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For commercial use of these toolsets, please note the license considerations for the kent source tools at the: Genome Store


This discussion assumes you are familiar with Unix shell command line programming and scripting. You will be encountering and interacting with csh/tcsh, bash, perl, and python scripting languages. You will need at least one computer with several CPU cores, preferably a multiple compute cluster system or equivalent in a cloud computing environment.

This entire discussion assumes the bash shell is the user's unix shell.

Compute resources

For any reasonable sized genome assemblies, this procedure will require cluster compute resources. Typical compute times can range from 1 to 2 days with 100 CPUs(cores). Much longer compute times will be seen for high contig count genome assemblies (hundreds of thousands of contigs) or for assemblies that are not well repeat masked. Please note this scatter plot and histogram showing compute time vs. genome size for alignments performed at UCSC

SizeVsTime.png LastzProcessingTimeHistogram.png

Parasol Job Control System

For cluster compute resources UCSC uses the parasol job control system. The scripts and programs used here expect to find the Parasol_job_control_system in place and operational.

Install scripts and kent command line utilities

This is a bit of a kludge at this time (April 2018), we are working on a cleaner distribution of these scripts. As was mentioned in the Parasol_job_control_system setup, the kent command line binaries and these scripts are going to reside in /data/bin/ and /data/scripts/. This is merely a style custom to keep scripts separate from binaries, this is not strictly necessary to keep them separate.

 mkdir -p /data/scripts /data/bin
 chmod 755 /data/scripts /data/bin

 rsync -a rsync:// /data/bin/
 git archive --remote=git:// \
  --prefix=kent/ HEAD src/hg/utils/automation \
     | tar vxf - -C /data/scripts --strip-components=5 \
        --exclude='kent/src/hg/utils/automation/incidentDb' \
      --exclude='kent/src/hg/utils/automation/configFiles' \
      --exclude='kent/src/hg/utils/automation/ensGene' \
      --exclude='kent/src/hg/utils/automation/genbank' \
      --exclude='kent/src/hg/utils/automation/lastz_D' \
  wget -O /data/bin/ ''

NOTE: A copy of the lastz binary is included in the rsync download of binaries from hgdownload. It is named lastz-1.04.00 to identify the version. Source for lastz can be obtained from lastz github.

PATH setup

Add or verify the two directories /data/bin and /data/scripts are added to the shell PATH environment. This can be added simply to the .bashrc file in your home directory:

echo 'export PATH=/data/bin:/data/scripts:$PATH' >> $HOME/.bashrc

Then, source that file to add that to this current shell:

. $HOME/.bashrc

Verify you see those pathnames on the PATH variable:

echo $PATH

Working directory hierarchy

It is best to organize your work in a directory hierarchy. For example maintain all your genome sequences in:

 ... etc ...

Where those database directories can have the 2bit files, chrom.sizes, and track construction directories, for example:


Such organizations are a personal preference custom. However you do this, keep it consistent to make it easier to use scripts on multiple sequences.

Obtain genome sequences

Genome sequences from the U.C. Santa Cruz Genomics Institute can be obtained directly from the hgdownload server via rsync. For example

mkdir /data/genomes/dm6
cd /data/genomes/dm6
rsync -avzP \
   rsync:// .
rsync -avzP \
   rsync:// .
ls -og
-rw-rw-r--. 1 36969050 Aug 28  2014 dm6.2bit
-rw-rw-r--. 1    45055 Aug 28  2014 dm6.chrom.sizes

Genome sequences from the NCBI/Entrez/Genbank system can be found via the assembly_summary.txt text listing information files, for example invertebrate genomes:

 wget -O /tmp/invertebrate.assembly_summary.txt ''

Looking for the Anopheles genome:

 grep -w Anopheles /tmp/invertebrate.assembly_summary.txt 
 GCF_000005575.2 PRJNA163        SAMN02952903    AAAB00000000.1  representative genome   180454  7165    Anopheles gambiae str. PEST     strain=PEST            latest   Chromosome      Major   Full    2006/10/16      AgamP3  The International Consortium for the Sequencing of Anopheles Genome     GCA_000005575.1 different

Note the Assembly identification from the ftp path GCF_000005575.2_AgamP3, working with that sequence, using the rsync service in place of the FTP:

 mkdir /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3
 cd /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3
 rsync -L -a -P rsync:// ./
 rsync -L -a -P \
     rsync:// ./
 ls -og
 total 79908
 -rw-rw-r--. 1   811394 Mar  7  2017 GCF_000005575.2_AgamP3_assembly_report.txt
 -rw-rw-r--. 1 81010275 Jun 15  2016 GCF_000005575.2_AgamP3_genomic.fna.gz

The assembly_report.txt file is useful to have for the meta-data information it has about the assembly. The fna.gz file needs to be in 2bit format for the processing system, and the chrom.sizes made from the 2bit:

faToTwoBit GCF_000005575.2_AgamP3_genomic.fna.gz GCF_000005575.2_AgamP3.2bit
twoBitInfo GCF_000005575.2_AgamP3.2bit stdout | sort -k2,2nr > GCF_000005575.2_AgamP3.chrom.sizes
ls -og
total 156132
-rw-rw-r--. 1 77912208 Apr  6 03:48 GCF_000005575.2_AgamP3.2bit
-rw-rw-r--. 1   138303 Apr  6 03:48 GCF_000005575.2_AgamP3.chrom.sizes
-rw-rw-r--. 1   811394 Mar  7  2017 GCF_000005575.2_AgamP3_assembly_report.txt
-rw-rw-r--. 1 81010275 Jun 15  2016 GCF_000005575.2_AgamP3_genomic.fna.gz

lastz parameter file

SEE ALSO: lastz DEF file parameters

The DEF file is used with the script to specify alignment parameters to lastz and the axtChain operations. The example for dm6 target vs. A. gambiae query sequence, loose parameters are used for this distant alignment:

cat DEF
# dm6 vs GCF_000005575.2_AgamP3

# TARGET: D. melanogaster dm6

# QUERY: GCF_000005575.2_AgamP3


NOTE: UCSC tends to keep options for running alignments to approximately four category sets:

  • human to other primates
  • human to other mammals
  • human to more distant vertebrates
  • fly and worm alignments and other such distant organisms

Many examples of DEF files and chaining arguments can be found in the record of alignments at UCSC in the source tree make doc files. For example, alignments to human/hg38: hg38 lastz and the 100-way alignment: Hg38_100-way_conservation_lastz_parameters

Many experiments have been tried over time. To keep it simple:

  • human to other primates
# Where human_chimp.v2.q is:
#  A    C    G    T
#   90 -330 -236 -356
# -330  100 -318 -236
# -236 -318  100 -330
# -356 -236 -330   90
-chainMinScore=5000 -chainLinearGap=medium
  • human to other mammals
# default BLASTZ_Q score matrix:
#       A     C     G     T
# A    91  -114   -31  -123
# C  -114   100  -125   -31
# G   -31  -125   100  -114
# T  -123   -31  -114    91
-chainMinScore=3000 -chainLinearGap=medium
  • human to more distant vertebrates
# HoxD55.q matrix is:
#     A    C    G    T
#    91  -90  -25 -100
#   -90  100 -100  -25
#   -25 -100  100  -90
#  -100  -25  -90  91
-chainMinScore=5000 -chainLinearGap=loose
  • fly and worm alignments and other such distant organisms
# HoxD55.q matrix is:
#     A    C    G    T
#    91  -90  -25 -100
#   -90  100 -100  -25
#   -25 -100  100  -90
#  -100  -25  -90  91
-chainMinScore=1000 -chainLinearGap=loose

perform alignment

After the DEF file is established, verify the files specified in it are actually present at the locations specified:

egrep "_DIR|_LEN" DEF | sed -e 's/.*=//;' | xargs ls -og
-rw-rw-r--. 1 36969050 Aug 28  2014 /data/genomes/dm6/dm6.2bit
-rw-rw-r--. 1    45055 Aug 28  2014 /data/genomes/dm6/dm6.chrom.sizes
-rw-rw-r--. 1 77912208 Apr  6 03:48 /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3/GCF_000005575.2_AgamP3.2bit
-rw-rw-r--. 1   138303 Apr  6 03:48 /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3/GCF_000005575.2_AgamP3.chrom.sizes

Use a screen to keep this command attached to a terminal that you can detach from and reattach to at a later time. For large genomes, or with fewer CPU cores available, this command can run for many days. Time the operation of the command and record all output from it for later analysis if any problems arise from the operation:

screen -S dm6.GCF_000005575
time (/data/scripts/ `pwd`/DEF -verbose=2 -noDbNameCheck \
 -workhorse=localhost -bigClusterHub=localhost -skipDownload \
   -dbHost=localhost -smallClusterHub=localhost \
     -trackHub -fileServer=localhost -syntenicNet) > do.log 2>&1 &

The screen -S dm6.GCF_000005575 gives a name to the terminal so you can find it later in a listing of a number of screens. To detach from the running terminal, use two key presses:

"Ctrl-a Ctrl-d"

to reattach to this screen: screen -r -d dm6.GCF_000005575

BEWARE the drawback of the screen is that you can accidentally exit the shell while in the screen and you thus lose it. The processes that were attached to that shell can continue if they do not respond to the SIGHUP signal. To avoid this side-effect, develop a habit of always exiting a shell with the two key presses "Ctrl-a Ctrl-d", in a shell that is not in a screen it will merely echo those keystrokes and do nothing.

Monitor progress

To determine which step the process is working on, in this working directory, look for the word step in the do.log file:

cd /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3
grep -w step do.log
HgStepManager: executing from step 'partition' through step 'syntenicNet'.
HgStepManager: executing step 'partition' Fri Apr  6 04:50:34 2018.
HgStepManager: executing step 'blastz' Fri Apr  6 04:50:46 2018.

To view the parasol status of your batch:

parasol list batches
#user     run   wait   done crash pri max cpu  ram  plan min batch
centos    323  18446  10283     0  10  -1   1  2.0g  323   0 /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3/run.blastz/

To view the status of that particular batch:

cd /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3/run.blastz/
para time
29052 jobs in batch
16647 jobs (including everybody's) in Parasol queue or running.
Checking finished jobs
Completed: 12405 of 29052 jobs
Jobs currently running: 323
In queue waiting: 16324 jobs
CPU time in finished jobs:      81145s    1352.42m    22.54h    0.94d  0.003 y
IO & Wait Time:                142817s    2380.28m    39.67h    1.65d  0.005 y
Time in running jobs:            4076s      67.93m     1.13h    0.05d  0.000 y
Average job time:                  18s       0.30m     0.01h    0.00d
Longest running job:               43s       0.72m     0.01h    0.00d
Longest finished job:              72s       1.20m     0.02h    0.00d
Submission to last job:           718s      11.97m     0.20h    0.01d
Estimated complete:               930s      15.51m     0.26h    0.01d

This example happens to be running on an Open Stack cluster with 323 allocated CPU cores:

parasol status
CPUs total: 323
CPUs free: 0
CPUs busy: 323
Nodes total: 20
Nodes dead: 0
Nodes sick?: 0
Jobs running:  323
Jobs waiting:  14977
Jobs finished: 13752
Jobs crashed:  0
Spokes free: 30
Spokes busy: 0
Spokes dead: 0
Active batches: 1
Total batches: 1
Active users: 1
Total users: 1
Days up: 0.012685
Version: 12.18

When a parasol batch is completed, this scripting process leaves a run.time file in the batch directory where you can see what type of cluster time you have used:

cd /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3/run.blastz
cat run.time
Completed: 29052 of 29052 jobs
CPU time in finished jobs:     149061s    2484.35m    41.41h    1.73d  0.005 y
IO & Wait Time:                268812s    4480.20m    74.67h    3.11d  0.009 y
Average job time:                  14s       0.24m     0.00h    0.00d
Longest finished job:              72s       1.20m     0.02h    0.00d
Submission to last job:          1312s      21.87m     0.36h    0.02d
Estimated complete:                 0s       0.00m     0.00h    0.00d

For small genomes such as the two in this example, the steps after the lastz alignment can proceed rapidly:

grep -w step do.log
HgStepManager: executing from step 'partition' through step 'syntenicNet'.
HgStepManager: executing step 'partition' Fri Apr  6 04:50:34 2018.
HgStepManager: executing step 'blastz' Fri Apr  6 04:50:46 2018.
HgStepManager: executing step 'cat' Fri Apr  6 05:13:52 2018.
HgStepManager: executing step 'chainRun' Fri Apr  6 05:14:12 2018.
HgStepManager: executing step 'chainMerge' Fri Apr  6 05:15:49 2018.
HgStepManager: executing step 'net' Fri Apr  6 05:15:58 2018.
HgStepManager: executing step 'load' Fri Apr  6 05:17:06 2018.
HgStepManager: executing step 'download' Fri Apr  6 05:17:35 2018.
HgStepManager: executing step 'cleanup' Fri Apr  6 05:17:36 2018.
HgStepManager: executing step 'syntenicNet' Fri Apr  6 05:17:42 2018.

The syntenicNet is the last step in this process, the do.log timing will indicate the full time for this alignment:

tail -3 do.log
real    27m20.456s
user    0m0.720s
sys     0m0.394s

And featureBits measurements have taken place to indicate the amount of coverage of the target genome by the query genome, for both the fundamental alignment, and the syntenic filtered alignment:

ls fb.*
cat fb.*
19155294 bases of 143726002 (13.328%) in intersection
1617815 bases of 143726002 (1.126%) in intersection

Reciprocal Best

After that alignment is completed, the reciprocal best alignment can be computed:

cd /data/genomes/dm6/trackData/GCF_000005575.2_AgamP3
export tDb=`grep "SEQ1_DIR=" DEF | sed -e 's#.*/##; s#.2bit##;'`
export qDb=`grep "SEQ2_DIR=" DEF | sed -e 's#.*/##; s#.2bit##;'`
export target2Bit=`grep "SEQ1_DIR=" DEF | sed -e 's/.*=//;'`
export targetSizes=`grep "SEQ1_LEN=" DEF | sed -e 's/.*=//;'`
export query2Bit=`grep "SEQ2_DIR=" DEF | sed -e 's/.*=//;'`
export querySizes=`grep "SEQ2_LEN=" DEF | sed -e 's/.*=//;'`
time (/data/scripts/ -buildDir=`pwd` -load \
  -workhorse=localhost -dbHost=localhost -skipDownload \
   -target2Bit=${target2Bit} -query2Bit=${query2Bit} \
    -targetSizes=${targetSizes} -querySizes=${querySizes} \
      -trackHub ${tDb} ${qDb}) > rbest.log 2>&1 &

This process does not have any parasol batch procedures. The procedure only does transformations on some of the result files computed during the first alignment procedure. Since this is not a parallel procedure, it takes a bit of time:

grep -w step rbest.log
HgStepManager: executing from step 'recipBest' through step 'cleanup'.
HgStepManager: executing step 'recipBest' Fri Apr  6 05:24:27 2018.
HgStepManager: executing step 'download' Fri Apr  6 05:55:38 2018.
HgStepManager: executing step 'load' Fri Apr  6 05:55:38 2018.
HgStepManager: executing step 'cleanup' Fri Apr  6 05:55:47 2018.

When completed, this has a featureBits measurement also:

cat fb.dm6.chainRBest.GCF_000005575.2_AgamP3.txt 
15316412 bases of 143726002 (10.657%) in intersection


Now that one chain is finished you can swap the reverse direction, note the "swap" and "swapDir" arguments to

mkdir -p /data/genomes/oviAri4/trackData/openstack.lastzHg38.2018-04-26/
cd /data/genomes/oviAri4/trackData/openstack.lastzHg38.2018-04-26/

time (/data/scripts/ \
   /data/genomes/hg38/trackData/openstack.lastzOviAri.2018-04-26/DEF \
   -swap -swapDir=`pwd` -verbose=2 -noDbNameCheck -workhorse=localhost \
   -bigClusterHub=localhost -skipDownload -dbHost=localhost \
   -smallClusterHub=localhost -trackHub -    fileServer=localhost \
   -syntenicNet) > swap.log 2>&1 &

Track Hub files

This procedure has constructed big* files that can be used to display these tracks in a track hub on the UCSC genome browser

ls axtChain/*.bb bigMaf/*.bb

(TBD: show structure of trackDb.txt track hub specifications)

How does this process work

The script performs the processing in distinct steps. Each step is almost always performed with a C-shell or bash shell script. Therefore, if there is a problem in any step, the commands performing the step can be dissected from the script in operation, the problem identified and fixed, and the step completed manually by running the rest of the commands in that script. Once a step has been completed, the process can continue with the next step using the argument -continue=nextStepName. Check the usage message from the script to see a listing of the steps and their sequence. Specifically:

partition, blastz, cat, chainRun, chainMerge, net, load, download, cleanup, syntenicNet

In this example, the various scripts are:

-rwxrwxr-x. 1 1914 Apr  6 04:50 run.blastz/doPartition.bash
-rw-rw-r--. 1 2713 Apr  6 04:50 run.blastz/
-rwxrwxr-x. 1  606 Apr  6 04:50 run.blastz/doClusterRun.csh
-rwxrwxr-x. 1  802 Apr  6 05:13
-rwxrwxr-x. 1   72 Apr  6 05:13
-rwxrwxr-x. 1  412 Apr  6 05:14 axtChain/run/chain.csh
-rwxrwxr-x. 1  700 Apr  6 05:14 axtChain/run/doChainRun.csh
-rwxrwxr-x. 1 3112 Apr  6 05:15 axtChain/netChains.csh
-rwxrwxr-x. 1 2162 Apr  6 05:17 axtChain/loadUp.csh
-rwxrwxr-x. 1 1479 Apr  6 05:17 cleanUp.csh
-rwxrwxr-x. 1 4507 Apr  6 05:17 axtChain/netSynteny.csh
-rwxrwxr-x. 1 6321 Apr  6 05:24 axtChain/doRecipBest.csh
-rwxrwxr-x. 1 1974 Apr  6 05:55 axtChain/loadRBest.csh
-rwxrwxr-x. 1  583 Apr  6 05:55 rBestCleanUp.bash

Notes from Hiram's Talks (by Dan) 4/21 and 4/28/21

  • LiftOver file creation, LASTZ Run, SameSpeciesLiftOver*

SameSpeciesLiftOver, made for… same species with near identical assemblies, often not great for many assemblies, somewhat antiquated. Hardly used, done with BLAT because expects high similarity, very quick to run. Must be the same biological sample, ie. hg19->hg38, mm10->mm39. It’s one command, fairly simple.

LastZ Makedoc lives here:


Tuning was a thing tried that didn’t work, should be ignored.

First you go to the makeDoc, change the query name, run a “screen” similar to nohup (old school), copy the commands onto the ku, Screen basics (they stay in the background)

 $ screen -ls
 $screen -S demoScreen #starts screen

Ctr A, ctr D to detach screen

 $ screen -r -d demoScreen  #go back to a detached screen

If you exit with the exit command, it’ll terminate your screen prematurely

Going through hg38 -> seaturtle KU is used by browser engineers, mostly hiram

  set -beEu -o pipefail

If anything fails, hard exit First steps are making dir

  mkdir /hive/data/genomes/hg38/bed/lastzCheMyd1.2015-02-06

Set version of lastz with dir BLASTZ=(v1.04.03) The score matrix for the alignment is listed in a comment here

  # default BLASTZ_Q score matrix

Documented in a printf now, eg human vs X. tropicalis, can’t use single quote within previously done with a “hereIs” doc setting params

  • 3 params (Go to one recently done and copy that, or go to shell script)
    • Primates to prim
    • Prim to mammal
    • Any to any, very distant
      • These look like BLASTZ_A
  • Target init stays the same, query is what changes.
  • Chunk is how to split each seq: LASTZ handles 40Mbp target vs 20Mbp query.
  • Limit is how many seqs (contigs) you fit into each limit, eg. 3 hg38 and 800 turtle
    • This choice is important for how many independent jobs go into the cluster, should be between 10k- 100,000
    • Num pieces target x number of query pieces
  • Run script first step to calculate how many jobs, see (
    • CrisprAll runs 5M jobs and 1 week to run
  • seq_LAP
    • how much overlap between sequences, eg. 10k for target and 0 for query
    • Prevent artificial breaks
  • BASE is where work is done
  • tempDir is ?? fastest file transfer dir

Run the command (14hr)

  • Produces regular and syntenic chain/net, only Regular shown
  • Syntenic going in order on chromosome, in synteny, filter of those so only those that go in same order remain,

Run (6hr)

  • If there’s a best align, this gets made in recipBest

Do the reverse “swap” doBlastChainNet (2hr)

  • produces reg and syntenic chain/net

For assembly hubs:

  • Different dir initialization, (BASE)
  • Different doBlastChainNet command.
  • Bunch of exports, setting variables also stored in BASE dir
  • Sed line annotates a comment in the makeDoc with bases in intersection
  • Mkdir in the assem hub dir, do the swap command, when you’re in swap land you set -target2Bit with query files 2bit and chrom.sizes

This human->sheep took nearly 600 minutes, (100hrs) “You can count on a day to run”

For genome without assembly Hub:

  • All it takes is 2bit and chom.sizes
  • You can’t view it without an assembly

How to move around assembly hubs

  $ goto GCF_002742125, goes to proper dir

Multiple alignments Downstream gets created from pairwise chain/net, though not always from “regular” one, which confuses users.

4/28/21 Demo

Demo rn7 to bosTau9

Smaller contig is target, larger is query. Figure this using wc -l on *.sizes file

Copy similar makeDoc from similar org (See vim tutorial wiki):

  • Mark line with (m + a)
  • “ a ‘ a ------- yank lines and paste them into “lastzRuns.txt”
  • Search and replace all db names, dates, etc
  • 10s --- 10 letter substitute
  • . ---- repeat last command

After you mod the file, run the command to put things into DEF folder Run some command (stop=partition), then check the number of job. N times M should be <100k, hiram uses “bc” to do the math.

Make a screen, called rn7, run the timed command.

  • It logs into KU and runs the partitioned jobs with priority “nice”
  • Crt A, crt D to end screen


  • Parasol batch fails
    • Go to dir where it was working, look at it, debug error manually

See Recorded Demo here:

The new streamline pairLastz script

The pairLastz script streamlines making the DEF file, running, running, and the swap into one script.

  usage: <target> <query> <tClade> <qClade>

Before starting, add a file to your hgwdev home directory:


which is a single line of an email address where you would like to receive email from processes on hgwdev. You may already be receiving email from hgwdev, but with this file, you can control where it goes exactly. The script will send an email to your user name on hgwdev when it completes. (Helpful)

The script determines the target, query, clades, and full GC assembly hub name to run the pairLastz script. You can then skip the "Determining target and query" and the "Determining clade" steps.

  python3 ~/kent/src/utils/qa/ -a1 hg38 -a2 GCF_001704415.1
  screen -S 20220323
  time (~/kent/src/hg/utils/automation/ hg38 GCF_001704415.1_ARS1 primate mammal) >  hg38.GCF_001704415.1_20220323.log 2>&1 &

Determining target and query

Use the following script to determine target and query (which are inputs to the alignment script). Here is an example

  python3 /hive/users/gperez2/liftOver/ -a1 calJac4 -a2 rheMac10
  rheMac10 is target
  calJac4 is query

<-- Extra Details --> You can use the scoring scheme to determine which should be the target and which would be the query:

  1. 1 point for largest genome
  2. 1 point for the lowest number of contigs/scaffolds/chromosomes
  3. 1 point for lowest N50 number
  4. 1 point for largest N50 sequence

All of the measurements can be obtained with the script on the chrom.sizes for the genomes. The higher scoring genome should be the target. In the case of a tie, then the largest genome is the target.

If one of the assemblies is an assembly hub and available on GenArk, you can go to the directory using the following command:

$ goto GCF_002742125.1

If you don't have the goto command, you can then add the following to your .bashrc file:

function goto() {
export asmId=$1

export gcX=`echo "$asmId" | cut -c1-3`
export d0=`echo "$asmId" | cut -c5-7`
export d1=`echo "$asmId" | cut -c8-10`
export d2=`echo "$asmId" | cut -c11-13`

export destDir=""

if [ "${gcX}" = "GCF" ]; then

# printf "$destDir\n" 1>&2
export cdDir=`ls -d ${destDir}/${asmId}*`

if [ -d "${cdDir}" ]; then
  printf "cd $cdDir\n" 1>&2
  cd "$cdDir"
  printf "# can not find ${cdDir}\n" 1>&2

Determining clade

You need to specify clade of the target and query organisms that control the alignment scoring scheme (thanks Hiram!). There are 3 categories of clade options. You want to use the most specific.


Check machines on ku

Check if machines are down or backed up with job queries:

ssh ku
parasol status
parasol list machines
parasol list batches

Exit from ku and move to a screen

Moving to a screen

You can check your screens with the following command:

screen -list

You can make a new screen with the following command:

screen -S screenName

You can exit the screen by doing Ctrl-a then Ctrl-d

You can reattach to the screen by the following command:

screen -r -d screenName


The script can be ran from anywhere on dev. Hiram and Gerardo have been running the script from the automation directory (~/kent/src/hg/utils/automation/). The following command will write the status of the script to a file and be used to update the makeDoc:

time (~/kent/src/hg/utils/automation/ \
target query tClade qClade) \
> fileName.log 2>&1 &

You can check the status of the alignment by doing a tail on the fileName.log file.

You can see the following fileName.log as an example of what to expect:


If the run gets killed before completing the alignment, then contact Hiram to see if some files can be salvaged.

Updating makeDoc

After the script finishes running, you should update the makeDoc.

The makeDoc’s can be found in:


If the liftOver files are for two GenArk assemblies, you can update the generic makedoc:


The following is an example on what goes on a makeDoc:

git show 1054d4e3c1d6bdb3d2799860d0eca70dfd35447c

# LASTZ human hg19 (DONE - 2021-09-30 - Hiram)

# should be able to run this from anywhere, this time it was run from:
    cd /hive/data/genomes/mm39/bed

  time (~/kent/src/hg/utils/automation/ mm39 hg19 mammal primate) \
      > mm39.hg19.log 2>&1

    grep -w real mm39.hg19.log | tail -1 | sed -e 's/^/    # /;'
    # real    1200m57.924s

    # this command outputs this makeDoc text:

    cat lastz.hg19/makeDoc.txt

# LASTZ Mouse Mm39 vs. Human Hg19 (DONE - 2021-09-30 - Hiram)
    mkdir /hive/data/genomes/mm39/bed/lastzHg19.2021-09-30
    cd /hive/data/genomes/mm39/bed/lastzHg19.2021-09-30

    printf '# Human Hg19 vs. Mouse Mm39

# TARGET: Mouse Mm39

# QUERY: Human Hg19


' > DEF

    time (~/kent/src/hg/utils/automation/  -verbose=2 `pwd`/DEF -syntenicNet \
        -workhorse=hgwdev -smallClusterHub=hgwdev -bigClusterHub=ku \
        -chainMinScore=3000 -chainLinearGap=medium) > do.log 2>&1
    grep -w real do.log | sed -e 's/^/    # /;'
    # real      474m8.118s
    #     # real        474m8.118s
    #     # real        370m29.622s
    # real      844m37.788s

    sed -e 's/^/    # /;' fb.mm39.chainHg19Link.txt
    # 938444606 bases of 2654624157 (35.351%) in intersection

    ### and for the swap

    cd /hive/data/genomes/hg19/bed/blastz.mm39.swap

   time (~/kent/src/hg/utils/automation/   -swap -verbose=2 \
      /hive/data/genomes/mm39/bed/lastzHg19.2021-09-30/DEF -swapDir=`pwd` \
      -syntenicNet -workhorse=hgwdev -smallClusterHub=hgwdev -bigClusterHub=ku \
         -chainMinScore=3000 -chainLinearGap=medium) > swap.log 2>&1

    grep -w real swap.log | sed -e 's/^/    # /;'
    # real      57m17.328s

    sed -e 's/^/    # /;' fb.hg19.chainMm39Link.txt
    # 969322683 bases of 2991710746 (32.400%) in intersection
    sed -e 's/^/    # /;' fb.hg19.chainSynMm39Link.txt
    # 921405754 bases of 2991710746 (30.799%) in intersection

    time (~/kent/src/hg/utils/automation/  -load -workhorse=hgwdev -buildDir=`pwd` \
       hg19 mm39) > rbest.log 2>&1

    grep -w real rbest.log | sed -e 's/^/    # /;'
    # real      299m2.449s

    sed -e 's/^/    # /;' fb.hg19.chainRBest.Mm39.txt
    # 892863094 bases of 2991710746 (29.845%) in intersection


Push it to the RR

You should be able to see your files at a location like this for genArk hubs (similar for native genomes):

ls /usr/local/apache/htdocs-hgdownload/goldenPath/GCF/001/704/415/GCF_001704415.1/liftOver

Native databases to native databases chain files can be pushed to the RR by a push request:


Native databases to genArk genomes chain files can be pushed to the RR by a push request:


GenArk genomes to native databases chain files can be pushed by running some commands. The commands can found in Pushing_to_the_RR

GenArk genomes to GenArk genomes chain files can be pushed by running some commands. The commands can found in Pushing_to_the_RR