很贵的FHIT基因综合讨论组

微基因的HLA分型太粗糙，于是我用第三方工具再做了一遍

这下可以得到6位精度的HLA分型了，read count > 50的都能分出来。
工具：arcasHLA，你还需要bwa, samtools等等等
硬件：最好核多内存大，例如我有256G内存，28核cpu，还需要足够快的硬盘。

有谁缺少HLA报告的可以自己做。

[alignment] Observed HLA genes:
                gene          abundance    read count    classes
                HLA-A             0.07%           175        104
                HLA-B             0.06%           140        103
                HLA-C             0.06%           153        101
                HLA-DMA           0.12%           209          3
                HLA-DMB           0.13%           237          3
                HLA-DOA           0.13%           214         26
                HLA-DOB           0.16%           291         10
                HLA-DPA1          0.11%           188         28
                HLA-DPA2          0.13%           211          7
                HLA-DPB1          0.10%           178         97
                HLA-DPB2          0.11%           186         10
                HLA-DQA1          0.09%           154         40
                HLA-DQA2          0.10%           164         19
                HLA-DQB1          0.16%           281         89
                HLA-DRA           0.11%           189          8
                HLA-DRB1          0.11%           197         33
                HLA-DRB2          0.04%            49          1
                HLA-DRB3          0.04%            66          7
                HLA-DRB4          0.04%            74         11
                HLA-DRB5          0.00%             1          1
                HLA-DRB7          0.04%            72          1
                HLA-E             0.08%           202         37
                HLA-F             0.09%           197         13
                HLA-G             0.09%           207         39
                HLA-H             0.02%            49         12
                HLA-HFE           0.12%           271          1
                HLA-J             0.08%           199          9
                HLA-K             0.04%            88         21
                HLA-L            65.88%        160367          2
                HLA-N             0.02%             6          1
                HLA-S             0.07%            40          4
                HLA-T            31.28%         31887          3
                HLA-U             0.00%             2          2
                HLA-V             0.06%            74          3
                HLA-W             0.25%           519         19
                HLA-Y             0.01%            14          3

2019-12-21 • IP属地中国

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5 个回复

[已注销]

膜拜大佬……
管理员可以看到嘛？既然可以提供，那么给我们测过全基因组的报告升级一下呗。

温柔的RYR2基因

放个github链接呀

费力科思 - WeGene勤杂工

需要平衡准确性和精度

oliegene

按楼主的操作了，直接跑docker容器很爽，宿主机器配置没那么高，cpu i7-8700K RAM 32G 跑的蛮快
github 链接：https://github.com/RabadanLab/arcasHLA

容器资源占用，峰值RAM占用不超8G

CONTAINER ID NAME CPU % MEM USAGE / LIMIT MEM % NET I/O BLOCK I/O PIDS
eb98d6957541 hla-ce 0.00% 4.27GiB / 31.36GiB 13.62% 1.6GB / 13MB 20.5GB / 16.4GB 2

结果日志

[alignment] Processing pseudoalignment
[alignment] Pseudoaligned 49794 reads to HLA reference
[alignment] 49581 reads mapped to a single HLA gene
[alignment] Observed HLA genes:
gene abundance read count classes
HLA-A 0.21% 113 74
HLA-B 0.20% 105 74
HLA-C 0.26% 141 91
HLA-DMA 0.53% 200 2
HLA-DMB 0.53% 204 3
HLA-DOA 0.38% 140 13
HLA-DOB 0.55% 220 10
HLA-DPA1 0.40% 153 32
HLA-DPA2 0.45% 161 7
HLA-DPB1 0.45% 168 98
HLA-DPB2 0.46% 173 9
HLA-DQA1 0.45% 167 49
HLA-DQA2 0.36% 133 22
HLA-DQB1 0.81% 317 101
HLA-DRA 0.35% 129 4
HLA-DRB1 0.48% 186 10
HLA-DRB3 0.01% 3 1
HLA-DRB4 0.38% 146 13
HLA-DRB7 0.34% 131 1
HLA-E 0.37% 196 91
HLA-F 0.45% 226 13
HLA-G 0.35% 172 60
HLA-H 0.06% 30 15
HLA-HFE 88.60% 44948 3
HLA-J 0.38% 204 40
HLA-K 0.18% 97 6
HLA-L 0.25% 134 4
HLA-N 0.03% 2 1
HLA-P 0.52% 185 7
HLA-S 0.09% 12 4
HLA-T 0.30% 66 8
HLA-U 0.02% 2 1
HLA-V 0.22% 56 3
HLA-W 0.58% 261 14
--------------------------------------------------------------------------------
[genotype] Genotyping parameters:
population: prior
minimum count: 40
max iterations: 1000
tolerance: 1e-06
drop iterations: 20
drop threshold: 0.1
zygosity threshold: 0.15
--------------------------------------------------------------------------------
[genotype] Genotyping HLA-A
[genotype] 113 reads aligned to HLA-A in 74 classes
[genotype] Top 10 alleles by undivided read count:
allele read count
A*24:459 53
A*24:443 46
A*24:473Q 46
A*24:02:01 45
A*24:02:101 45
A*24:02:103 45
A*24:02:108 45
A*24:02:116 45
A*24:02:125 45
A*24:02:127 45

[genotype] Quantifying allele transcript abundance
[genotype] EM converged after 10 iterations

[genotype] Top alleles by abundance:
allele abundance
A*24:459 32.83%
A*26:01:01 22.55%
A*26:01:64 9.73%
A*24:443 5.34%
A*24:473Q 5.17%
A*03:01:01 4.28%

[genotype] Pairs by % explained reads:
allele pair explained
A*24:459, A*26:01:64 79.65%
A*24:443, A*26:01:64 73.45%
A*24:473Q, A*26:01:64 73.45%
A*03:01:01, A*24:459 51.33%
A*24:443, A*24:459 49.56%
A*24:459, A*24:473Q 49.56%
A*03:01:01, A*24:443 45.13%
A*03:01:01, A*24:473Q 45.13%
A*24:443, A*24:473Q 41.59%
A*03:01:01, A*26:01:64 38.05%

[genotype] Checking zygosity
[genotype] Likely heterozygous: minor/major nonshared count 0.71

[genotype] Most likely genotype explaining 90 reads:
A*24:459
A*26:01:01
--------------------------------------------------------------------------------
[genotype] Genotyping HLA-B
[genotype] 105 reads aligned to HLA-B in 74 classes
[genotype] Top 10 alleles by undivided read count:
allele read count
B*15:01:01 48
B*18:01:48 48
B*37:04:02 47
B*15:535 44
B*46:01:01 44
B*46:01:31 44
B*46:66 44
B*46:82 44
B*46:89 44
B*46:90 44

[genotype] Quantifying allele transcript abundance
[genotype] EM converged after 26 iterations

[genotype] Top alleles by abundance:
allele abundance
B*18:01:48 24.07%
B*15:01:01 16.18%
B*07:44N 8.74%
B*18:01:31 7.22%
B*40:06:01 4.23%
B*40:06:04 4.23%
B*40:06:17 4.23%
B*40:06:20 4.23%
B*40:06:26 4.23%
B*40:06:27 4.23%
B*46:01:01 3.77%
B*46:01:31 3.77%
B*15:296 3.25%
B*15:245:01 2.62%
B*35:420 2.61%
B*15:266 2.41%

[genotype] Pairs by % explained reads:
allele pair explained
B*18:01:48, B*40:06:04 70.48%
B*15:01:01, B*40:06:04 67.62%
B*46:01:01, B*40:06:04 63.81%
B*15:296, B*40:06:04 61.90%
B*15:245:01, B*40:06:04 60.00%
B*07:44N, B*18:01:48 59.05%
B*15:266, B*40:06:04 59.05%
B*15:01:01, B*18:01:48 58.10%
B*07:44N, B*15:01:01 56.19%
B*18:01:48, B*46:01:01 54.29%
B*07:44N, B*46:01:01 52.38%
B*15:296, B*18:01:48 52.38%
B*07:44N, B*15:296 50.48%
B*15:245:01, B*18:01:48 50.48%
B*18:01:48, B*35:420 50.48%
B*15:266, B*18:01:48 49.52%
B*07:44N, B*15:245:01 48.57%
B*07:44N, B*15:266 47.62%
B*15:01:01, B*35:420 47.62%
B*15:01:01, B*46:01:01 47.62%
B*15:01:01, B*15:245:01 46.67%
B*15:01:01, B*15:266 46.67%
B*15:01:01, B*15:296 46.67%
B*35:420, B*46:01:01 43.81%
B*15:245:01, B*46:01:01 42.86%
B*15:266, B*46:01:01 42.86%
B*15:296, B*46:01:01 42.86%
B*35:420, B*40:06:04 42.86%
B*15:296, B*35:420 41.90%
B*15:245:01, B*15:296 40.95%
B*15:266, B*15:296 40.95%
B*15:245:01, B*35:420 40.00%
B*15:245:01, B*15:266 39.05%
B*15:266, B*35:420 39.05%
B*07:44N, B*40:06:04 37.14%
B*07:44N, B*35:420 26.67%

[genotype] Checking zygosity
[genotype] Likely heterozygous: minor/major nonshared count 0.55

[genotype] Most likely genotype explaining 74 reads:
B*18:01:31
B*40:06:01
--------------------------------------------------------------------------------
省略很多……

dfdtc

目前情况是，这个工具做出来和官方给的报告有些项目差的很多，比如我测出来的HLA，有不少在第一位上都出现不符合的情况，具体什么情况....目前难以验证

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微基因的HLA分型太粗糙，于是我用第三方工具再做了一遍

与内容相关的链接

5 个回复