andras86
commented
5 years ago As I assume it's not due to massive insert length, it might have to do with read names. Can you put the first few lines of those R1 and R2 fastq files in here? I already don't like the way those filenames look, they don't just differ in R1/R2 but their prefixes are totally different. Could be the case for the read IDs inside them as well. Since OptiType processes two single-end mapped files and pairs them up later based on the read IDs, if they have different prefixes for R1 and R2 reads, it won't be able to pair them. If that's the case, you'll have to hack something in to make it work. I can help you with that after the weekend. Btw, have you actually checked if those fastq files belong together? It would be such unusual practice to give corresponding R1 and R2 files different prefixes...
toddcreasy
BioLaoXu
Hi,
I'm trying to map and call alleles on fastq files from TCGA. However, out of the 400 samples I've run, only a very small number were called. The failed ones (as indicated from the output below) seem to have a possible read mapping problem and thus cbc can't solve. Is there something I'm missing from the log output that would indicate a problem? If so, how might I fix it?
I'm using the latest versions of razers3 and optitype.
mapping with 4 threads...
0:00:01.50 Mapping C500.TCGA-BT-A42B-10A-01D-A23K-08.3_gdc_realn_R1.fastq to GEN reference...
0:29:46.60 Mapping C500.TCGA-XF-A9T2-10A-01D-A42H-08.2_gdc_realn_R2.fastq to GEN reference...
0:44:43.01 Generating binary hit matrix. 0:44:43.09 Loading /ts18/ngs/studies/TCGA_BLCA_Mutect/optitype/2018_12_14_11_14_41_1.bam started. Number of HLA reads loaded (updated every thousand): 1K...2K...3K...4K...5K...6K...7K...8K.../Biomarker/ngs/software/OptiType/OptiType-1.3.2/hlatyper.py:239: FutureWarning: from_items is deprecated. Please use DataFrame.from_dict( dict(items), ...) instead. DataFrame.from_dict(OrderedDict(items)) may be used to preserve the key order. pos_df = pd.DataFrame.from_items(iter(hits.items())).T
0:44:47.81 8604 reads loaded. Creating dataframe... 0:44:48.28 Dataframes created. Shape: 8604 x 11179, hits: 2717490 (2717490), sparsity: 1 in 35.39 0:44:48.89 Loading /ts18/ngs/studies/TCGA_BLCA_Mutect/optitype/2018_12_14_11_14_41_2.bam started. Number of HLA reads loaded (updated every thousand): 1K...2K...3K...4K...5K...6K...7K...8K... 0:44:52.14 8222 reads loaded. Creating dataframe... 0:44:52.59 Dataframes created. Shape: 8222 x 11179, hits: 1917861 (1917861), sparsity: 1 in 47.93 0:44:53.58 Alignment pairing completed. 0 paired, 16826 unpaired, 0 discordant
WARNING: Less than 10% of reads could be paired. Consider an appropriate unpaired_weight setting in your config file (currently 0.000), because you may need to resort to using u npaired reads.
0:44:57.43 temporary pruning of identical rows and columns
0:44:57.44 Size of mtx with unique rows and columns: (0, 1) 0:44:57.44 determining minimal set of non-overshadowed alleles
0:44:57.45 Keeping only the minimal number of required alleles (1,)
0:44:57.45 Creating compact model...
starting ilp solver with 4 threads...
0:44:57.45 Initializing OptiType model... WARNING: Constant objective detected, replacing with a placeholder to prevent solver failure. Welcome to the CBC MILP Solver Version: 2.9.9 Build Date: Oct 13 2018
command line - /home/kgvx167/anaconda3/bin/cbc -threads 4 -printingOptions all -import /home/kgvx167/tmpolFvmh.pyomo.lp -stat=1 -solve -solu /home/kgvx167/tmpolFvmh.pyomo.soln ( default strategy 1) threads was changed from 0 to 4 Option for printingOptions changed from normal to all CoinLpIO::readLp(): Maximization problem reformulated as minimization Presolve 0 (-4) rows, 0 (-3) columns and 0 (-5) elements Statistics for presolved model Original problem has 1 integers (1 of which binary)
Problem has 0 rows, 0 columns (0 with objective) and 0 elements Column breakdown: 0 of type 0.0->inf, 0 of type 0.0->up, 0 of type lo->inf, 0 of type lo->up, 0 of type free, 0 of type fixed, 0 of type -inf->0.0, 0 of type -inf->up, 0 of type 0.0->1.0 Row breakdown: 0 of type E 0.0, 0 of type E 1.0, 0 of type E -1.0, 0 of type E other, 0 of type G 0.0, 0 of type G 1.0, 0 of type G other, 0 of type L 0.0, 0 of type L 1.0, 0 of type L other, 0 of type Range 0.0->1.0, 0 of type Range other, 0 of type Free Continuous objective value is 0 - 0.00 seconds Cgl0004I processed model has 0 rows, 0 columns (0 integer (0 of which binary)) and 0 elements Cbc3007W No integer variables - nothing to do Cuts at root node changed objective from 0 to -1.79769e+308 Probing was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds) Gomory was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds) Knapsack was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds) Clique was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds) MixedIntegerRounding2 was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds) FlowCover was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds) TwoMirCuts was tried 0 times and created 0 cuts of which 0 were active after adding rounds of cuts (0.000 seconds)
Result - Optimal solution found
Objective value: 0.00000000 Enumerated nodes: 0 Total iterations: 0 Time (CPU seconds): 0.02 Time (Wallclock seconds): 0.00
Total time (CPU seconds): 0.04 (Wallclock seconds): 0.01
/home/kgvx167/anaconda3/envs/python27/lib/python2.7/site-packages/pandas/core/series.py:851: FutureWarning: Passing list-likes to .loc or [] with any missing label will raise KeyError in the future, you can use .reindex() as an alternative.
See the documentation here: https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike return self.loc[key]
0:44:57.78 Result dataframe has been constructed...