
What is CrossMap ?¶
CrossMap is a program for genome coordinates conversion between different assemblies (such as hg18 (NCBI36) <=> hg19 (GRCh37)). It supports commonly used file formats including BAM, CRAM, SAM, Wiggle, BigWig, BED, GFF, GTF and VCF.
Who is using CrossMap ?¶
How CrossMap works?¶

Algorithm¶
CrossMap first determines the correspondence between genome assemblies from UCSC chain file (chain file describes the pair-wise alignments between two genomes). Genome intervals will be stored in interval tree data structure, which allows one to efficiently find all intervals that overlap with any given interval or point. Then CrossMap remaps each entry in BAM/SAM, BED, GFF/GTF, VCF file to the target assembly by querying the interval tree. Exon/intron structure in BED file; spliced alignments, paired alignments, insert size, header section, SAM flags in BAM/SAM file; reference alleles, indels in VCF file will be processed properly.
For Wiggle/BigWig format files, line-by-line computation will be very slow. To increase speed, CrossMap groups consecutive coordinates with the same coverage score into bins (i.e., genomic regions), then remaps those regions one-by-one to the target assembly by querying the interval tree. In other words, Wiggle/BigWig files will be converted into bedGraph format internally, which will be converted into BigWig format (if UCSC’s ‘wigToBigWig’ executable exists and is callable).
Time complexity¶
Assume there are N lines in the chain file. CrossMap loads the chain file first and processes the query file line by line. Thus the space complexity is O(N). For each query region (s,t), it takes O(logN) time to locate which chain(s) overlap with s and t. Then it takes O(logN) time to search the sorted ungapped alignments in this chain that overlap with s and t and calculate the converted values for s and t in the target assembly. So in total it takes O(logN) time to convert one query. The time complexity is O(logN*M) to convert M queries.
In practical, the time CrossMap takes increases linearly to the size of input file.
Release history¶
07/22/2019: Release version 0.3.6.
Support MAF (mutation annotation format).
Fix error “TypeError: AlignmentHeader does not support item assignment (use header.to_dict()” when lifting over BAM files. User does not need to downgrade pysam to 0.13.0 to lift over BAM files.
07/11/2019: Release version 0.3.5.
Fix bugs where .0 is appended to the end coordinate in the resulting GFF file.
04/01/2019: Release version 0.3.4.
Fix bugs when chromosome IDs (of the source genome) in chain file do not have ‘chr’ prefix (such as “GRCh37ToHg19.over.chain.gz”). This version also allows CrossMap to detct if a VCF mapping was inverted, and if so reverse complements the altenerative allele (Thanks Andrew Yates). Improve wording.
01/07/2019: Release version 0.3.3.
Version 0.3.3 is exactly the same as Version 0.3.2. The reason to release this version is that CrossMap-0.3.2.tar.gz was broken when uploading to pypi.
12/14/18: Release version 0.3.2.
Fix the key error problem (e.g KeyError: “sequence ‘b‘7_KI270803v1_alt’’ not present”). This error happens when a locus from the orignal assembly is mapped to a “alternative”, “unplaced” or “unlocalized” contig in the target assembly, and this “target contig” does not exist in your target_ref.fa. In version 0.3.2, such loci will be silently skipped and saved to the “.unmap” file.
11/05/18: Release version 0.3.0:
v0.3.0 or newer will Support Python3. Previous versions support Python2.7.*
add pyBigWig as a dependency.
09/06/17: Release version 0.2.8:
In Bam file lift over: fixed the bug “CrossMap does not set the unmapped read flag for the first read in pair when it is unmapped”.
In VCF file lift over: Update the “contig field” in VCF header section. Contig name and size will be changed from the old assembly to the new assembly.
09/06/17: Release version 0.2.7:
In VCF file lift over: fixed the bug “non-standard chromosome IDs were not converted”.
05/09/17: Release version 0.2.6:
In BAM file lift over: fixed bugs during BAM file sorting and indexing steps (works with pysam v0.11.1).
In BAM file lift over: fixed bugs “the read group type is automatically and wrongly changed from Z to A” (https://github.com/pysam-developers/pysam/issues/113).
10/7/16: Release version 0.2.5:
fixed bugs during single-end BAM file conversion.
Add optional tags to the output BAM file. Details see: Convert BAM/CRAM/SAM format files.
08/18/16: Release version 0.2.4:
fixed bugs during BAM file conversion:
When the strand of the ead changes, the seq filed is reverse complemented and the quality field is reversed.
In the output VCF file, if the reference allele field is empty:
Use CrossMap v0.2.4. Update pysam to the latest version. And make sure chromosome IDs in the reference genome file are in the form of “chr1”, “chr2”, …, “chrX”,”chrY” (but not “1”, “2”, …, “X”,”Y”, in this case, pysam cannot index your reference genome file for some unknown reasons.).
to upgrade, run: pip install CrossMap –upgrade
04/13/16: Release version 0.2.3:
Same as v0.2.2.
Two dependency packages bx-python and pysam do not ship with CrossMap starting from v0.2.3 .
Users could install CrossMap using pip: pip install CrossMap. Note: bx-python and pysam will be installed automatically if they haven’t been installed before.
11/10/15: Release version 0.2.2: Generate *.unmap files (regions that cannot be unambiguously converted) when converting BED, GTF, GFF files. This version also supports genePred (bed12+8) format. (Thanks for Andrew Yates from EMBL-EBI)
08/26/15: Release version 0.2.1: Very minor change, same as 0.2.
08/11/15: Release version 0.2: Fixed the bug that CrossMap will not convert wiggle format files due to name collision with bx python.
07/27/15: Release version 0.1.9. For VCF file conversion in v0.1.9:
CrossMap uses the indexed reference genome (target assembly) sequences rather than load the entire file into memory. Users could index their reference genome file using samtools faidx before running CrossMap, otherwise, CrossMap will index it automatically the first time you run it.
In the output VCF file, whether the chromosome IDs contain “chr” or not depends on the input format.
05/15/15: Release version 0.1.8: Fixed the bug that CrossMap will output invalid VCF file when the input VCF file contains a INFO field with whitespace.
05/04/15: Release version 0.1.7: Address the problem that CrossMap does not convert strand in inversions when input file is BED6 or BED12 format.
11/06/14: Release version 0.1.6: Fixed “negative coordinates” bug.
08/05/14: Release version 0.1.5: Support compressed (*.gz, *.Z, *.z, *.bz, *.bz2, *.bzip2) wiggle file as input.
05/19/14: add chain files for hg38->hg19, hg19->hg38, hg18->hg38, hg19->GRCh37, GRCh37->hg19. In CrossMap v0.1.4, conversion results of BAM/SAM files can be directed to STDOUT to support piping.
12/12/13: CrossMap was accepted by Bioinformatics
10/23/13: CrossMap (0.1.3) was released
Installation¶
Use pip to install CrossMap¶
pip3 install git+https://github.com/liguowang/CrossMap.git
or
pip3 install CrossMap #Install CrossMap supporting Python3
Use pip to upgrade CrossMap¶
pip3 install CrossMap --upgrade #upgrade CrossMap supporting Python3
Install CrossMap from source code¶
Prerequisite
CrossMap (version <= 0.2.9)
CrossMap (version >= 0.3.0)
$ tar zxf CrossMap-VERSION.tar.gz
$ cd CrossMap-VERSION
# install CrossMap to default location. In Linux/Unix, this location is like:
# /home/user/lib/python2.7/site-packages/
$ python setup.py install
# or you can install CrossMap to a specified location:
$ python setup.py install --root=/home/user/CrossMap
# setup PYTHONPATH. Skip this step if CrossMap was installed to default location.
$ export PYTHONPATH=/home/user/CrossMap/usr/local/lib/python2.7/site-packages:$PYTHONPATH.
# Skip this step if CrossMap was installed to default location.
$ export PATH=/home/user/CrossMap/usr/local/bin:$PATH
NOTE:
Mac users need to download and install Xcode command line tools.
Input and Output¶
CrossMap basically needs 2 input files. chain format file describing genome-wide pairwise alignments between assemblies and the file containing genome coordinates that you want to convert to different assembly. If input file is in VCF format, a reference genome sequence file(in FASTA format) is needed.
Chain file¶
UCSC built chain files (Human, Homo sapiens)
hg38ToHg19.over.chain.gz (Chain file for hg38 to hg19 conversion)
hg19ToHg38.over.chain.gz (Chain file for hg19 to hg38 conversion)
hg18ToHg38.over.chain.gz (Chain file for hg18 to hg38 conversion)
hg19ToHg18.over.chain.gz (Chain file for hg19 to hg18 conversion)
hg19ToHg17.over.chain.gz (Chain file for hg19 to hg17 conversion)
hg18ToHg19.over.chain.gz (Chain file for hg18 to hg19 conversion)
hg18ToHg17.over.chain.gz (Chain file for hg18 to hg17 conversion)
hg17ToHg19.over.chain.gz (Chain file for hg17 to hg19 conversion)
hg17ToHg18.over.chain.gz (Chain file for hg17 to hg18 conversion)
GRCh37ToHg19.over.chain.gz (Chain file for GRCh37 to hg19 conversion)
hg19ToGRCh37.over.chain.gz (Chain file for hg19 to GRCh37 conversion)
UCSC built chain files (Mouse, Mus musculus)
mm10ToMm9.over.chain.gz (Chain file for mm10 to mm9 conversion)
mm9ToMm10.over.chain.gz (Chain file for mm9 to mm10 conversion)
mm9ToMm8.over.chain.gz (Chain file for mm9 to mm8 conversion)
UCSC Chain file of other species can be downloaded from: http://hgdownload.soe.ucsc.edu/downloads.html
Ensembl built chain files (Human, Homo sapiens)
NCBI34 <=> GRCh38
NCBI35 <=> GRCh38
NCBI36 <=> GRCh38
GRCh37 <=> GRCh38
NCBI34 <=> GRCh37
NCBI35 <=> GRCh37
NCBI36 <=> GRCh37
Ensembl built chain files (Mouse, Mus musculus)
Ensembl Chain file of other species can be downloaded from: ftp://ftp.ensembl.org/pub/assembly_mapping/
User Input file¶
Output file¶
Format of Output files depends on the input format
Input_format |
Output_format |
---|---|
BED |
BED (Genome coordinates will be updated to the target assembly) |
BAM |
BAM (Genome coordinates, header section, all SAM flags, insert size will be updated accordingly) |
CRAM |
BAM (require pysam >= 0.8.2) |
SAM |
SAM (Genome coordinates, header section, all SAM flags, insert size will be updated accordingly) |
Wiggle |
BigWig |
BigWig |
BigWig |
GFF |
GFF (Genome coordinates will be updated to the target assembly) |
GTF |
GTF (Genome coordinates will be updated to the target assembly) |
VCF |
VCF (Genome coordinates and reference alleles will be updated to the target assembly) |
Usage¶
Run CrossMap.py without any arguments will print help message:
# run CrossMap without argument
$ python CrossMap.py
Program: CrossMap (v0.3.4)
- Description:
CrossMap is a program for convenient conversion of genome coordinates between assembly versions (e.g. from human hg18 to hg19 or vice versa). It supports file in BAM, CRAM, SAM, BED, Wiggle, BigWig, GFF, GTF and VCF format.
Usage: CrossMap.py <command> [options]
bam convert alignment file in BAM, CRAM or SAM format. bed convert genome coordinate or annotation file in BED, bedGraph or other BED-like format. bigwig convert genome coordinate file in BigWig format. gff convert genome coordinate or annotation file in GFF or GTF format. vcf convert genome coordinate file in VCF format. wig convert genome coordinate file in Wiggle, or bedGraph format.
Run CrossMap.py with a command keyword will print help message for the command. For example:
$ python CrossMap.py bed
#Screen output
Usage
-----
CrossMap.py bed chain_file input_bed_file [output_file]
Description
-----------
Convert BED format file. The "chain_file" and "input_bed_file" can be regular or
compressed (*.gz, *.Z, *.z, *.bz, *.bz2, *.bzip2) file, local file or URL
(http://, https://, ftp://) pointing to remote file. BED format file must have
at least 3 columns (chrom, start, end). If no "output_file" is specified,
output will be directed to the screen (console).
Example1 (write output to file)
-------------------------------
CrossMap.py bed hg18ToHg19.over.chain.gz test.hg18.bed test.hg19.bed
Example2 (write output to screen)
---------------------------------
CrossMap.py bed hg18ToHg19.over.chain.gz test.hg18.bed
Convert BED format files¶
A BED (Browser Extensible Data) file is a tab-delimited text file describing genome regions or gene annotations. It is the standard file format used by UCSC. It consists of one line per feature, each containing 3-12 columns. CrossMap converts BED files with less than 12 columns to a different assembly by updating the chromosome and genome coordinates only; all other columns remain unchanged. Regions from old assembly mapping to multiple locations to the new assembly will be split. For 12-columns BED files, all columns will be updated accordingly except the 4th column (name of bed line), 5th column (score value) and 9th column (RGB value describing the display color). 12-column BED files usually define multiple blocks (e.g. exon); if any of the exons fails to map to a new assembly, the whole BED line is skipped.
The input BED file can be plain text file, compressed file with extension of .gz, .Z, .z, .bz, .bz2 and .bzip2, or even a URL pointing to accessible remote files (http://, https:// and ftp://). Compressed remote files are not supported. The output is a BED format file with exact the same number of columns as the original one.
Standard BED format has 12 columns, but CrossMap also supports BED-like formats:
BED3: The first 3 columns (“chrom”, “start”, “end”) of BED format file.
BED6: The first 6 columns (“chrom”, “start”, “end”, “name”, “score”, “strand”) of BED format file.
Other: Format has at least 3 columns (“chrom”, “start”, “end”) and no more than 12 columns. All other columns are arbitrary.
NOTE:
For BED-like formats mentioned above, CrossMap only updates “chrom (1st column)”, “start (2nd column) “, “end (3rd column) ” and “strand” (if any). All other columns will keep AS-IS.
Lines starting with ‘#’, ‘browser’, ‘track’ will be skipped.
Lines will less than 3 columns will be skipped.
2nd-column and 3-column must be integers, otherwise, the line will be skipped.
“+” strand is assumed if no strand information was found.
For standard BED format (12 columns). If any of the defined exon blocks cannot be uniquely mapped to target assembly, the whole entry will be skipped.
“input_chain_file” and “input_bed_file” can be regular or compressed (.gz, .Z, .z, .bz, .bz2, .bzip2) file, local file or URL (http://, https://, ftp://) pointing to remote file.
If output_file was not specified, results will be printed to screen (console). In this case, the original bed entries (include items failed to convert) were also printed out.
If input region cannot be consecutively mapped target assembly, it will be split.
*.unmap file contains regions that cannot be unambiguously converted.
Example (run CrossMap with no output_file specified):
$ python CrossMap.py bed hg18ToHg19.over.chain.gz test.hg18.bed3
# Conversion results were printed to screen directly (column1-3 are hg18 based, column5-7 are hg19 based)::
chr1 142614848 142617697 -> chr1 143903503 143906352
chr1 142617697 142623312 -> chr1 143906355 143911970
chr1 142623313 142623350 -> chr1 143911971 143912008
Example (run CrossMap with output_file (test.hg19.bed3) specified):
$ python CrossMap.py bed hg18ToHg19.over.chain.gz test.hg18.bed3 test.hg19.bed3
$ cat test.hg19.bed3
chr1 143903503 143906352
chr1 143906355 143911970
chr1 143911971 143912008
Example (one input region was split because it cannot be consecutively mapped target assembly):
$ python CrossMap.py bed hg18ToHg19.over.chain.gz test.hg18.bed3
chr10 81346644 81349952 + -> chr10 81356692 81360000 +
chr10 81349952 81364937 + -> chr10 81360000 81374985 +
chr10 81364952 81365854 + -> chr10 81375000 81375902 +
chr10 81365875 81369946 + -> chr10 81375929 81380000 +
chr10 81369946 81370453 + -> chr10 81380000 81380507 +
chr10 81370483 81371363 + -> chr10 81380539 81381419 +
chr10 81371363 81371365 + -> chr10 62961832 62961834 +
chr10 81371412 81371432 + (split.1:chr10:81371412:81371422:+) chr10 62961775 62961785 +
chr10 81371412 81371432 + (split.2:chr10:81371422:81371432:+) chrX 63278348 63278358 +
Example (Use bed command to convert a bedGraph file, output another bedGraph file. If Use wig command to convert a bedGraph file, output a bigWig file. ):
$ python3 ../bin/CrossMap.py bed ../data/UCSC_chain/hg19ToHg38.over.chain.gz 4_hg19.bgr
chrX 5873316 5873391 2.0 -> chrX 5955275 5955350 2.0
chrX 5873673 5873710 0.8 -> chrX 5955632 5955669 0.8
chrX 5873710 5873785 1.4 -> chrX 5955669 5955744 1.4
chrX 5873896 5873929 0.9 -> chrX 5955855 5955888 0.9
chrX 5873929 5874004 1.5 -> chrX 5955888 5955963 1.5
chrX 5874230 5874471 0.3 -> chrX 5956189 5956430 0.3
chrX 5874471 5874518 0.9 -> chrX 5956430 5956477 0.9
$ python3 ../bin/CrossMap.py wig ../data/UCSC_chain/hg19ToHg38.over.chain.gz 4_hg19.bgr output_hg38
@ 2018-11-06 00:09:11: Read chain_file: ../data/UCSC_chain/hg19ToHg38.over.chain.gz
@ 2018-11-06 00:09:12: Liftover wiggle file: 4_hg19.bgr ==> output_hg38.bgr
@ 2018-11-06 00:09:12: Merging overlapped entries in bedGraph file ...
@ 2018-11-06 00:09:12: Sorting bedGraph file:output_hg38.bgr
@ 2018-11-06 00:09:12: Writing header to "output_hg38.bw" ...
@ 2018-11-06 00:09:12: Writing entries to "output_hg38.bw" ...
Convert BAM/CRAM/SAM format files¶
SAM (Sequence Alignment Map) format is a generic format for storing sequencing alignments, and BAM is binary and compressed version of SAM (Li et al., 2009). CRAM was designed to be an efficient reference-based alternative to the SAM and BAM file formats Most high-throughput sequencing (HTS) alignments were in SAM/BAM format and many HTS analysis tools work with SAM/BAM format. CrossMap updates chromosomes, genome coordinates, header sections, and all SAM flags accordingly. CrossMap’s version number is inserted into the header section, along with the names of the original BAM file and the chain file. For pair-end sequencing, insert size is also recalculated. The input BAM file should be sorted and indexed properly using samTools (Li et al., 2009). Output format is determined from the input format and BAM output will be sorted and indexed automatically.
Typing command without any arguments will print help message:
$ python CrossMap.py bam
Usage: CrossMap.py bam chain_file input_file output_file [options]
Note: If output_file == STDOUT or -, CrossMap will write BAM file to the screen
Options:
-m INSERT_SIZE, --mean=INSERT_SIZE
Average insert size of pair-end sequencing (bp).
[default=200.0]
-s INSERT_SIZE_STDEV, --stdev=INSERT_SIZE_STDEV
Stanadard deviation of insert size. [default=30.0]
-t INSERT_SIZE_FOLD, --times=INSERT_SIZE_FOLD
A mapped pair is considered as "proper pair" if both
ends mapped to different strand and the distance
between them is less then '-t' * stdev from the mean.
[default=3.0]
-a, --append-tags Add tag to each alignment.
Example (Convert BAM from hg19 to hg18):
# add optional tags using '-a' (recommend always use '-a' option)
$ CrossMap.py bam -a ../data/hg19ToHg18.over.chain.gz test.hg19.bam test.hg18
Insert size = 200.000000
Insert size stdev = 30.000000
Number of stdev from the mean = 3.000000
Add tags to each alignment = True
@ 2016-10-07 15:29:06: Read chain_file: ../data/hg19ToHg18.over.chain.gz
@ 2016-10-07 15:29:07: Liftover BAM file: test.hg19.bam ==> test.hg18.bam
@ 2016-10-07 15:29:14: Done!
@ 2016-10-07 15:29:14: Sort "test.hg18.bam" ...
@ 2016-10-07 15:29:15: Index "test.hg18.sorted.bam" ...
Total alignments:99914
QC failed: 0
R1 unique, R2 unique (UU): 96094
R1 unique, R2 unmapp (UN): 3579
R1 unique, R2 multiple (UM): 0
R1 multiple, R2 multiple (MM): 0
R1 multiple, R2 unique (MU): 233
R1 multiple, R2 unmapped (MN): 8
R1 unmap, R2 unmap (NN): 0
R1 unmap, R2 unique (NU): 0
R1 unmap, R2 multiple (NM): 0
# BAM/SAM header sections was updated:
$ samtools view -H test.hg19.bam
@SQ SN:chr1 LN:249250621
@SQ SN:chr2 LN:243199373
@SQ SN:chr3 LN:198022430
@SQ SN:chr4 LN:191154276
@SQ SN:chr5 LN:180915260
@SQ SN:chr6 LN:171115067
@SQ SN:chr7 LN:159138663
@SQ SN:chr8 LN:146364022
@SQ SN:chr9 LN:141213431
@SQ SN:chr10 LN:135534747
@SQ SN:chr11 LN:135006516
@SQ SN:chr12 LN:133851895
@SQ SN:chr13 LN:115169878
@SQ SN:chr14 LN:107349540
@SQ SN:chr15 LN:102531392
@SQ SN:chr16 LN:90354753
@SQ SN:chr17 LN:81195210
@SQ SN:chr18 LN:78077248
@SQ SN:chr19 LN:59128983
@SQ SN:chr20 LN:63025520
@SQ SN:chr21 LN:48129895
@SQ SN:chr22 LN:51304566
@SQ SN:chrX LN:155270560
@SQ SN:chrY LN:59373566
@SQ SN:chrM LN:16571
@RG ID:Sample_618545BE SM:Sample_618545BE LB:Sample_618545BE PL:Illumina
@PG ID:bwa PN:bwa VN:0.6.2-r126
$ samtools view -H test.hg18.bam
@HD VN:1.0 SO:coordinate
@SQ SN:chr1 LN:247249719
@SQ SN:chr10 LN:135374737
@SQ SN:chr11 LN:134452384
@SQ SN:chr11_random LN:215294
@SQ SN:chr12 LN:132349534
@SQ SN:chr13 LN:114142980
@SQ SN:chr13_random LN:186858
@SQ SN:chr14 LN:106368585
@SQ SN:chr15 LN:100338915
@SQ SN:chr15_random LN:784346
@SQ SN:chr16 LN:88827254
@SQ SN:chr17 LN:78774742
@SQ SN:chr17_random LN:2617613
@SQ SN:chr18 LN:76117153
@SQ SN:chr18_random LN:4262
@SQ SN:chr19 LN:63811651
@SQ SN:chr19_random LN:301858
@SQ SN:chr1_random LN:1663265
@SQ SN:chr2 LN:242951149
@SQ SN:chr20 LN:62435964
@SQ SN:chr21 LN:46944323
@SQ SN:chr21_random LN:1679693
@SQ SN:chr22 LN:49691432
@SQ SN:chr22_random LN:257318
@SQ SN:chr3 LN:199501827
@SQ SN:chr3_random LN:749256
@SQ SN:chr4 LN:191273063
@SQ SN:chr4_random LN:842648
@SQ SN:chr5 LN:180857866
@SQ SN:chr6 LN:170899992
@SQ SN:chr6_random LN:1875562
@SQ SN:chr7 LN:158821424
@SQ SN:chr7_random LN:549659
@SQ SN:chr8 LN:146274826
@SQ SN:chr8_random LN:943810
@SQ SN:chr9 LN:140273252
@SQ SN:chr9_random LN:1146434
@SQ SN:chrM LN:16571
@SQ SN:chrX LN:154913754
@SQ SN:chrX_random LN:1719168
@SQ SN:chrY LN:57772954
@RG ID:Sample_618545BE SM:Sample_618545BE LB:Sample_618545BE PL:Illumina
@PG PN:bwa ID:bwa VN:0.6.2-r126
@PG ID:CrossMap VN:0.1.3
@CO Liftover from original BAM/SAM file: test.hg19.bam
@CO Liftover is based on the chain file: ../test/hg19ToHg18.over.chain.gz
Optional tags:
- Q
QC. QC failed.
- N
Unmapped. Originally unmapped or originally mapped but failed to lift over to new assembly.
- M
Multiple mapped. Alignment can be lifted over to multiple places.
- U
Unique mapped. Alignment can be lifted over to only 1 place.
Tags for pair-end sequencing include:
QF = QC failed
NN = both read1 and read2 unmapped
NU = read1 unmapped, read2 unique mapped
NM = read1 unmapped, multiple mapped
UN = read1 uniquely mapped, read2 unmap
UU = both read1 and read2 uniquely mapped
UM = read1 uniquely mapped, read2 multiple mapped
MN = read1 multiple mapped, read2 unmapped
MU = read1 multiple mapped, read2 unique mapped
MM = both read1 and read2 multiple mapped
Tags for single-end sequencing include:
QF = QC failed
SN = unmaped
SM = multiple mapped
SU = uniquely mapped
NOTE:
All alignments (mapped, partial mapped, unmapped, QC failed) will write to one file. Users can filter them by tags (this is why ‘-a’ is always recommended).
Header section will be updated to the target assembly.
Genome coordinates and all SAM flags in the alignment section will be updated to the target assembly.
if the input is a CRAM file, pysam must >= 0.8.2
Optional fields in the alignment section will not be updated.
Convert Wiggle format files¶
Wiggle (WIG) format is useful for displaying continuous data such as GC content and the reads intensity of high-throughput sequencing data. BigWig is a self-indexed binary-format Wiggle file, and has the advantage of supporting random access. This means only regions that need to be displayed are retrieved by genome browser, and it dramatically reduces the time needed for data transferring (Kent et al., 2010). Input wiggle data can be in variableStep (for data with irregular intervals) or fixedStep (for data with regular intervals). Regardless of the input, the output will always in bedGraph format. bedGraph format is similar to wiggle format and can be converted into BigWig format using UCSC wigToBigWig tool. We export files in bedGraph format because it’s more compact than wiggle format, and more importantly, CrossMap internally transforms wiggle into bedGraph to increase running speed.
Typing command without any arguments will print help message:
$ python2.7 CrossMap.py wig
Usage
-----
CrossMap.py wig chain_file input_wig_file output_prefix
Description
-----------
Convert wiggle format file. The "chain_file" can be regular or compressed (*.gz,
*.Z, *.z, *.bz, *.bz2, *.bzip2) file, local file or URL (http://, https://,
ftp://) pointing to remote file. Both "variableStep" and "fixedStep" wiggle
lines are supported. Wiggle format:
http://genome.ucsc.edu/goldenPath/help/wiggle.html
Example
-------
CrossMap.py wig hg18ToHg19.over.chain.gz test.hg18.wig test.hg19
NOTE:
To improve performance, this script calls GNU “sort” command internally. If “sort” command does not exist, CrossMap will exit.
Convert BigWig format files¶
If an input file is in BigWig format, the output is BigWig format if UCSC’s ‘wigToBigWig’ executable can be found; otherwise, the output file will be in bedGraph format.
After v0.3.0, UCSC’s ‘wigToBigWig’ is no longer needed.
Typing command without any arguments will print help message:
$ python2.7 CrossMap.py bigwig
Usage
-----
CrossMap.py bigwig chain_file input_bigwig_file output_prefix
Description
-----------
Convert BigWig format file. The "chain_file" can be regular or compressed (*.gz,
*.Z, *.z, *.bz, *.bz2, *.bzip2) file, local file or URL (http://, https://,
ftp://) pointing to remote file. Bigwig format:
http://genome.ucsc.edu/goldenPath/help/bigWig.html
Example
-------
CrossMap.py bigwig hg18ToHg19.over.chain.gz test.hg18.bw test.hg19
Example (Convert BigWig file from hg18 to hg19):
$ python CrossMap.py bigwig hg19ToHg18.over.chain.gz test.hg19.bw test.hg18
@ 2013-11-17 22:12:42: Read chain_file: ../data/hg19ToHg18.over.chain.gz
@ 2013-11-17 22:12:44: Liftover bigwig file: test.hg19.bw ==> test.hg18.bgr
@ 2013-11-17 22:15:38: Merging overlapped entries in bedGraph file ...
@ 2013-11-17 22:15:38: Sorting bedGraph file:test.hg18.bgr
@ 2013-11-17 22:15:39: Convert wiggle to bigwig ...
NOTE:
To improve performance, this script calls GNU “sort” command internally. If “sort” command does not exist, CrossMap will exit.
Output files: output_prefix.bw, output_prefix.bgr, output_prefix.sorted.bgr
Convert GFF/GTF format files¶
GFF (General Feature Format) is another plain text file used to describe gene structure. GTF (Gene Transfer Format) is a refined version of GTF. The first eight fields are the same as GFF. Plain text, compressed plain text, and URLs pointing to remote files are all supported. Only chromosome and genome coordinates are updated. The format of the output is determined from the input.
Typing command without any arguments will print help message:
$ python2.7 CrossMap.py gff
Usage
-----
CrossMap.py gff chain_file input_gff_file output_file
Description
-----------
Convert GFF or GTF format file. The"chain_file" can be regular or compressed
(*.gz, *.Z, *.z, *.bz, *.bz2, *.bzip2) file, local file or URL (http://,
https://, ftp://) pointing to remote file. Input file must be in GFF or GTF
format. GFF format: http://genome.ucsc.edu/FAQ/FAQformat.html#format3 GTF
format: http://genome.ucsc.edu/FAQ/FAQformat.html#format4
Example1 (write output to file)
-------------------------------
CrossMap.py gff hg19ToHg18.over.chain.gz test.hg19.gtf test.hg18.gtf
Example2 (write output to screen)
---------------------------------
CrossMap.py gff hg19ToHg18.over.chain.gz test.hg19.gtf
Example (Convert GTF file from hg19 to hg18):
$ python CrossMap.py gff hg19ToHg18.over.chain.gz test.hg19.gtf test.hg18.gtf
@ 2013-11-17 20:44:47: Read chain_file: ../data/hg19ToHg18.over.chain.gz
$ head test.hg19.gtf
chr1 hg19_refGene CDS 48267145 48267291 0.000000 - 0 gene_id "NM_001194986"; transcript_id "NM_001194986";
chr1 hg19_refGene exon 66081691 66081907 0.000000 + . gene_id "NM_002303"; transcript_id "NM_002303";
chr1 hg19_refGene CDS 145334684 145334792 0.000000 + 2 gene_id "NM_001039703"; transcript_id "NM_001039703";
chr1 hg19_refGene exon 172017752 172017890 0.000000 + . gene_id "NM_001136127"; transcript_id "NM_001136127";
chr1 hg19_refGene CDS 206589249 206589333 0.000000 + 2 gene_id "NM_001170637"; transcript_id "NM_001170637";
chr1 hg19_refGene exon 210573812 210574006 0.000000 + . gene_id "NM_001170580"; transcript_id "NM_001170580";
chr1 hg19_refGene CDS 235850249 235850347 0.000000 - 0 gene_id "NM_000081"; transcript_id "NM_000081";
chr1 hg19_refGene CDS 235880012 235880078 0.000000 - 1 gene_id "NM_000081"; transcript_id "NM_000081";
chr1 hg19_refGene exon 3417741 3417872 0.000000 - . gene_id "NM_001409"; transcript_id "NM_001409";
chr1 hg19_refGene exon 10190773 10190871 0.000000 + . gene_id "NM_006048"; transcript_id "NM_006048";
$ head test.hg18.gtf
chr1 hg19_refGene CDS 48039732 48039878 0.000000 - 0 gene_id "NM_001194986"; transcript_id "NM_001194986";
chr1 hg19_refGene exon 65854279 65854495 0.000000 + . gene_id "NM_002303"; transcript_id "NM_002303";
chr1 hg19_refGene CDS 144046041 144046149 0.000000 + 2 gene_id "NM_001039703"; transcript_id "NM_001039703";
chr1 hg19_refGene exon 170284375 170284513 0.000000 + . gene_id "NM_001136127"; transcript_id "NM_001136127";
chr1 hg19_refGene CDS 204655872 204655956 0.000000 + 2 gene_id "NM_001170637"; transcript_id "NM_001170637";
chr1 hg19_refGene exon 208640435 208640629 0.000000 + . gene_id "NM_001170580"; transcript_id "NM_001170580";
chr1 hg19_refGene CDS 233916872 233916970 0.000000 - 0 gene_id "NM_000081"; transcript_id "NM_000081";
chr1 hg19_refGene CDS 233946635 233946701 0.000000 - 1 gene_id "NM_000081"; transcript_id "NM_000081";
chr1 hg19_refGene exon 3407601 3407732 0.000000 - . gene_id "NM_001409"; transcript_id "NM_001409";
chr1 hg19_refGene exon 10113360 10113458 0.000000 + . gene_id "NM_006048"; transcript_id "NM_006048";
NOTE:
Each feature (exon, intron, UTR, etc) is processed separately and independently, and we do NOT check if features originally belonging to the same gene were converted into the same gene.
If user wants to lift over gene annotation files, use BED12 format.
If no output file was specified, the output will be printed to screen (console). In this case, items failed to convert are also printed out.
Convert VCF format files¶
VCF (variant call format) is a flexible and extendable line-oriented text format developed by the 1000 Genome Project. It is useful for representing single nucleotide variants, indels, copy number variants, and structural variants. Chromosomes, coordinates, and reference alleles are updated to a new assembly, and all the other fields are not changed.
Typing command without any arguments will print help message:
$ python2.7 CrossMap.py vcf
usage
-----
CrossMap.py vcf chain_file input_VCF_file ref_genome_file output_file
Description
-----------
Convert VCF format file. The "chain_file" and "input_VCF_file" can be regular or
compressed (*.gz, *.Z, *.z, *.bz, *.bz2, *.bzip2) file, local file or URL
(http://, https://, ftp://) pointing to remote file. "ref_genome_file" is genome
sequence file of 'target assembly' in FASTA format.
Example
-------
CrossMap.py vcf hg19ToHg18.over.chain.gz test.hg19.vcf hg18.fa test.hg18.vcf
Example (Convert VCF file from hg19 to hg18):
$ python CrossMap.py vcf hg19ToHg18.over.chain.gz test.hg19.vcf ../database/genome/hg18.fa test.hg18.vcf
@ 2015-07-27 10:14:23: Read chain_file: ../data/hg19ToHg18.over.chain.gz
@ 2013-11-17 20:53:39: Creating index for ../database/genome/hg18.fa
@ 2015-07-27 10:14:50: Total entries: 497
@ 2015-07-27 10:14:50: Failed to map: 0
$ grep -v '#' test.hg19.vcf |head -10
chr1 10933566 . C G . PASS ADP=13;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:7:13:13:0:13:100%:9.6148E-8:0:36:0:0:8:5
chr1 11187893 . T C . PASS ADP=224;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:133:226:224:0:224:100%:3.6518E-134:0:38:0:0:41:183
chr1 11205058 . C T . PASS ADP=625;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:255:643:625:0:625:100%:0E0:0:37:0:0:294:331
chr1 11292753 . A G . PASS ADP=52;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:27:52:52:2:50:96.15%:9.0394E-28:39:38:0:2:0:50
chr1 11318763 . C G . str10 ADP=88;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:51:88:88:0:88:100%:1.7384E-52:0:38:0:0:1:87
chr1 11319587 . A G . PASS ADP=70;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:40:70:70:0:70:100%:1.0659E-41:0:38:0:0:0:70
chr1 16202995 . C T . PASS ADP=463;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:1:463:463:458:5:1.08%:3.0913E-2:37:33:188:270:4:1
chr1 27088546 . A T . PASS ADP=124;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:21:124:124:65:59:47.58%:1.7915E-22:37:38:59:6:55:4
chr1 27101390 . T C . str10 ADP=267;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:1:267:267:262:5:1.87%:3.0665E-2:32:22:85:177:5:0
chr1 34007097 . T C . PASS ADP=10;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:1:10:10:6:4:40%:4.3344E-2:34:32:0:6:0:4
$ grep -v '#' test.hg18.vcf |head -10
1 10856153 . C G . PASS ADP=13;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:7:13:13:0:13:100%:9.6148E-8:0:36:0:0:8:5
1 11110480 . T C . PASS ADP=224;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:133:226:224:0:224:100%:3.6518E-134:0:38:0:0:41:183
1 11127645 . C T . PASS ADP=625;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:255:643:625:0:625:100%:0E0:0:37:0:0:294:331
1 11215340 . A G . PASS ADP=52;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:27:52:52:2:50:96.15%:9.0394E-28:39:38:0:2:0:50
1 11241350 . C G . str10 ADP=88;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:51:88:88:0:88:100%:1.7384E-52:0:38:0:0:1:87
1 11242174 . A G . PASS ADP=70;WT=0;HET=0;HOM=1;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 1/1:40:70:70:0:70:100%:1.0659E-41:0:38:0:0:0:70
1 16075582 . C T . PASS ADP=463;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:1:463:463:458:5:1.08%:3.0913E-2:37:33:188:270:4:1
1 26961133 . A T . PASS ADP=124;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:21:124:124:65:59:47.58%:1.7915E-22:37:38:59:6:55:4
1 26973977 . T C . str10 ADP=267;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:1:267:267:262:5:1.87%:3.0665E-2:32:22:85:177:5:0
1 33779684 . T C . PASS ADP=10;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:1:10:10:6:4:40%:4.3344E-2:34:32:0:6:0:4
$ grep -v '#' test.hg18.vcf.unmap #coordinates are still based on hg19
chr14 20084444 . G C . PASS ADP=253;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:1:253:253:247:5:1.98%:3.0631E-2:38:39:123:124:5:0
chr14 20086290 . T C . PASS ADP=441;WT=0;HET=1;HOM=0;NC=0 GT:GQ:SDP:DP:RD:AD:FREQ:PVAL:RBQ:ABQ:RDF:RDR:ADF:ADR 0/1:4:441:441:427:14:3.17%:5.4963E-5:37:38:236:191:6:8
NOTE:
Genome coordinates and reference allele will be updated to target assembly.
Reference genome is genome sequence of target assembly.
If the reference genome sequence file (../database/genome/hg18.fa) was not indexed, CrossMap will automatically indexed it (only the first time you run CrossMap).
Output files: output_file and output_file.unmap.
In the output VCF file, whether the chromosome IDs contain “chr” or not depends on the format of the input VCF file.
Convert MAF format files¶
MAF (mutation annotation format) files are tab-delimited files that contain somatic and/or germline mutation annotations. Please do not confused with Multiple Alignment Format.
Typing command without any arguments will print help message:
$ python2.7 CrossMap.py maf
usage
-----
CrossMap.py maf chain_file input_MAF_file ref_genome_file build_name output_file
Description
-----------
Convert MAF format file. The "chain_file" and "input_MAF_file" can be regular or
compressed (*.gz, *.Z, *.z, *.bz, *.bz2, *.bzip2) file, local file or URL
(http://, https://, ftp://) pointing to remote file. "ref_genome_file" is genome
sequence file of 'target assembly' in FASTA format. "build_name" is the name of
the 'target_assembly' (eg "GRCh38")
Example
-------
CrossMap.py maf hg19ToHg38.over.chain.gz test.hg19.maf hg38.fa GRCh38 test.hg38.maf
Compare to UCSC liftover tool¶
To access the accuracy of CrossMap, we randomly generated 10,000 genome intervals (download from here) with the fixed interval size of 200 bp from hg19. Then we converted them into hg18 using CrossMap and UCSC liftover tool with default configurations. We compare CrossMap to UCSC liftover tool because it is the most widely used tool to convert genome coordinates.
CrossMap failed to convert 613 intervals, and UCSC liftover tool failed to convert 614 intervals. All failed intervals are exactly the same except one region (chr2 90542908 90543108). UCSC failed to convert it because this region needs to be split twice:
Original (hg19) |
Split (hg19) |
Target (hg18) |
---|---|---|
chr2 90542908 90543108 - |
chr2 90542908 90542933 - |
chr2 89906445 89906470 - |
chr2 90542908 90543108 - |
chr2 90542933 90543001 - |
chr2 87414583 87414651 - |
chr2 90542908 90543108 - |
chr2 90543010 90543108 - |
chr2 87414276 87414374 - |
For genome intervals that were successfully converted to hg18, the start and end coordinates are exactly the same between UCSC conversion and CrossMap conversion.

Citation¶
Zhao, H., Sun, Z., Wang, J., Huang, H., Kocher, J.-P., & Wang, L. (2013). CrossMap: a versatile tool for coordinate conversion between genome assemblies. Bioinformatics (Oxford, England), btt730.
LICENSE¶
CrossMap is distributed under GNU General Public License
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA