Bcl2fastq2 Conversion Software V2.19 User Guide 15051736 V2

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bcl2fastq2 Conversion v2.19
User Guide

Introduction
Install bcl2fastq2 Conversion Software
BCL Conversion Input Files
Sample Sheet
Run BCL Conversion and Demultiplexing
BCL Conversion Output Files
Troubleshooting
Appendix: Installation Requirements
Revision History
Technical Assistance

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ILLUMINA PROPRIETARY

bcl2fastq2 Conversion Software v2.19 Guide

This document and its contents are proprietary to Illumina, Inc. and its affiliates ("Illumina"), and are intended solely for the
contractual use of its customer in connection with the use of the product(s) described herein and for no other purpose. This
document and its contents shall not be used or distributed for any other purpose and/or otherwise communicated, disclosed, or
reproduced in any way whatsoever without the prior written consent of Illumina. Illumina does not convey any license under its
patent, trademark, copyright, or common-law rights nor similar rights of any third parties by this document.
The instructions in this document must be strictly and explicitly followed by qualified and properly trained personnel in order to
ensure the proper and safe use of the product(s) described herein. All of the contents of this document must be fully read and
understood prior to using such product(s).
FAILURE TO COMPLETELY READ AND EXPLICITLY FOLLOW ALL OF THE INSTRUCTIONS CONTAINED HEREIN MAY RESULT
IN DAMAGE TO THE PRODUCT(S), INJURY TO PERSONS, INCLUDING TO USERS OR OTHERS, AND DAMAGE TO OTHER
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ILLUMINA DOES NOT ASSUME ANY LIABILITY ARISING OUT OF THE IMPROPER USE OF THE PRODUCT(S) DESCRIBED
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© 2017 Illumina, Inc. All rights reserved.
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and/or other countries. All other names, logos, and other trademarks are the property of their respective owners.

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Introduction
The Illumina sequencing instruments generate per-cycle base call (BCL) files at the end of the sequencing run. A
majority of analysis applications use per-read FASTQ files as input for analysis. You can use the bcl2fastq2 Conversion
Software v2.19 to convert base call (BCL) files from a sequencing run into FASTQ files.
Use this guide to install the bcl2fastq2 Conversion Software and run the BCL conversion and demultiplexing process.

Supported Instruments
The bcl2fastq2 Conversion Software supports the following instruments:
u

MiniSeq

u

MiSeq

u

NextSeq 500, 550

u

HiSeq X

u

HiSeq 2000, 2500, 3000, 4000

u

NovaSeq 5000, 6000

If your Illumina sequencing system runs an earlier software version of Real-Time Analysis (RTA) than v1.18.54 and you
want to convert BCL to FASTQ, install bcl2fastq v1.8.4, and refer to the bcl2fastq Conversion User Guide Version
v1.8.4 (part # 15038058) for instructions.

BCL Conversion and Demultiplexing Directory
The bcl2fastq2 Conversion Software performs BCL conversion and demultiplexing in a single step. By default, the
software puts the resulting demultiplexed compressed FASTQ files in /Data/Intensities/BaseCalls.
The software puts reads with undetermined indexes in files that begin with Undetermined_S0_. If unindexed
samples are included in a lane with indexed information, the software exits with an error (missing a barcode).
If the Sample_Project column is specified for a sample in the sample sheet, the FASTQ files for that sample are placed
in /Data/Intensities/BaseCalls/.
Multiple samples can use the same project directory. If the Sample_ID and Sample_Name columns are specified but
do not match, the FASTQ files are placed in an additional sub-directory called  with files named using
the Sample_Name value.

BCL to FASTQ Conversion Process
The bcl2fastq2 Conversion Software converts the base calls in the per-cycle BCL files to the per-read FASTQ format.
As an option, the software can trim adapters and remove Unique Molecular Identifier (UMI) bases from reads.
Adapter Trimming—The bcl2fastq2 Conversion Software checks whether a read extends past the sample DNA
insert and into the adapter sequence. The software uses an approximate string matching algorithm to identify all or
part of the adapter, and treats the insertions and deletions as a single mismatch. If an adapter sequence is detected,
base calls matching the adapter and beyond the match are masked or removed in the FASTQ file.
Unique Molecular Indentifiers (UMIs) Removal—UMIs are random k-mers attached to the genomic DNA before
polymerase chain reaction (PCR) amplification. After the UMI is amplified with amplicons, the software can retrieve
these bases and place them into the read name in the FASTQ files. Also, when the TrimUMI sample sheet setting is
active, the software can remove the bases from the reads.

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Demultiplexing—First, the software reorganizes the FASTQ files based on the index sequencing information. For best
practices, avoid choosing indexes that differ by fewer than 3 bases during sample preparation. After generating the
FASTQ files, the software generates the statistics and reports for the demultiplexed FASTQ files. The software also
recalculates the base calling analysis statistics and store the statistics in the InterOp folder. You can view the statistics
with the Sequencing Analysis Viewer (SAV) software from Illumina.
Output Files
u

FASTQ Files

u

InterOp Files

u

ConversionStats File

u

DemultiplexingStats File

u

Adapter Trimming File

u

FastqSummary and DemuxSummary

u

HTML Reports

u

JSON File

Install bcl2fastq2 Conversion Software
You can download the bcl2fastq2 Conversion Software from the Downloads page on the Illumina website.
For installation requirements, see Appendix: Installation Requirements on page 26.

Install from RPM Package
You need to have access the root system to install.
1

To install the RPM file, use the following command line:
yum install -y 

The starting point for the bcl2fastq converter is the binary executable /usr/local/bin/bcl2fastq.
2

To install the RPM package in a user specified location, use the following command line:
rpm --install --prefix 


Install from Source
For installation, the directory locations are specified with the following environment variables:
Variables

Description

SOURCE

Location of the bcl2fastq2 source code

BUILD

Location of the build directory

INSTALL_DIR

Location where the executable is installed

For example, the environment variables can be set as:
export TMP=/tmp
export SOURCE=${TMP}/bcl2fastq
export BUILD=${TMP}/bcl2fastq2-v2.19.x-build
export INSTALL_DIR=/usr/local/bcl2fastq2-v2.19.x
The build directory must be different from the source directory.

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Follow these steps to install from source:
1

Decompress and extract the source code.
cd ${TMP}
tar -xvzf bcl2fastq2-v2.19.x.tar.gz
This command populates the directory ${TMP}/bcl2fastq.

2

Configure the build using the following commands:
mkdir ${BUILD}
cd ${BUILD}
chmod ugo+x ${SOURCE}/src/configure
chmod ugo+x ${SOURCE}/src/cmake/bootstrap/installCmake.sh
${SOURCE}/src/configure --prefix=${INSTALL_DIR}
The first two commands create a build directory to work from. The next two lines ensure necessary files can be
executed. Executing the final configure command populates the ${BUILD} directory with that necessary files
needed to build bcl2fastq2 in step 3 . The --prefix parameter provides the absolute path to the installation
directory. Make sure you have write permission to the ${INSTALL_DIR} directory. The ${BUILD} directory will be
created.

3

Build and install the package using the following commands:
cd ${BUILD}
make
make install
Depending on the ${INSTALL_DIR} directory, you may need root privilege.

BCL Conversion Input Files
After sequencing, the instruments generate a BaseCalls directory, which contains the base calls files (BCL), for
demultiplexing.
For demultiplexing, the bcl2fastq2 Conversion Software requires the following input files:
Instrument

Input Files

MiSeq and HiSeq 2000/2500

•
•
•
•
•
•
•

BCL Files (*.bcl.gz)
STATS Files
FILTER Files
Position Files
RunInfo Files
Config Files
Sample Sheet Files (optional)

MiniSeq and NextSeq 500/550

•
•
•
•
•
•

BCL Files (*bcl.bgzf)
BCI Files
FILTER Files
Position Files
RunInfo Files
Sample Sheet Files (optional)

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Instrument

Input Files

HiSeq X and HiSeq 3000/4000

•
•
•
•
•

BCL Files (*.bcl.gz)
FILTER Files
Position Files
RunInfo Files
Sample Sheet Files (optional)

NovaSeq

•
•
•
•
•

CBCL Files (*.cbcl)
FILTER Files (*.filter)
Position Files (s.locs)
Runinfo FIles (Runinfo.xml)
Samples Sheet Files (SampleSheet.csv, optional)

BCL Conversion Input Files Diagram
Figure 1 BCL Conversion Input Files from the MiSeq or HiSeq 2000/2500 System

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Figure 2 BCL Conversion Input Files from the MiniSeq or NextSeq System

Figure 3 BCL Conversion Input Files from the HiSeq X System

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Figure 4 BCL Conversion Input Files from the NovaSeq System

Folder and File Naming
The top-level run folder name is generated using 3 fields to identify the , separated by
underscores.
The software generates the top-level run folder using 3 fields separated by underscores to identify the
.
Example:
YYMMDD_machinename_NNNN
For best practices, do not deviate from the run folder naming convention because doing so can cause the software to
stop.
u

The first field is a six-digit number (YYMMDD) specifying the date of the run.

u

The second field specifies the name of the sequencing machine. The field can consist of any combination of upper
or lower case letters, digits, or hyphens, but it cannot contain any other characters or underscore.

u

The third field is a four-digit number that specifies the experiment ID on that instrument. Each instrument supplies
a series of consecutively numbered experiment IDs from the on-board sample tracking database or a LIMS.

For best practices, we recommend that you create unique names for the experiment or sample IDs for each
instrument to avoid naming conflicts.
For example, a run folder named 150108_instrument1_3147 indicates that the experiment ID is 3147; the run is on
instrument 1, and the date is on January 8, 2015 (YYMMDD). The date and instrument name specify a unique run
folder for any number of instruments.
Also, you can view the flow cell number in the run folder name.

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Example:
YYMMDD_machinename_NNNN_FCYYY
When you publish the data to a public database, we recommend that you use a prefix for each instrument with the
identity of the sequencing center.

BCL Files
The BCL files are compressed with the gzip (*.gz) or the blocked GNU zip (*.bgzf) format.
The BaseCalls directory contains the BCL files. The NextSeq and MiniSeq files are located in the following directory:
Data/Intensities/BaseCalls/L
You can locate the HiSeq and MiSeq files in the following directory:
Data/Intensities/BaseCalls/L/C.1
Table 1 BCL File Format
Bytes

Description

Data type

Bytes 0–3

Number N of cluster

Unsigned 32 bits
integer

Bytes 4–(N+3)
N—Cluster
index

Bits 0–1 are the bases, [A, C, G, T] for [0, 1, 2, 3]:
bits 2–7 are shifted by 2 bits and contain the quality
score.
All bits with 0 in a byte is reserved for no call.

Unsigned 8 bits
integer

CBCL Files
The BCL data are aggregated and written out in the CBCL format when aggregation is on (the current aggregation
scheme is per lane/surface). The CBCL file format is as follows:
Table 2 CBCL File Format
CBCL File Header
Bytes/Field

Description

Data Type

Bytes 0 - 1

Version number, current version is 1

unsigned 16 bits little endian integer

Bytes 2 - 5

Header size

unsigned 32 bits little endian integer

Byte 6

Number of bits per basecall

unsigned

Byte 7

Number of bits per q-score

unsigned

q-val mapping info
Bytes 0-3

Number of bins (B), zero indicates no
mapping

B pairs of 4 byte values (if B > 0)

{from, to}, {from, to}, {from, to} …
from: quality score bin
to: quality score

Number of tile records

unsigned 32bits little endian integer

gzip virtual file offsets, one record per tile
Bytes 0-3: tile number
Bytes 4-7

Number of clusters that were written
into the current block (required due to
bit-packed q-scores)

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unsigned 32 bit integer

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Bytes 8-11

Uncompressed block size of the tile
data (useful for sanity check when
excluding non-PF clusters)

unsigned 32 bit integer

Bytes 12-15

Compressed block size of the tile data

unsigned 32 bit integer

non-PF clusters excluded flag

1: non-PF clusters are excluded
0: non-PF clusters are included
CBCL File Content

N blocks of gzip files, where N is the number of tiles. Each block consists of C number of basecall, quality score pairs where C
is the number of clusters for the given tile.
Each basecall, quality score pair has the following format (assuming 2 bits are used for the basecalls):
Bits 0-1: Basecalls (respectively [A, C, G, T] for [00, 01, 10, 11])
Bits 2 and up: Quality score (unsigned Q bit little endian integer where Q is the number of bits per q-score).
For a two bit quality score, this is two clusters per byte where the bottom 4 bits are the first cluster and the higher 4 bits are the
second cluster.

BCI Files
The BCI (*.bci) files contain one record per tile for the sequencing run in binary format. You can locate these files from
the following directory:
/Data/Intensities/BaseCalls/L
Table 3 BCI File Format
Bytes

Description

Bytes 0–3

Tile number

Bytes 4–7

Number of clusters in the tile

STATS Files
The STATS file (*.stats) is a binary file that contains base calling statistics. You can locate these files from the following
directory:
Data/Intensities/BaseCalls/L00/C.1
Table 4 Stats File Format
Start

Description

Data Type

Byte 0

Cycle number

integer

Byte 4

Average Cycle Intensity

double

Byte 12

Average intensity for A over all clusters with intensity for A

double

Byte 20

Average intensity for C over all clusters with intensity for C

double

Byte 28

Average intensity for G over all clusters with intensity for G

double

Byte 36

Average intensity for T over all clusters with intensity for T

double

Byte 44

Average intensity for A over clusters with base call A

double

Byte 52

Average intensity for C over clusters with base call C

double

Byte 60

Average intensity for G over clusters with base call G

double

Byte 68

Average intensity for T over clusters with base call T

double

Byte 76

Number of clusters with base call A

integer

Byte 80

Number of clusters with base call C

integer

Byte 84

Number of clusters with base call G

integer

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Start

Description

Data Type

Byte 88

Number of clusters with base call T

integer

Byte 92

Number of clusters with base call X

integer

Byte 96

Number of clusters with intensity for A

integer

Byte 100

Number of clusters with intensity for C

integer

Byte 104

Number of clusters with intensity for G

integer

Byte 108

Number of clusters with intensity for T

integer

FILTER Files
The FILTER file (*.filter) is a binary file that contains the filter results. You can locate these files from the following
directory:
Data/Intensities/BaseCalls/L
Table 5 Filter File Format
Bytes

Description

Bytes 0–3

Zero value (for backwards compatibility)

Bytes 4–7

Filter format version number

Bytes 8–11

Number of clusters

Bytes 12–(N+11)
N—cluster number

Unsigned 8 bits integer
Bit 0 is pass or failed filter

CONTROL Files
CONTROL files (*.control) are deprecated as of bcl2fastq v2.19 and are no longer used by the software.

CONFIG Files
NOTE
The CONFIG files are only created on RTA 1 systems (MiSeq and HiSeq 2500). They are not produced or
expected on newer platforms.
The CONFIG (*config.xml) file records information specific to the generation of the subfolders. The file contains a tagvalue list that describes the cycle-image folders used to generate each folder of intensity and sequence files. You can
locate the file from the following directory:
/Data/Intensities/
The other CONFIG (*config.xml) file is in the BaseCalls directory, which contains the meta-information on the base
caller runs. You can locate the file from the following directory:
/Data/Intensities/BaseCalls/

Position Files
The BCL to FASTQ converter can use different types of position files.
The LOCS (*.locs) file is a binary file that contains the cluster positions. Additionally, the *.clocs files are compressed
versions of LOCS files.
The *_pos.txt files are text-based files with 2 columns and a number of rows equal to the number of clusters. The first
column is the X-coordinate and the second column is the Y-coordinate. Each line has a  at the end.

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You can locate these files in the following directory:
Data/Intensities/L

RunInfo File
The RunInfo.xml file is located at the top-level run folder . The file contains information on the run,
flow cell, and instrument IDs, date and read structure. Also, the file provides the number of reads, the number of
cycles per read, and the index reads.

Sample Sheet
The sample sheet (*SampleSheet.csv) file provides information on the relationship between samples and indexes
during library creation. The sample sheet is optional and the default location is the top-level run folder. You can use the
--sample-sheet command line option to specify any CSV file in any location. When a sample sheet is not provided, all
reads are assigned to the default sample Undetermined_S0, which includes one file per lane per read.

Settings Section
The bcl2fastq2 Conversion Software uses the Settings section of the SampleSheet to specify adapter trimming, UMI,
and index-fastq options..
Table 6 Adapter Specifications
Setting

Description

Adapter or TrimAdapter

The adapter sequence to be trimmed. If an AdapterRead2 is provided, this sequence is
only used to trim Read 1. To trim two or more adapters, separate the sequences by a plus
sign (+). The plus sign between the adapters signifies that these are independent
adapters and that they need to be assessed for trimming independently for each read.

AdapterRead2 or
TrimAdapterRead2

The adapter sequence to be trimmed in Read 2. If not provided, the same sequence
specified in Adapter is used. To trim two or more adapters, separate the sequences by a
plus sign (+). The plus sign between the adapters signifies that these are independent
adapters and that they need to be assessed for trimming independently for each read.

MaskAdapter

The adapter sequence to be masked rather than trimmed. If MaskAdapterRead2 is
provided, this sequence is only used to mask Read 1.

MaskAdapterRead2

The adapter sequence to be masked in Read 2. If not provided, the same sequence
specified in MaskAdapter is used.

FindAdaptersWithIndels

1 (default) or 0. If 1 (true), an approximate string matching algorithm is used to identify the
adapter, treating insertions and deletions as a single mismatch (Myers 1999, J.ACM). If 0
(false), a sliding window algorithm is used, in which insertions and deletions of bases
inside the adapter sequence is not tolerated.

Table 7 Cycle and Tile Specifications
Setting

Description

Read1EndWithCycle

The last cycle to use for Read 1.

Read2EndWithCycle

The last cycle to use for Read 2.

Read1StartFromCycle

The first cycle to use for Read 1.

Read2StartFromCycle

The first cycle to use for Read 2.

Read1UMILength

The length of the UMI used for Read 1.

Read2UMILength

The length of the UMI used for Read 2.

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Setting

Description

Read1UMIStartFromCycle

The first cycle to use for UMI in Read 1.
The cycle index is absolute and not affected by Read1StartFromCycle. The software
supports UMIs only at the beginning or end of reads. This sample sheet setting must be
used in conjunction with the Read1UMILength sample sheet setting or it will be ignored.

Read2UMIStartFromCycle

The first cycle to use for UMI in Read 2.
The cycle index is absolute and not affected by Read2StartFromCycle. The software
currently supports UMIs only at the beginning or end of reads. This sample sheet setting
must be used in conjunction with the Read2UMILength sample sheet setting or it will be
ignored.

TrimUMI

0 (default) or 1 (true). When TrimUMI setting is set to 1, the software trims the UMI bases
from Read 1 and Read 2.

ExcludeTiles

Tiles to exclude. Separate tiles using a plus sign [+], or specified as a range with a hyphen
[-]. For example, ExcludeTiles,1101+2201+1301-1306 means skip tiles 1101, 2201,
and 1301 through 1306.

ExcludeTilesLaneX

Tiles to exclude for Lane X. For example, ExcludeTilesLane6,1101–1108 means skip
tiles 1101 through 1108 for lane 6 only.

Table 8 FASTQ Specifications
Setting

Description

CreateFastqForIndexReads

0 (default) or 1. If 1 (true), generate FASTQ files for index reads. Normally, these FASTQ
files are not needed, because demultiplexing is carried out automatically based on the
sample sheet. Also, the index sequence is already placed in the sequence identifiers in
the FASTQ files.
Generating FASTQ files is based on the following:
• The index read masks are specified from the --use-bases-mask option.
• The RunInfo.xml file when the --use-bases-mask option is not used.

ReverseComplement

0 (default) or 1. If 1 (true), all reads are reverse complemented as they are written to
FASTQ files. This step is necessary in certain unusual cases (eg processing of mate-pair
data using BWA, which expects paired-end data).

Data Section
The bcl2fastq2 Conversion Software uses the information in the columns of the Data section.
Column

Description

Lane

When specified, the software generates FASTQ files for only the samples with the
specified lane number.

Sample_ID

The sample ID. Do not use "all" or "unknown" as the sample ID. If either of these is used as
the name, the sample will be omitted from the report.

Sample_Name

The sample name. Note: Do not use "all" or "undetermined" as the sample name. If either
of these is used as the name, the sample will be omitted from the report.

Sample_Project

The sample project name. The software creates a directory with the specified sample
project name and stores the FASTQ files there. You can use multiple samples in the same
project. Note: Do not use "all" or "default" as the sample project name. If either of these is
used as the name, the sample will be omitted from the report.

index

The index sequence.

index2

The index sequence for index 2.

If the Sample_ID and Sample_Name columns do not match, the FASTQ files are placed in an additional sub-directory
called .

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You can use alphanumeric characters, hyphens [-], and underscores [_] for the Sample_Project, Sample_ID,
and Sample_Name. Sample_ID, Sample_Name, and Sample_Project field entries in the sample sheet cannot
contain illegal characters that are not allowed by some file systems. Examples of common characters that are not
allowed are the space character and the following: ?()[]/\=+<>:;"',*^| &.

Sample Sheet Demultiplexing Scenarios
The Illumina Experiment Manager performs the following for sample sheet BCL conversion and demultiplexing:
u

All reads are placed in the Undetermined_S0 FASTQ files when there is no sample sheet.

u

All reads are placed in the Undetermined_S0 FASTQ files when there is a sample sheet but no data section.

u

All reads are placed in the sample FASTQ file as defined in the sample sheet when there is a sample sheet and one
sample with no indexes.

u

When there is a sample sheet and the samples have indexes, the software performs the following:
u Reads without a matching index are placed in the default Undetermined_S0 FASTQ files.
u Reads with a valid index are placed in the sample FASTQ file as defined in the sample sheet.

For each sample, there is one file per lane per read number when reads exist for that sample, lane, and read number.
NOTE
When the Lane column of the sample sheet Data section is populated, only those lanes are converted. When
the Lane column is not used, all lanes are converted.

Create a Sample Sheet with IEM
The Illumina Experiment Manager (IEM) software helps you create and edit sample sheets for Illumina sequencers and
analysis software. You can use IEM to create sample sheets for any Illumina sequencer.
You can download IEM at support.illumina.com/sequencing/sequencing_software/experiment_
manager/downloads.html.
View the Illumina Experiment Manager User Guide for creating a sample sheet.

Run BCL Conversion and Demultiplexing
Use the following command to run the bcl2fastq2 Conversion Software :
nohup /usr/local/bin/bcl2fastq [options]
An example of a command with options:
nohup /usr/local/bin/bcl2fastq --runfolder-dir 
--output-dir 
This command produces a set of FASTQ files in the BaseCalls directory. Reads with an unresolved or erroneous index
are placed in the Undetermined_S0 FASTQ files. By default, --runfolder-dir is the current directory and -output-dir is the Data/Intensities/BaseCalls sub-directory of the run folder.

BCL2FASTQ Options
The main command line options are the --runfolder-dir and --output-dir. For command line options that
have a corresponding sample sheet setting, the value passed on the command line overwrites the value found in the
sample sheet.

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Table 9 Main Options
Option

Description

-R, --runfolder-dir

Path to run folder directory
Default: ./

-o, --output-dir

Path to demultiplexed output
Default: /Data/Intensities/BaseCalls/

You can use the following advanced options for non-default settings or for customized settings.
Table 10 Directory Options
Option

Description

-i, --input-dir

Path to input directory
Default: /Data/Intensities/BaseCalls/

--sample-sheet

Path to sample sheet, so you can specify the location and name of
the sample sheet, if different from default.
Default: /SampleSheet.csv

The following directory options and thread control options provide more control of the conversion process, but are not
needed for standard usage.
Table 11 Additional Directory Options
Option

Description

--intensities-dir

Path to intensities directory
If intensities directory is specified, then the input directory must
also be specified.
Default: /../

--interop-dir

Path to demultiplexing statistics directory
Default: /InterOp/

--stats-dir

Path to human-readable demultiplexing statistics directory
Default: /Stats/

--reports-dir

Path to reporting directory
Default: /Reports/

For processing, if your computing platform supports threading, the software manages the threads by the following
defaults:
u

4 threads for reading the data

u

4 threads for writing the data

u

20% for demultiplexing data

u

100% for processing demultiplexed data

The file i/o threads spend most of their time sleeping, and so take little processing time. The processing of
demultiplexed data is allocated 1 thread per CPU to make sure that there are no idle CPUs, resulting in more threads
than CPUs by default. You can use the following options to provide control on threading. If, for example, you share your
computing resources with colleagues and wish to limit your usage, these options are useful.

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Table 12 Processing Options
Option

Description

-r, --loading-threads

Number of threads used for loading BCL data.
Default depends on architecture.

-p,
--processing-threads

Number of threads used for processing demultiplexed data.
Default depends on architecture.

-w,
--writing-threads

Number of threads used for writing FASTQ data. This number should not be set higher
than number of samples.
Default depends on architecture.

If you want to use these options to assign multiple threads, consider the following:
u

The most CPU demanding stage is the processing step (-p option). Assign this step the most threads.

u

Reading and writing stages are lightweight and do not need many threads. This consideration is especially
important for a local hard drive where too many threads mean too many parallel read write actions giving
suboptimal performance.

u

Use one thread per CPU core plus a little more to supply CPU with work. This method prevents CPUs being idle
due to a thread being blocked while waiting for another thread.

u

The number of threads depends on the data. If you specify more writing threads than samples, the extra threads
do no work but can cost time due to context switching.

Table 13 Behavioral Options
Option

Description

--adapter-stringency

The minimum match rate that would trigger the masking or trimming process. This value is
calculated as MatchCount / (MatchCount + MismatchCount) and ranges from 0 to 1, but
it is not recommended to use any value < 0.5, as this value would introduce too many
false positives. The default value for this parameter is 0.9, meaning that only reads with
> 90% sequence identity with the adapter are trimmed.
Default: 0.9

--barcode-mismatches

Number of allowed mismatches per index
Multiple entries, comma delimited allowed. Each entry is applied to the corresponding
index; last entry applies to all remaining indexes.
Default: 1. Accepted values: 0, 1 or 2.

--create-fastq-for-indexreads

Create FASTQ files also for Index Reads.
Generating FASTQ files is based on the following:
• The index read masks are specified from the --use-bases-mask option.
• The RunInfo.xml file when the --use-bases-mask option is not used.

--ignore-missing-bcls

Missing or corrupt BCL files are ignored. Assumes 'N'/'#' for missing calls

--ignore-missing-filter

Missing or corrupt filter files are ignored. Assumes Passing Filter for all clusters in tiles
where filter files are missing.

--ignore-missing-positions

Missing or corrupt positions files are ignored. If corresponding position files are missing,
bcl2fastq writes unique coordinate positions in FASTQ header.

--minimum-trimmed-readlength

Minimum read length after adapter trimming. bcl2fastq trims the adapter from the read
down to the value of this parameter. If there is more adapter match below this value, then
those bases are masked, not trimmed (replaced by N rather than removed).
Default: 35

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Option

Description

--mask-short-adapter-reads

This option applies when a read is shorter than the length specified by --minimumtrimmed-read-length (note that the read does not specifically have to be trimmed for
this option to trigger, it need only fall below the —minimum-trimmed-read-length for
any reason). These parameters specify the following behavior:
If the number of bases left after adapter trimming is less than --minimum-trimmedread-length, force the read length to be equal to --minimum-trimmed-read-length
by masking adapter bases (replace with Ns) that fall below this length.
If the number of ACGT bases left after this process falls below --mask-short-adapterreads, mask all bases, resulting in a read with --minimum-trimmed-read-length
number of Ns. In addition, if a read is shorter than--mask-short-adapter-reads for any
reason, it will be masked with Ns. Because it applies when a read is shorter than the value
of --minimum-trimmed-read-length, it should be set to a value that is less than or
equal to this parameter. If it is set to a greater value, it will automatically default to the
same value as--minimum-trimmed-read-length.
Default: 22

--tiles

The --tiles argument takes a regular expression to select for processing only a subset
of the tiles available in the flow cell. Multiple selections can be made by separating the
regular expressions with commas. Examples:
To select all the tiles ending with 5 in all lanes:
--tiles [0–9][0–9][0–9]5
To select tile 2 in lane 1 and all the tiles in the other lanes:
--tiles s_1_0002,s_[2-8]

--use-bases-mask

The --use-bases-mask string specifies how to use each cycle.
An n means ignore the cycle.
A Y (or y) means use the cycle.
An I means use the cycle for the Index Read.
A number means that the previous character is repeated that many times.
An asterisk [*] means that the previous character is repeated until the end of this read or
index (length according to the RunInfo.xml).
The read masks are separated with commas: ,
The format for dual indexing is as follows: --use-bases-mask Y*,I*,I*,Y* or
variations thereof as specified.
You can also specify the --use-bases-mask multiple times for separate lanes, like this
way:
--use-bases-mask 1:y*,i*,i*,y* --use-bases-mask y*,n*,n*,y*
Where the 1: means: Use this setting for lane 1. In this case, the second --use-basesmask parameter is used for all other lanes.
If this option is not specified, the mask is determined from the 'RunInfo.xml file in the run
directory. If it cannot do this determination, supply the --use-bases-mask.
When the --use-bases-mask option is specified, the number of index cycles and the
length of index in the sample sheet should match.

--with-failed-reads

Include all clusters in the output, even clusters that are non-PF. These clusters would
have been excluded by default.
Note: This option cannot be applied to CBCL data.
On RTA 2 systems, clusters that fail filter are no longer read after cycle 25. On systems
other than MiSeq and HiSeq 2500, you will get 25 bases, then all Ns.

--write-fastq-reversecomplement

Generate FASTQ files containing reverse complements of actual data.

--no-bgzf-compression

Turn off BGZF compression, and use GZIP for FASTQ files. BGZF compression allows
downstream applications to decompress in parallel. This parameter is available in case a
consumer of FASTQ data cannot handle all standard GZIP formats.

--fastq-compression-level

Zlib compression level (1–9) used for FASTQ files.
Default: 4

--no-lane-splitting

Do not split FASTQ files by lane.

--find-adapters-withsliding-window

Find adapters with simple sliding window algorithm. Insertions and deletions of bases
inside the adapter sequence are not handled.

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NOTE
Do not use the --no-lane-splitting option if you want to upload the resulting FASTQ files to BaseSpace.
The FASTQ files generated from the --no-lane-splitting option are not compatible with the
BaseSpace file uploader. Files generated without this option (the default setting) are compatible for upload to
BaseSpace.
NOTE
FASTQ files containing failed reads cannot be uploaded to BaseSpace.

Table 14 General Options
Option

Description

-h,
--help

Produce help message and exit

-v,
--version

Print program version information

-l,
--min-log-level

Minimum log level
Recognized values: NONE, FATAL, ERROR, WARNING, INFO, DEBUG, TRACE
Default: INFO

BCL Conversion Output Files
The bcl2fastq2 Conversion Software provides the following output files: output directory has the following
characteristics:
u

FASTQ Files

u

InterOp Files

u

ConversionStats File

u

DemultiplexingStats File

u

AdapterTrimming File

u

FastqSummary and DemuxSummary

u

HTML Reports

u

JSON File

FASTQ Files
The bcl2fastq2 Conversion Software converts *.bcl, *.bcl.gz, *.bcl.bgzf, and .cbcl files into FASTQ files, which can be
used as input for secondary analysis. When there is no sample sheet, the software generates a Undetermined_S0
FASTQ file for each lane and read number combination.

FASTQ File Names
FASTQ files are named with the sample name and the sample number. The sample number is a numeric assignment
based on the order that the sample is listed for the run. For example:
Data\Intensities\BaseCalls\samplename_S1_L001_R1_001.fastq.gz

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u

samplename—The sample name listed for the sample. If a sample name is not provided, the file name includes
the sample ID.

u

S1—The sample number based on the order that samples are listed for the run starting with 1. In this example, S1
indicates that this sample is the first sample listed for the run.
NOTE
Reads that cannot be assigned to any sample are written to a FASTQ file for sample number 0, and
excluded from downstream analysis.

u

L001—The lane number.

u

R1—The read. In this example, R1 means Read 1. For a paired-end run, a file from Read 2 includes R2 in the file
name. When generated, the Index Reads are I1 or I2.

u

001—The last segment is always 001.

FASTQ files are compressed in the GNU zip format, as indicated by *.gz in the file name. FASTQ files can be
uncompressed using tools such as gzip (command-line) or 7-zip (GUI).

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:
u

The identifier

u

The sequence

u

A plus sign (+)

u

The quality scores in a +33 offset ASCII encoded format

The identifier is formatted as:
@Instrument:RunID:FlowCellID:Lane:Tile:X:Y:UMI ReadNum:FilterFlag:0:IndexSequence or SampleNumber
Example:
@SIM:1:FCX:1:2106:15337:1063:GATCTGTACGTC 1:N:0:ATCACG
GATCTGTACGTCTCTGCNTCACCTCCACCGTGCAACTCATCACGCAGCTCATGCCCTTCGGCTGCCTCCTGGACTA
+
CCCCCGGGGGGGGGGGG#:CFFGFGFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGEGGFGGG

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Table 15 Identifiers Table

Identifiers

Description

@

Each sequence identifier line starts with @.

instrument

The instrument ID.

run number

The run number on the instrument.

flowcell ID

The flowcell ID.

lane

The lane number.

tile

The tile number.

x_pos

The X coordinate of the cluster.

y_pos

The Y coordinate of the cluster.

UMI

[Optional] The Unique Molecular Identifiers (UMIs) are restricted to A/T/G/C/N. The
UMI sequences for Read 1 and Read 2 are separated by a plus sign (+) when the UMIs are
specified in the sample sheet.

read

Read 1—Single read.
Read 2—Paired-end read.

is filtered

Y—The read is filtered (only showing when --with-failed-reads option is applied).
N—The read is not filtered.

control number

0—No control bits are turned on.
Even number—Control bits are turned on.

index sequence or sample
number

The Index reads are restricted to A/T/G/C/N. When an indexed sample sheet is used, the
index sequence is written to the end of the read identifier. If an unindexed sample sheet is
used (single sample per lane), the sample number is written to the read identifier.

FASTQ Compression
FASTQ files are compressed in the GNU zip format, as indicated by *.gz in the file name. FASTQ files can be
uncompressed using tools such as gzip (command-line) or 7-zip (GUI).
The BGZF variant facilitates parallel decompression of the FASTQ files by downstream applications. If a downstream
application cannot handle the BGZF variant, it can be turned off with the --no-bgzf-compression command
line.

Quality Scores
A quality score, or Q-score, is a prediction of the probability of an incorrect base call. A higher Q-score implies that a
base call is more reliable.
Based on the Phred scale, the Q-score serves as a compact way to communicate small error probabilities. Given a
base call, X, the probability that X is not true, P(~X), results in a quality score, Q(X), according to the relationship:
Q(X) = -10 log10(P(~X))
where P(~X) is the estimated error probability.
The following table shows the relationship between the quality score and error probability.
Quality Score Q(X)

Error Probability P(~X)

Q40

0.0001 (1 in 10,000)

Q30

0.001 (1 in 1,000)

Q20

0.01 (1 in 100)

Q10

0.1 (1 in 10)

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For more information on the Phred quality score, see en.wikipedia.org/wiki/Phred_quality_score.
During the sequencing run, base call quality scores are calculated after cycle 25 and results are recorded in base call
(*.bcl) files, which contain the base call and quality score per cycle.

Quality Scores Encoding
In FASTQ files, quality scores are encoded into a compact form, which uses only 1 byte per quality value. In this
encoding, the quality score is represented as the character with an ASCII code equal to its value + 33. The following
table demonstrates the relationship between the encoding character, its ASCII code, and the quality score
represented.
NOTE
When Q-score binning is in use, the subset of Q-scores applied by the bins is displayed.
Table 16 ASCII Characters Encoding Q-scores 0–40
Symbol

ASCII Code

Q-Score

Symbol

ASCII Code

Q-Score

!

33

0

6

54

21

"

34

1

7

55

22

#

35

2

8

56

23

$

36

3

9

57

24

%

37

4

:

58

25

&

38

5

;

59

26

'

39

6

<

60

27

(

40

7

=

61

28

)

41

8

>

62

29

*

42

9

?

63

30

+

43

10

@

64

31

,

44

11

A

65

32

-

45

12

B

66

33

.

46

13

C

67

34

/

47

14

D

68

35

0

48

15

E

69

36

1

49

16

F

70

37

2

50

17

G

71

38

3

51

18

H

72

39

4

52

19

I

73

40

5

53

20

InterOp Files
You can locate the InterOp files in the directory: /InterOp. The directory contains binary files
used by the Sequencing Analysis Viewer (SAV) software to summarize various analysis metrics, such as cluster
density, intensities, quality scores, and overall run quality.
The index metrics are stored in the IndexMetricsOut.bin file generated by bcl2fastq2, which has the following binary
format:
Byte 0: file version (1)

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Bytes (variable length): record:
u

2 bytes: lane number (unint16)

u

2 bytes: tile number (unint16)

u

2 bytes: read number (unint16)

u

2 bytes: number of bytes Y for index name (unint16)

u

Y bytes: index name string (string in UTF8Encoding)

u

4 bytes: # clusters identified as index (uint32)

u

2 bytes: number of bytes V for sample name (unint16)

u

V bytes: sample name string (string in UTF8Encoding)

u

2 bytes: number of bytes W for sample project (unint16)

u

W bytes: sample project string (string in UTF8Encoding)

ConversionStats File
You can locate the ConversionStats.xml file in the directory: /Stats/, or in the directory
specified by the --stats-dir option.
The file contains the following information per tile:
u

Raw Cluster Count

u

Read number

u

YieldQ30

u

Yield

u

QualityScore Sum

The file contains the following information per lane:
u

Lane Number

DemultiplexingStats File
You can locate the DemultiplexingStats.xml file in the directory: /Stats/, or in the
directory specified by the --stats-dir option. The file contains the following information per lane, barcode, and
sample, project.
Also, the file contains the following information for flow cell:
u

Barcode Count

u

PerfectBarcode Count

u

OneMismatchBarcode Count

AdapterTrimming File
The AdapterTrimming file is a text-based file format that contains a statistic summary of adapter trimming for the
FASTQ file. You can locate the file in the /Stats/ or in the directory specified by the -stats-dir option.
The file contains the following information:
u

Lane

u

Read

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u

Project

u

Sample ID

u

Sample Name

u

Sample Number

u

TrimmedBases

u

PercentageOfBased (being trimmed)

Also, the file contains the fraction of reads with untrimmed bases for each sample, lane, and read number.

FastqSummaryF1L#
The FastqSummaryF1L#.txt file (the # indicates the lane number) contains the number of raw and passed filter reads
for each sample number and tile. You can locate the file in the /Stats/ or in the directory
specified by the --stats-dir option.

DemuxSummaryF1L#
The DemuxSummaryF1L#.txt (the # indicates the lane number) file is only created if the sample sheet contains at least
one sample and the sample barcode is provided. This file contains the percentage of each tile that each sample
makes up. The file also contains a list of the 1,000 most common unknown barcode sequences, and the total number
of reads with each barcode seen (Note: to improve speed, the total for each barcode is estimated using a sampling
algorithm, and is approximate).
You can locate the file in the /Stats/ or in the directory specified by the --stats-dir
option.

HTML Report
The HTML reports are generated from data in the DemultiplexingStats.xml and ConversionStats.xml files. You can
locate the reports in the directory: /Reports/html/, or in the directory specified by the -reports-dir option.
The Flowcell Summary contains the following information:
u

Clusters (Raw)

u

Clusters (PF)

u

Yield (MBases)
NOTE
For HiSeq X, HiSeq 4000, and HiSeq 3000, the number of raw clusters is actually the number of wells on the flow
cell that could potentially be seeded. The value is the same in all cases.

The Lane Summary provides the following information for each project, sample, and index sequence specified in the
sample sheet:
u

Lane #

u

Clusters (Raw)

u

% of the Lane

u

% Perfect Barcode

u

% One Mismatch

u

Clusters (Filtered)

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u

Yield

u

% PF Clusters

u

%Q30 Bases

u

Mean Quality Score

The Top Unknown Barcodes table in the HTML report provides the count and sequence for the 10 most common
unmapped bar codes in each lane.

JSON File
The Java Script Object Notification (JSON) file contains the *.json file extension. The format for the JSON file makes it
easier to parse the output data. The data in the JSON file are a combination of all the following files:
u

InterOP

u

ConversionStats

u

DemultiplexingStats

u

Adapter Trimming

u

FastqSummary and DemuxSummary

u

HTML Report

u
u

The format of the JSON file is similar to the following example:
{
Flowcell: string //matches Flowcell from RunInfo.xml
RunNumber: int, //matches Run Number from RunInfo.xml
RunId: string, //matches Run Id from RunInfo.xml
ReadInfosForLanes: [ //details per-lane read information
{
LaneNumber: int,
ReadInfos: [
Number: int, //indicates read 1 or read 2 (possible values: 1 and 2)
NumCycles: int, //indicates number of cycles for this read
IsIndexedRead, bool // indicates whether or not this read is an
index read
]
}
],
ConversionResults:[ //details the conversion/demultiplexing results
{
LaneNumber: int,
TotalClustersRaw: int, //number of raw clusters in this lane (null
for HiSeq X)
TotalClustersPf: int //number of clusters passing filter in this
lane
Yield: int, //total yield in this lane
DemuxResults: [ //do not include undetermined reads in this array
{
SampleId: string,

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SampleName: string,
IndexMetrics: [ //empty array if no indices were used for
demultiplexing this sample
{
IndexSequence: string, //if there are two indices, then
concatenate with '+' character (e.g.
"ATCGTCG+TGATCTA")
MismatchCounts: {
0: int, //count of perfectly matching barcodes
1: int //count of barcodes with one mismatch
}
}
],
NumberReads: int, //number of read pairs identified as
index/index-pair
Yield: int, //number of bases after trimming
ReadMetrics: [
{
ReadNumber: int,
Yield: int,
YieldQ30: int,
QualityScoreSum: int,
TrimmedBases: int
}
]
}
]
}
],
UnknownBarcodes: [ //details all the unknown barcodes for a given lane and
number of times it was encountered
{
Lane: int,
Barcodes: {
string: int //example: "ATGAAGAT": 5888
}
}
]
}

Troubleshooting
u

If the bcl2fastq2 Conversion Software fails to complete a run, it could be missing an input file or have a corrupt file.
View the log file for missing or corrupt files. The exact wording of the file status reported varies depending on the
nature of the file corruption. If the problem is the BCL file, launch the --ignore-missing-bcls option. See
BCL Advanced Options.

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u

If there is a high percentage of reads assigned as undetermined, view the Top Unknown Barcodes table in the
HTML report on the index sequence.

u

If the bcl2fastq2 Conversion Software has problems processing Small RNA samples, use the --minimumtrim-read-length 20 and --mask-short-adapter-reads 20 command line instead of the default
settings.

Appendix: Installation Requirements
The bcl2fastq2 Conversion Software requires the following components:
Component

Requirements

Network Infrastructure

1 Gigabit minimum.

Server Infrastructure

Single multiprocessor or multicore computer running Linux.

Analysis Computer

Run software on the Linux operating systems only.

Memory

32 GB RAM.

Software

We recommend the either the CentOS 6 or the RedHat Enterprise Linux 6 platform.

NOTE
Other Linux distributions may work if the dependencies are met, but
are not officially supported for installation.
The following software is required:
• zlib
• librt
• libpthread

The following software are required to build the bcl2fastq2 Conversion
Software :
•
•
•
•
•
•

gcc 4.8.2 or later (with support for C++11)
boost 1.54
CMake 2.8.9
zlib
librt
libpthread

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Revision History
Part #

Revision

Date

15051736

02

March 2017

Description of Change
•
•
•
•

Updated to support bcl2fastq2 v2.19.
Added NovaSeq file structure information.
Added CBCL file format section.
Revised BCL2FASTQ options.
Updated to support bcl2fastq2 v2.18.
Reformatted the User Guide to Illumina style standards.
Added JSON file and input files list for MiniSeq.
Revised BCL2FASTQ options and sample sheet settings.

15051736

01

April 2016

•
•
•
•

15051736

G

July 2015

Updated to software requirements, gcc version.

15051736

F

June 2015

Updated to support bcl2fastq2 v2.17.

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Technical Assistance
For technical assistance, contact Illumina Technical Support.
Website:
Email:

www.illumina.com
techsupport@illumina.com

Illumina Customer Support Telephone Numbers
North America
1.800.809.4566

Germany
0800.180.8994

Singapore
1.800.579.2745

Australia
1.800.775.688

Hong Kong
800960230

Spain
900.812168

Austria
0800.296575

Ireland
1.800.812949

Sweden
020790181

Belgium
0800.81102

Italy
800.874909

Switzerland
0800.563118

China
400.635.9898

Japan
0800.111.5011

Taiwan
00806651752

Denmark
80882346

Netherlands
0800.0223859

United Kingdom
0800.917.0041

Finland
0800.918363

New Zealand
0800.451.650

Other countries
+44.1799.534000

France
0800.911850

Norway
800.16836

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.

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2



Source Exif Data:
File Type                       : PDF
File Type Extension             : pdf
MIME Type                       : application/pdf
PDF Version                     : 1.4
Linearized                      : No
Page Count                      : 30
Page Mode                       : UseOutlines
Language                        : en-us
Producer                        : madbuild
Create Date                     : 2017:03:07 17:25:41-08:00
Modify Date                     : 2017:03:07 17:25:41-08:00
Title                           : bcl2fastq2 Conversion Software v2.19 User Guide
Author                          : Illumina
Subject                         : Instructions for running the bcl2fastq2 Conversion Software v2.19
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