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===> Where do you most often perform bioinformatics analysis <===

1	Personal computer (laptop/desktop) 
2	Lab server
3	Departmental server
4	University server/cluster
5	Cloud
6	Other

===> Type of problems <===

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Writing a program for efficient matrix multiplication is tricky. A naive implementation usually looks like this (I will use a square matrix for simplicity):

for (i = 0; i < n; ++i)
  for (j = 0; j < n; ++i)
    for (k = 0, m[i][j] = 0.; k < n; ++i)
      m[i][j] += a[i][k] * b[k][j];

The problem is the inner loop a[i][k] * b[k][j] where b[k][j] and b[k+1][j] are not adjacent in memory. This leads to frequent cache misses for large matrices. The better implementation is to transpose matrix b. The implementation will look like:

for (i = 0; i < n; ++i) // transpose

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var max_leftover = 0.1, max_diff = 0.05, min_mapq = 20;

var file = arguments.length == 0? new File() : new File(arguments[0]);
var buf = new Bytes();

var re = /(\d+)([MIDSH])/g;
var decoy = {};
while (file.readline(buf) >= 0) {
	var m, line = buf.toString();
	if ((m = /^@SQ.*\tSN:(\S+).*\tLN:(\d+)/.exec(line)) != null) {

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#include <stdlib.h>
#include <unistd.h>
#include <string.h>
#include <stdio.h>
#include <time.h>

const char *mm_colors = "RGBWOPYSE";
const char *mm_numbers = "123456789";

long *mm_enumerate(int m, int n, int rep, long *_z) // m colors, n columns

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Querying Genotypes with Standard SQL

This document demonstrates that we can use three conceptual SQL tables for variant annotations, sample phenotypes and genotypes, respectively, to achieve flexible query of genotype data. The tables are conceptual in that they are primarily used for constructing queries but not for storing real data as they are not efficient enough for large-scale data.

We will use an example to show the structure of the three tables and how to query data in standard SQL. You can find all the SQL statements in

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# VQSR for single human sample mapped to b37. Usage:
#
#   make -f vqsr-b37.mak prefix=my-vcf-prefix
#
# For this to work, the input VCF must be named as "my-vcf-prefix.vcf" and
# there must be "GenomeAnalysisTK.jar" and "b37" directory from the GATK
# resource bundle in the working directory.
#
# References:
#

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#
# generate 01compositional.bed.gz
#

# low-complexity by mDUST
mdust hs37d5.fa -c -w7 -v28 \
  | hs37d5.mdust-w7-v28.txt \
  | cut -f1,3,4 \
  | gawk -vOFS="\t" '{--$2;print}' \
  | bgzip > 01compositional/hs37d5.mdust-w7-v28.bed.gz

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/* To compile this program, you need rld0.{h,c} from ropebwt2 or fermi2:
 *
 *   gcc -g -O2 -Wall -o occ1 rld0.c occ1.c
 */

#include <string.h>
#include <stdint.h>
#include <stdio.h>
#include "rld0.h"

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#include <stdlib.h>
#include <unistd.h>
#include <stdio.h>
#include <stdint.h>
#include <pthread.h>

#define KO_BUFSIZE 0x40000

typedef struct {
	FILE *fp_in, *fp_out;

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#include <bzlib.h>
#include <zlib.h>
#include <stdio.h>
#include <stdlib.h>

typedef struct zfile_s {
	int is_bz;
	gzFile fpz;
	FILE *fp; // for bzip2
	BZFILE *fpbz;