Error : mixcr line 215: 20652 Killed $java -Dmi.license.file="$dir/mi.license" -D${app}.path="$dir" -D${app}.command=${app} "${javaArgs[@]}" -jar "$jar" "${appArgs[@]}"

[liu9756]

Hi! I use mixcr analyze 10x-sc-xcr-vdj command to process my files, however, in refineTagsAndSort section, I am informed that /users/PAS2177/liu9756/mixcr/mixcr: line 215: 20652 Killed $java -Dmi.license.file="$dir/mi.license" -D${app}.path="$dir" -D${app}.command=${app} "${javaArgs[@]}" -jar "$jar" "${appArgs[@]}"

The following is the command output:

` Average R1 nucleotides trimmed right: 8.506156640558773E-6
Tag parsing report:
Execution time: 0ns
Total reads: 205850900
Matched reads: 205850900 (100%)
Projection +R1 +R2: 205850900 (100%)
For variant 0:
For projection +R1 +R2:
CELL:Left position: 0
UMI:Left position: 16
CELL:Right position: 16
UMI:Right position: 26
R2:Left position: 0
Variants: 0
Cost: 0
CELL length: 16
UMI length: 10
R2 length: 101

mixcr refineTagsAndSort <<<<<<<<<<<<<<<<<
Running:
mixcr refineTagsAndSort --report results_10x.refine.report.txt --json-report results_10x.refine.report.json results_10x.vdjca results_10x.refined.vdjca
Correction will be applied to the following tags: CELL, UMI
Sorting will be applied to the following tags: CELL, UMI
The following whitelist will be used for CELL: WhitelistFromAddress(address=builtin:737K-august-2016)
Initialization: progress unknown
Initialization: 0.9%
Initialization: 11% ETA: 00:03:24
Initialization: 21.5% ETA: 00:10:16
Initialization: 22.6% ETA: 03:37:25
Initialization: 25.2% ETA: 01:35:36
Initialization: 27.4% ETA: 01:18:30
Initialization: 28.8% ETA: 01:56:00
/users/PAS2177/liu9756/mixcr/mixcr: line 215: 20652 Killed $java -Dmi.license.file="$dir/mi.license" -D${app}.path="$dir" -D${app}.command=${app}
"${javaArgs[@]}" -jar "$jar" "${appArgs[@]}"
[liu9756@owens-login04 NEW_BCR_S7]$
`

[mizraelson]

How much memory did you use? It seems like the process was killed due to the lack of RAM.

[liu9756]

100G

[liu9756]

I will try 200G

[mizraelson]

Sometimes for a very large datasets 100G might not be enough. Let's see if 200G will do.