. Click the + icon.
} Click the x icon to delete a row.
} Right-click on a row in the table and use the commands in the drop-down menu.
2
Enter a unique sample ID in the Sample ID field.
Use alphanumeric characters, dashes, or underscores.
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[Optional] Enter a sample description in the Sample Description field.
Use alphanumeric characters, dashes, underscores, or spaces.
4
Expand the Index 1 (i7) drop-down list and select an Index 1 adapter.
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Expand the Index 2 (i5) drop-down list and select an Index 2 adapter.
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Expand the Genome Folder drop-down list and select a reference genome.
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[Optional] Click the Export
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When finished, click Save Run.
icon to export sample information in *.csv format.
Import Samples
1
Click Template. The template file contains the correct column headings for import.
2
Enter the sample information in each column for the samples in the run, and then
save the file.
3
Click Import Samples and browse to the location of the sample information file.
4
When finished, click Save Run.
Local Run Manager Resequencing Analysis Module Workflow Guide
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Set Parameters
} Indel Realignment—On by default. When enabled, regions containing indels are
locally realigned to minimize the number of mismatches.
Analysis Methods
The Resequencing analysis module performs the following analysis steps and then
writes analysis output files to the Alignment folder.
} Demultiplexes index reads
} Generates FASTQ files
} Aligns to a reference
} Identifies variants
Demultiplexing
Demultiplexing compares each Index Read sequence to the index sequences specified for
the run. No quality values are considered in this step.
Index reads are identified using the following steps:
} Samples are numbered starting from 1 based on the order they are listed for the run.
} Sample number 0 is reserved for clusters that were not assigned to a sample.
} Clusters are assigned to a sample when the index sequence matches exactly or when
there is up to a single mismatch per Index Read.
FASTQ File Generation
After demultiplexing, the software generates intermediate analysis files in the FASTQ
format, which is a text format used to represent sequences. FASTQ files contain reads for
each sample and the associated quality scores. Any controls used for the run and
clusters that did not pass filter are excluded.
Each FASTQ file contains reads for only 1 sample, and the name of that sample is
included in the FASTQ file name. FASTQ files are the primary input for alignment.
Adapter Trimming
The Resequencing analysis module performs adapter trimming by default.
During longer runs, clusters can sequence beyond the sample DNA and read bases from
a sequencing adapter. To prevent sequencing into the adapter, the adapter sequence is
trimmed before the sequence is written to the FASTQ file. Trimming the adapter sequence
avoids reporting false mismatches with the reference sequence and improves alignment
accuracy and performance.
Adapter Sequences
When using the Resequencing analysis module, the following adapter sequences are
trimmed depending on the selected library prep method:
} Nextera, Nextera XT, Nextera v2
CTGTCTCTTATACACATCT
} Nextera Mate Pair
CTGTCTCTTATACACATCT+AGATGTGTATAAGAGACAG
} TruSeq HT or TruSeq LT
} Read 1: AGATCGGAAGAGCACACGTCTGAACTCCAGTCA
} Read 2: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT
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During the alignment step, reads are aligned against the entire reference genome using
the Burrows-Wheeler Aligner (BWA), which aligns relatively short nucleotide sequences
against a long reference sequence. BWA automatically adjusts parameters based on read
lengths and error rates, and then estimates insert size distribution.
The Resequencing analysis module provides the option of using BWA-MEM or BWABacktrack Legacy for the alignment step.
BWA-MEM
BWA-MEM is the most recent version of the Burrows-Wheeler Alignment algorithm.
Optimized for longer read lengths of ≥ 70 bp, BWA-MEM has a significant positive
impact on detection of variants, especially insertions and deletions.
BWA-Backtrack
BWA-Backtrack is an earlier version of the Burrows-Wheeler Aligner algorithm that
aligns sequencing read lengths in < 70 bp segments. Use this version for very short
reads, or when consistency is required with previous study data.
Variant Calling
Variant calling records single nucleotide polymorphisms (SNPs), insertions/deletions
(indels), and other structural variants in a standardized variant call format (VCF).
For each SNP or indel called, the probability of an error is provided as a variant quality
score. Reads are realigned around candidate indels to improve the quality of the calls
and site coverage summaries.
The Resequencing analysis module provides the option of using Starling or GATK for
variant calling.
Starling
Starling calls both SNPs and small indels, and summarizes depth and probabilities for
every site in the genome. Starling produces a VCF file for each sample that contains
variants.
Starling treats each insertion or deletion as a single mismatch. Base calls with more than
2 mismatches to the reference sequence within 20 bases of the call are ignored. If the call
occurs within the first or last 20 bases of a read, the mismatch limit is increased to 41
bases.
GATK
The Genome Analysis Toolkit (GATK) calls raw variants for each sample, analyzes
variants against known variants, and then calculates a false discovery rate for each
variant. Variants are flagged as homozygous (1/1) or heterozygous (0/1) in the VCF file
sample column. For more information, see www.broadinstitute.org/gatk.
Local Run Manager Resequencing Analysis Module Workflow Guide
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Analysis Methods
Alignment
View Analysis Results
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From the Local Run Manager dashboard, click the run name.
2
From the Run Overview tab, review the sequencing run metrics.
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[Optional] Click the Copy to Clipboard
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Click the Sequencing Information tab to review run parameters and consumables
information.
5
Click the Samples and Results tab to view the analysis report.
} If analysis was repeated, expand the Select Analysis drop-down and select the
appropriate analysis.
} From the left navigation bar, select a sample name to view the report for another
sample.
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[Optional] Click the Copy to Clipboard
icon for access to the output run folder.
icon for access to the Analysis folder.
Document # 1000000002705 v00
Analysis results are summarized on the Samples and Results tab. The report is also
available in a PDF file format for each sample and as an aggregate report in the Analysis
folder.
Sample Information
Table 1 Sample Information Table
Column Heading
Description
Sample ID
The sample ID provided when the run was created.
Sample Name
The sample name provided when the run was created.
Run Folder
The name of the run folder.
Total PF Reads
The total number of reads passing filter.
Percent Q30 Bases
The percentage of bases called with a quality score ≥ Q30.
Read Level Statistics
Table 2 Read Level Statistics Table
Column Heading
Description
Total Aligned Reads
The total number of reads that aligned to the reference for each
read (Read 1 and Read 2).
Percent Aligned Reads
The percentage of reads that aligned to the reference for each
read (Read 1 and Read 2).
Base Level Statistics
Table 3 Base Level Statistics Table
Column Heading
Description
Total Aligned Bases
The total number of bases that aligned to the reference for each
read (Read 1 and Read 2).
Percent Aligned Bases
The percentage of aligned bases averaged over cycles per read
(Read 1 and Read 2).
Mismatch Rate
The percentage of bases that did not align to the reference
averaged over cycles per read (Read 1 and Read 2).
Coverage Histogram
The coverage histogram shows the depth of sequencing coverage across the number of
bases covered. The depth of coverage is calculated by the number of bases aligned to a
given reference position averaged over all positions.
Local Run Manager Resequencing Analysis Module Workflow Guide
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Analysis Report
Analysis Report
Figure 1 Coverage Histogram (Example)
Small Variants Summary
Table 4 Small Variants Summary Table
Row Heading
Description
Total Passing
The total number of variants passing filter for single nucleotide
variations (SNVs), insertions, and deletions.
Percent Found in dbSNP
The percentage of variants called by the variant caller that are
also present in dbSNP.
Het/Hom Ratio
The ratio of the number of heterozygous SNPs and number of
homozygous SNPs detected for the sample.
Ts/Tv Ratio
The ratio of transitions and transversions in SNPs.
• Transitions are variants of the same nucleotide type
(pyrimidine to pyrimidine, C and T; or purine to purine, A
and G).
• Transversions are variants of a different nucleotide type
(pyrimidine to purine, or purine to pyrimidine).
Fragment Length Summary
The fragment length summary section lists the average length of the sequenced fragment
for the selected sample, the minimum fragment length, the maximum fragment length,
and the range of variability listed as standard deviation. To account for potential
outliers, the minimum and maximum are calculated from values within ~ 3 standard
deviations, excluding the lower and upper 0.15% of the data.
Duplicate Information
The duplicate information section lists the percentage of clusters for a paired-end
sequencing run that are considered to be PCR duplicates. PCR duplicates are defined as
2 clusters from a paired-end run where both clusters have the exact same alignment
positions for each read.
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The following analysis output files are generated for the Resequencing analysis module
and provide analysis results for alignment and variant calling. Analysis output files are
located in the Alignment folder.
File Name
Description
Demultiplexing (*.demux)
Intermediate files containing demultiplexing results.
FASTQ (*.fastq.gz)
Intermediate files containing quality scored base calls.
FASTQ files are the primary input for the alignment step.
Alignment files in the
BAM format (*.bam)
Contains aligned reads for a given sample.
Variant call files in the
VCF format (*.vcf)
Contains information about variants found at specific
positions in a reference genome.
Variant call files in the
genome VCF format
(*.genome.vcf)
Contains the genotype for each position, whether called
as a variant or called as a reference.
Demultiplexing File Format
The process of demultiplexing reads the index sequence attached to each cluster to
determine from which sample the cluster originated. The mapping between clusters and
sample number are written to 1 demultiplexing (*.demux) file for each tile of the flow
cell.
The demultiplexing file naming format is s_1_X.demux, where X is the tile number.
Demultiplexing files start with a header:
} Version (4 byte integer), currently 1
} Cluster count (4 byte integer)
The remainder of the file consists of sample numbers for each cluster from the tile.
When the demultiplexing step is complete, the software generates a demultiplexing file
named DemultiplexSummaryF1L1.txt.
} In the file name, F1 represents the flow cell number.
} In the file name, L1 represents the lane number.
} Demultiplexing results in a table with 1 row per tile and 1 column per sample,
including sample 0.
} The most commonly occurring sequences in index reads.
FASTQ File Format
FASTQ file is a text-based file format that contains base calls and quality values per read.
Each record contains 4 lines:
} The identifier
} The sequence
} A plus sign (+)
} The quality scores in an ASCII encoded format
The identifier is formatted as:
Local Run Manager Resequencing Analysis Module Workflow Guide
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Analysis Output Files
Analysis Output Files
@Instrument:RunID:FlowCellID:Lane:Tile:X:Y ReadNum:FilterFlag:0:SampleNumber
Example:
@SIM:1:FCX:1:15:6329:1045 1:N:0:2
TCGCACTCAACGCCCTGCATATGACAAGACAGAATC
+
<>;##=><9=AAAAAAAAAA9#:<#<;<<<????#=
BAM File Format
A BAM file (*.bam) is the compressed binary version of a SAM file that is used to
represent aligned sequences up to 128 Mb. SAM and BAM formats are described in
detail at https://samtools.github.io/hts-specs/SAMv1.pdf.
BAM files use the file naming format of SampleName_S#.bam, where # is the sample
number determined by the order that samples are listed for the run.
BAM files contain a header section and an alignments section:
} Header—Contains information about the entire file, such as sample name, sample
length, and alignment method. Alignments in the alignments section are associated
with specific information in the header section.
} Alignments—Contains read name, read sequence, read quality, alignment
information, and custom tags. The read name includes the chromosome, start
coordinate, alignment quality, and the match descriptor string.
The alignments section includes the following information for each or read pair:
} RG: Read group, which indicates the number of reads for a specific sample.
} BC: Barcode tag, which indicates the demultiplexed sample ID associated with the
read.
} SM: Single-end alignment quality.
} AS: Paired-end alignment quality.
} NM: Edit distance tag, which records the Levenshtein distance between the read and
the reference.
} XN: Amplicon name tag, which records the amplicon tile ID associated with the
read.
BAM files are suitable for viewing with an external viewer such as IGV or the UCSC
Genome Browser.
BAM index files (*.bam.bai) provide an index of the corresponding BAM file.
VCF File Format
VCF is a widely used file format developed by the genomics scientific community that
contains information about variants found at specific positions in a reference genome.
VCF files use the file naming format SampleName_S#.vcf, where # is the sample number
determined by the order that samples are listed for the run.
VCF File Header—Includes the VCF file format version and the variant caller version.
The header lists the annotations used in the remainder of the file. If MARS is listed, the
Illumina internal annotation algorithm annotated the VCF file. The VCF header includes
the reference genome file and BAM file. The last line in the header contains the column
headings for the data lines.
VCF File Data Lines—Each data line contains information about a single variant.
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Analysis Output Files
VCF File Headings
Heading
Description
CHROM
The chromosome of the reference genome. Chromosomes appear in
the same order as the reference FASTA file.
POS
The single-base position of the variant in the reference chromosome.
For SNPs, this position is the reference base with the variant; for indels
or deletions, this position is the reference base immediately before the
variant.
ID
The rs number for the SNP obtained from dbSNP.txt, if applicable.
If there are multiple rs numbers at this location, the list is semicolon
delimited. If no dbSNP entry exists at this position, a missing value
marker ('.') is used.
REF
The reference genotype. For example, a deletion of a single T is
represented as reference TT and alternate T. An A to T single nucleotide
variant is represented as reference A and alternate T.
ALT
The alleles that differ from the reference read.
For example, an insertion of a single T is represented as reference A and
alternate AT. An A to T single nucleotide variant is represented as
reference A and alternate T.
QUAL
A Phred-scaled quality score assigned by the variant caller.
Higher scores indicate higher confidence in the variant and lower
probability of errors. For a quality score of Q, the estimated probability
of an error is 10-(Q/10). For example, the set of Q30 calls has a 0.1% error
rate. Many variant callers assign quality scores based on their statistical
models, which are high in relation to the error rate observed.
VCF File Annotations
Heading
Description
FILTER
If all filters are passed, PASS is written in the filter column.
• LowDP—Applied to sites with depth of coverage below a cutoff.
• LowGQ—The genotyping quality (GQ) is below a cutoff.
• LowQual—The variant quality (QUAL) is below a cutoff.
• LowVariantFreq—The variant frequency is less than the given
threshold.
• R8—For an indel, the number of adjacent repeats (1-base or 2-base)
in the reference is greater than 8.
• SB—The strand bias is more than the given threshold. Used with the
Somatic Variant Caller and GATK.
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Heading
Description
INFO
Possible entries in the INFO column include:
• AC—Allele count in genotypes for each ALT allele, in the same order
as listed.
• AF—Allele Frequency for each ALT allele, in the same order as listed.
• AN—The total number of alleles in called genotypes.
• CD—A flag indicating that the SNP occurs within the coding region
of at least 1 RefGene entry.
• DP—The depth (number of base calls aligned to a position and used
in variant calling).
• Exon—A comma-separated list of exon regions read from RefGene.
• FC—Functional Consequence.
• GI—A comma-separated list of gene IDs read from RefGene.
• QD—Variant Confidence/Quality by Depth.
• TI—A comma-separated list of transcript IDs read from RefGene.
FORMAT
The format column lists fields separated by colons. For example,
GT:GQ. The list of fields provided depends on the variant caller used.
Available fields include:
• AD—Entry of the form X,Y, where X is the number of reference calls,
and Y is the number of alternate calls.
• DP—Approximate read depth; reads with MQ=255 or with bad mates
are filtered.
• GQ—Genotype quality.
• GQX—Genotype quality. GQX is the minimum of the GQ value and
the QUAL column. In general, these values are similar; taking the
minimum makes GQX the more conservative measure of genotype
quality.
• GT—Genotype. 0 corresponds to the reference base, 1 corresponds
to the first entry in the ALT column, and so on. The forward slash (/)
indicates that no phasing information is available.
• NL—Noise level; an estimate of base calling noise at this position.
• PL—Normalized, Phred-scaled likelihoods for genotypes.
• SB—Strand bias at this position. Larger negative values indicate less
bias; values near 0 indicate more bias. Used with the Somatic Variant
Caller and GATK.
• VF—Variant frequency; the percentage of reads supporting the
alternate allele.
SAMPLE
The sample column gives the values specified in the FORMAT column.
Genome VCF Files
Genome VCF (gVCF) files are VCF v4.1 files that follow a set of conventions for
representing all sites within the genome in a reasonably compact format. The gVCF files
include all sites within the region of interest in a single file for each sample.
The gVCF file shows no-calls at positions with low coverage, or where a low-frequency
variant (< 3%) occurs often enough (> 1%) that the position cannot be called to the
reference. A genotype (GT) tag of ./. indicates a no-call.
For more information, see sites.google.com/site/gvcftools/home/about-gvcf.
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The following output files provide supplementary information, or summarize run results
and analysis errors. Although, these files are not required for assessing analysis results,
they can be used for troubleshooting purposes. All files are located in the Alignment
folder unless otherwise specified.
File Name
Description
AdapterTrimming.txt
Lists the number of trimmed bases and percentage of
bases for each tile. This file is present only if adapter
trimming was specified for the run.
AnalysisLog.txt
Processing log that describes every step that occurred
during analysis of the current run folder. This file does
not contain error messages.
Located in the root level of the run folder.
AnalysisError.txt
Processing log that lists any errors that occurred
during analysis. This file is present only if errors
occurred.
Located in the root level of the run folder.
CompletedJobInfo.xml
Written after analysis is complete, contains
information about the run, such as date, flow cell ID,
software version, and other parameters.
Located in the root level of the run folder.
DemultiplexSummaryF1L1.txt
Reports demultiplexing results in a table with 1 row
per tile and 1 column per sample.
ErrorsAndNoCallsByLaneTile
ReadCycle.csv
A comma-separated values file that contains the
percentage of errors and no-calls for each tile, read,
and cycle.
Mismatch.htm
Contains histograms of mismatches per cycle and nocalls per cycle for each tile.
ResequencingRunStatistics.xml
Contains summary statistics specific to the run.
Located in the root level of the run folder.
Summary.xml
Contains a summary of mismatch rates and other
base calling results.
Summary.htm
Contains a summary web page generated from
Summary.xml.
Analysis Folder
The analysis folder holds the files generated by the Local Run Manager software.
The relationship between the output folder and analysis folder is summarized as follows:
} During sequencing, Real-Time Analysis (RTA) populates the output folder with files
generated during image analysis, base calling, and quality scoring.
} RTA copies files to the analysis folder in real time. After RTA assigns a quality score
to each base for each cycle, the software writes the file RTAComplete.xml to both
folders.
} When the file RTAComplete.xml is present, analysis begins.
Local Run Manager Resequencing Analysis Module Workflow Guide
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Analysis Output Files
Supplementary Output Files
}
As analysis continues, Local Run Manager writes output files to the analysis folder,
and then copies the files back to the output folder.
Folder Structure
Data
Intensities
BaseCalls
Alignment—Contains *.bam and *.vcf files, and files specific to the
analysis module.
L001—Contains one subfolder per cycle, each containing *.bcl files.
Sample1_S1_L001_R1_001.fastq.gz
Sample2_S2_L001_R1_001.fastq.gz
Undetermined_S0_L001_R1_001.fastq.gz
L001—Contains *.locs files, 1 for each tile.
RTA Logs—Contains log files from RTA software analysis.
InterOp—Contains binary files used by Sequencing Analysis Viewer (SAV).
Logs—Contains log files describing steps performed during sequencing.
Queued—A working folder for software; also called the copy folder.
AnalysisError.txt
AnalysisLog.txt
CompletedJobInfo.xml
QueuedForAnalysis.txt
[WorkflowName]RunStatistics
RTAComplete.xml
RunInfo.xml
runParameters.xml
Alignment Folders
Each time that analysis is requeued, the Local Run Manager creates an Alignment folder
named AlignmentN, where N is a sequential number.
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Custom analysis settings are intended for technically advanced users. If settings are
applied incorrectly, serious problems can occur.
Add a Custom Analysis Setting
1
From the Module-Specific Settings section of the Create Run screen, click Show
advanced module settings.
2
Click Add custom setting.
3
In the custom setting field, enter the setting name as listed in the Available Analysis
Settings section.
4
In the setting value field, enter the setting value.
5
To remove a setting, click the x icon.
Available Analysis Settings
}
}
}
}
Adapter Trimming—By default, adapter trimming is enabled in the Resequencing
analysis module. To specify a different adapter, use the Adapter setting. The same
adapter sequence is trimmed for Read 1 and Read 2.
} To specify 2 adapter sequences, separate the sequences with a plus (+) sign.
} To specify a different adapter sequence for Read 2, use the AdapterRead2 setting.
Setting Name
Setting Value
Adapter
Enter the sequence of the adapter to be trimmed.
AdapterRead2
Enter the sequence of the adapter to be trimmed.
Quality Score Trim—The BWA alignment algorithm automatically trims the 3' ends
of non-indexed reads with low quality scores. By default, the value is set to 15.
Setting Name
Setting Value
QualityScoreTrim
Enter a value greater than 0.
Variant Frequency—Filters variants with a frequency less than the specified
threshold.
Setting Name
Setting Value
VariantFrequencyFilterCutoff
Enter a threshold value.
With GATK or Starling, the default value is 0.20.
Indel Repeat Cutoff—Filters insertions and deletions when the reference has a 1base or 2-base motif over 8 times (by default) next to the variant.
Local Run Manager Resequencing Analysis Module Workflow Guide
17
Custom Analysis Settings
Custom Analysis Settings
}
}
18
Setting Name
Setting Value
IndelRepeatFilterCutoff
Enter a threshold value.
The default value is 8.
Variant Genotyping Quality—Filters variants with a genotype quality (GQ) less than
the specified threshold.
Setting Name
Setting Value
VariantMinimumGQCutoff
Enter a value less than 99.
With GATK, the default value is 30.
With Starling, the default value is 20.
Variant Quality Cutoff—Filters variants with a quality (QUAL) less than the
specified threshold. QUAL indicates the confidence of the variant call.
Setting Name
Setting Value
VariantMiniumQualCutoff
Enter a threshold value.
With GATK, the default value is 30.
With Starling, the default value is 20.
Document # 1000000002705 v00
For technical assistance, contact Illumina Technical Support.
Table 5 Illumina General Contact Information
Website
Email
www.illumina.com
[email protected]
Table 6 Illumina Customer Support Telephone Numbers
Region
Contact Number
Region
North America
1.800.809.4566
Japan
Australia
1.800.775.688
Netherlands
Austria
0800.296575
New Zealand
Belgium
0800.81102
Norway
China
400.635.9898
Singapore
Denmark
80882346
Spain
Finland
0800.918363
Sweden
France
0800.911850
Switzerland
Germany
0800.180.8994
Taiwan
Hong Kong
800960230
United Kingdom
Ireland
1.800.812949
Other countries
Italy
800.874909
Contact Number
0800.111.5011
0800.0223859
0800.451.650
800.16836
1.800.579.2745
900.812168
020790181
0800.563118
00806651752
0800.917.0041
+44.1799.534000
Safety data sheets (SDSs)—Available on the Illumina website at
support.illumina.com/sds.html.
Product documentation—Available for download in PDF from the Illumina website. Go
to support.illumina.com, select a product, then select Documentation & Literature.
Local Run Manager Resequencing Analysis Module Workflow Guide
Technical Assistance
Technical Assistance
Illumina
5200 Illumina Way
San Diego, California 92122 U.S.A.
+1.800.809.ILMN (4566)
+1.858.202.4566 (outside North America)
[email protected]
www.illumina.com
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